Price Action Smart Money Concepts [BigBeluga]THE SMART MONEY CONCEPTS Toolkit
The Smart Money Concepts [ BigBeluga ] is a comprehensive toolkit built around the principles of "smart money" behavior, which refers to the actions and strategies of institutional investors.
The Smart Money Concepts Toolkit brings together a suite of advanced indicators that are all interconnected and built around a unified concept: understanding and trading like institutional investors, or "smart money." These indicators are not just randomly chosen tools; they are features of a single overarching framework, which is why having them all in one place creates such a powerful system.
This all-in-one toolkit provides the user with a unique experience by automating most of the basic and advanced concepts on the chart, saving them time and improving their trading ideas.
Real-time market structure analysis simplifies complex trends by pinpointing key support, resistance, and breakout levels.
Advanced order block analysis leverages detailed volume data to pinpoint high-demand zones, revealing internal market sentiment and predicting potential reversals. This analysis utilizes bid/ask zones to provide supply/demand insights, empowering informed trading decisions.
Imbalance Concepts (FVG and Breakers) allows traders to identify potential market weaknesses and areas where price might be attracted to fill the gap, creating opportunities for entry and exit.
Swing failure patterns help traders identify potential entry points and rejection zones based on price swings.
Liquidity Concepts, our advanced liquidity algorithm, pinpoints high-impact events, allowing you to predict market shifts, strong price reactions, and potential stop-loss hunting zones. This gives traders an edge to make informed trading decisions based on liquidity dynamics.
🔵 FEATURES
The indicator has quite a lot of features that are provided below:
Swing market structure
Internal market structure
Mapping structure
Adjustable market structure
Strong/Weak H&L
Sweep
Volumetric Order block / Breakers
Fair Value Gaps / Breakers (multi-timeframe)
Swing Failure Patterns (multi-timeframe)
Deviation area
Equal H&L
Liquidity Prints
Buyside & Sellside
Sweep Area
Highs and Lows (multi-timeframe)
🔵 BASIC DEMONSTRATION OF ALL FEATURES
1. MARKET STRUCTURE
The preceding image illustrates the market structure functionality within the Smart Money Concepts indicator.
➤ Solid lines: These represent the core indicator's internal structure, forming the foundation for most other components. They visually depict the overall market direction and identify major reversal points marked by significant price movements (denoted as 'x').
➤ Internal Structure: These represent an alternative internal structure with the potential to drive more rapid market shifts. This is particularly relevant when a significant gap exists in the established swing structure, specifically between the Break of Structure (BOS) and the most recent Change of High/Low (CHoCH). Identifying these formations can offer opportunities for quicker entries and potential short-term reversals.
➤ Sweeps (x): These signify potential turning points in the market where liquidity is removed from the structure. This suggests a possible trend reversal and presents crucial entry opportunities. Sweeps are identified within both swing and internal structures, providing valuable insights for informed trading decisions.
➤ Mapping structure: A tool that automatically identifies and connects significant price highs and lows, creating a zig-zag pattern. It visualizes market structure, highlights trends, support/resistance levels, and potential breakouts. Helps traders quickly grasp price action patterns and make informed decisions.
➤ Color-coded candles based on market structure: These colors visually represent the underlying market structure, making it easier for traders to quickly identify trends.
➤ Extreme H&L: It visualizes market structure with extreme high and lows, which gives perspective for macro Market Structure.
2. VOLUMETRIC ORDER BLOCKS
Order blocks are specific areas on a financial chart where significant buying or selling activity has occurred. These are not just simple zones; they contain valuable information about market dynamics. Within each of these order blocks, volume bars represent the actual buying and selling activity that took place. These volume bars offer deeper insights into the strength of the order block by showing how much buying or selling power is concentrated in that specific zone.
Additionally, these order blocks can be transformed into Breaker Blocks. When an order block fails—meaning the price breaks through this zone without reversing—it becomes a breaker block. Breaker blocks are particularly useful for trading breakouts, as they signal that the market has shifted beyond a previously established zone, offering opportunities for traders to enter in the direction of the breakout.
Here's a breakdown:
➤ Bear Order Blocks (Red): These are zones where a lot of selling happened. Traders see these areas as places where sellers were strong, pushing the price down. When the price returns to these zones, it might face resistance and drop again.
➤ Bull Order Blocks (Green): These are zones where a lot of buying happened. Traders see these areas as places where buyers were strong, pushing the price up. When the price returns to these zones, it might find support and rise again.
These Order Blocks help traders identify potential areas for entering or exiting trades based on past market activity. The volume bars inside blocks show the amount of trading activity that occurred in these blocks, giving an idea of the strength of buying or selling pressure.
➤ Breaker Block: When an order block fails, meaning the price breaks through this zone without reversing, it becomes a breaker block. This indicates a significant shift in market liquidity and structure.
➤ A bearish breaker block occurs after a bullish order block fails. This typically happens when there's an upward trend, and a certain level that was expected to support the market's rise instead gives way, leading to a sharp decline. This decline indicates that sellers have overcome the buyers, absorbing liquidity and shifting the sentiment from bullish to bearish.
Conversely, a bullish breaker block is formed from the failure of a bearish order block. In a downtrend, when a level that was expected to act as resistance is breached, and the price shoots up, it signifies that buyers have taken control, overpowering the sellers.
3. FAIR VALUE GAPS:
A fair value gap (FVG), also referred to as an imbalance, is an essential concept in Smart Money trading. It highlights the supply and demand dynamics. This gap arises when there's a notable difference between the volume of buy and sell orders. FVGs can be found across various asset classes, including forex, commodities, stocks, and cryptocurrencies.
FVGs in this toolkit have the ability to detect raids of FVG which helps to identify potential price reversals.
Mitigation option helps to change from what source FVGs will be identified: Close, Wicks or AVG.
4. SWING FAILURE PATTERN (SFP):
The Swing Failure Pattern is a liquidity engineering pattern, generally used to fill large orders. This means, the SFP generally occurs when larger players push the price into liquidity pockets with the sole objective of filling their own positions.
SFP is a technical analysis tool designed to identify potential market reversals. It works by detecting instances where the price briefly breaks a previous high or low but fails to maintain that breakout, quickly reversing direction.
How it works:
Pattern Detection: The indicator scans for price movements that breach recent highs or lows.
Reversal Confirmation: If the price quickly reverses after breaching these levels, it's identified as an SFP.
➤ SFP Display:
Bullish SFP: Marked with a green symbol when price drops below a recent low before reversing upwards.
Bearish SFP: Marked with a red symbol when price rises above a recent high before reversing downwards.
➤ Deviation Levels: After detecting an SFP, the indicator projects white lines showing potential price deviation:
For bullish SFPs, the deviation line appears above the current price.
For bearish SFPs, the deviation line appears below the current price.
These deviation levels can serve as a potential trading opportunity or areas where the reversal might lose momentum.
With Volume Threshold and Filtering of SFP traders can adjust their trading style:
Volume Threshold: This setting allows traders to filter SFPs based on the volume of the reversal candle. By setting a higher volume threshold, traders can focus on potentially more significant reversals that are backed by higher trading activity.
SFP Filtering: This feature enables traders to filter SFP detection. It includes parameters such as:
5. LIQUIDITY CONCEPTS:
➤ Equal Lows (EQL) and Equal Highs (EQH) are important concepts in liquidity-based trading.
EQL: A series of two or more swing lows that occur at approximately the same price level.
EQH: A series of two or more swing highs that occur at approximately the same price level.
EQLs and EQHs are seen as potential liquidity pools where a large number of stop loss orders or limit orders may be clustered. They can be used as potential reverse points for trades.
This multi-period feature allows traders to select less and more significant EQL and EQH:
➤ Liquidity wicks:
Liquidity wicks are a minor representation of a stop-loss hunt during the retracement of a pivot point:
➤ Buy and Sell side liquidity:
The buy side liquidity represents a concentration of potential buy orders below the current price level. When price moves into this area, it can lead to increased buying pressure due to the execution of these orders.
The sell side liquidity indicates a pool of potential sell orders below the current price level. Price movement into this area can result in increased selling pressure as these orders are executed.
➤ Sweep Liquidation Zones:
Sweep Liquidation Zones are crucial for understanding market structure and potential future price movements. They provide insights into areas where significant market participants have been forced out of their positions, potentially setting up new trading opportunities.
🔵 USAGE & EXAMPLES
The core principle behind the success of this toolkit lies in identifying "confluence." This refers to the convergence of multiple trading indicators all signaling the same information at a specific point or area. By seeking such alignment, traders can significantly enhance the likelihood of successful trades.
MS + OBs
The chart illustrates a highly bullish setup where the price is rejecting from a bullish order block (POC), while simultaneously forming a bullish Swing Failure Pattern (SFP). This occurs after an internal structure change, marked by a bullish Change of Character (CHoCH). The price broke through a bearish order block, transforming it into a breaker block, further confirming the bullish momentum.
The combination of these elements—bullish order blocks, SFP, and CHoCH—creates a powerful bullish signal, reinforcing the potential for upward movement in the market.
SFP + Bear OB
This chart above displays a bearish setup with a high probability of a price move lower. The price is currently rejecting from a bear order block, which represents a key resistance area where significant selling pressure has previously occurred. A Swing Failure Pattern (SFP) has also formed near this bear order block, indicating that the price briefly attempted to break above a recent high but failed to sustain that upward movement. This failure suggests that buyers are losing momentum, and the market could be preparing for a move to the downside.
Additionally, we can toggle on the Deviation Area in the SFP section to highlight potential levels where price deviation might occur. These deviation areas represent zones where the price is likely to react after the Swing Failure Pattern:
BUY – SELL sides + EQL
The chart showcases a bullish setup with a high probability of price breaking out of the current sell-side resistance level. The market structure indicates a formation of Equal Lows (EQL), which often suggests a build-up of liquidity that could drive the price higher.
The presence of strong buy-side pressure (69%), indicated by the green zone at the bottom, reinforces this bullish outlook. This area represents a key support zone where buyers are outpacing sellers, providing the foundation for a potential upward breakout.
EQL + Bull ChoCh
This chart illustrates a potential bullish setup, driven by the formation of Equal Lows (EQL) followed by a bullish Change of Character (CHoCH). The presence of Equal Lows often signals a liquidity build-up, which can lead to a reversal when combined with additional bullish signals.
Liquidity grab + Bull ChoCh + FVGs
This chart demonstrates a strong bullish scenario, where several important market dynamics are at play. The price begins its upward momentum from Liquidity grab following a bullish Change of Character (CHoCH), signaling the transition from a bearish phase to a bullish one.
As the price progresses, it performs liquidity grabs, which serve to gather the necessary fuel for further movement. These liquidity grabs often occur before significant price surges, as large market participants exploit these areas to accumulate positions before pushing the price higher.
The chart also highlights a market imbalance area, showing strong momentum as the price moves swiftly through this zone.
In this examples, we see how the combination of multiple “smart money” tools helps identify a potential trade opportunities. This is just one of the many scenarios that traders can spot using this toolkit. Other combinations—such as order blocks, liquidity grabs, fair value gaps, and Swing Failure Patterns (SFPs)—can also be layered on top of these concepts to further refine your trading strategy.
🔵 SETTINGS
Window: limit calculation period
Swing: limit drawing function
Mapping structure: show structural points
Algorithmic Logic: (Extreme-Adjusted) Use max high/low or pivot point calculation
Algorithmic loopback: pivot point look back
Show Last: Amount of Order block to display
Hide Overlap: hide overlapping order blocks
Construction: Size of the order blocks
Fair value gaps: Choose between normal FVG or Breaker FVG
Mitigation: (close - wick - avg) point to mitigate the order block/imbalance
SFP lookback: find a higher / lower point to improve accuracy
Threshold: remove less relevant SFP
Equal H&L: (short-mid-long term) display longer term
Liquidity Prints: Shows wicks of candles where liquidity was grabbed
Sweep Area: Identify Sweep Liquidation areas
By combining these indicators in one toolkit, traders are equipped with a comprehensive suite of tools that address every angle of the Smart Money Concept. Instead of relying on disparate tools spread across various platforms, having them integrated into a single, cohesive system allows traders to easily see confluence and make more informed trading decisions.
Buscar en scripts para "high low"
WaveTrend With Divs & RSI(STOCH) Divs by WeloTradesWaveTrend with Divergences & RSI(STOCH) Divergences by WeloTrades
Overview
The "WaveTrend With Divergences & RSI(STOCH) Divergences" is an advanced Pine Script™ indicator designed for TradingView, offering a multi-dimensional analysis of market conditions. This script integrates several technical indicators—WaveTrend, Money Flow Index (MFI), RSI, and Stochastic RSI—into a cohesive tool that identifies both regular and hidden divergences across these indicators. These divergences can indicate potential market reversals and provide critical trading opportunities.
This indicator is not just a simple combination of popular tools; it offers extensive customization options, organized data presentation, and valuable trading signals that are easy to interpret. Whether you're a day trader or a long-term investor, this script enhances your ability to make informed decisions.
Originality and Usefulness
The originality of this script lies in its integration and the synergy it creates among the indicators used. Rather than merely combining multiple indicators, this script allows them to work together, enhancing each other's strengths. For example, by identifying divergences across WaveTrend, RSI, and Stochastic RSI simultaneously, the script provides multiple layers of confirmation, which reduces the likelihood of false signals and increases the reliability of trading signals.
The usefulness of this script is apparent in its ability to offer a consolidated view of market dynamics. It not only simplifies the analytical process by combining different indicators but also provides deeper insights through its divergence detection features. This comprehensive approach is designed to help traders identify potential market reversals, confirm trends, and ultimately make more informed trading decisions.
How the Components Work Together
1. Cross-Validation of Signals
WaveTrend: This indicator is primarily used to identify overbought and oversold conditions, as well as potential buy and sell signals. WaveTrend's ability to smooth price data and reduce noise makes it a reliable tool for identifying trend reversals.
RSI & Stochastic RSI: These momentum oscillators are used to measure the speed and change of price movements. While RSI identifies general overbought and oversold conditions, Stochastic RSI offers a more granular view by tracking the RSI’s level relative to its high-low range over a period of time. When these indicators align with WaveTrend signals, it adds a layer of confirmation that enhances the reliability of the signals.
Money Flow Index (MFI): This volume-weighted indicator assesses the inflow and outflow of money in an asset, giving insights into buying and selling pressure. By analyzing the MFI alongside WaveTrend and RSI indicators, the script can cross-validate signals, ensuring that buy or sell signals are supported by actual market volume.
Example Bullish scenario:
When a bullish divergence is detected on the RSI and confirmed by a corresponding bullish signal on the WaveTrend, along with an increasing Money Flow Index, the probability of a successful trade setup increases. This cross-validation minimizes the risk of acting on false signals, which might occur when relying on a single indicator.
Example Bearish scenario:
When a bearish divergence is detected on the RSI and confirmed by a corresponding bearish signal on the WaveTrend, along with an decreasing Money Flow Index, the probability of a successful trade setup increases. This cross-validation minimizes the risk of acting on false signals, which might occur when relying on a single indicator.
2. Divergence Detection and Market Reversals
Regular Divergences: Occur when the price action and an indicator (like RSI or WaveTrend) move in opposite directions. Regular bullish divergence signals a potential upward reversal when the price makes a lower low while the indicator makes a higher low. Conversely, regular bearish divergence suggests a downward reversal when the price makes a higher high, but the indicator makes a lower high.
Hidden Divergences: These occur when the price action and indicator move in the same direction, but with different momentum. Hidden bullish divergence suggests the continuation of an uptrend, while hidden bearish divergence suggests the continuation of a downtrend. By detecting these divergences across multiple indicators, the script identifies potential trend reversals or continuations with greater accuracy.
Example: The script might detect a regular bullish divergence on the WaveTrend while simultaneously identifying a hidden bullish divergence on the RSI. This combination suggests that while a trend reversal is possible, the overall market sentiment remains bullish, providing a nuanced view of the market.
A Regular Bullish Divergence Example:
A Hidden Bullish Divergence Example:
A Regular Bearish Divergence Example:
A Hidden Bearish Divergence Example:
3. Trend Strength and Sentiment Analysis
WaveTrend: Measures the strength and direction of the trend. By identifying the extremes of market sentiment (overbought and oversold levels), WaveTrend provides early signals for potential reversals.
Money Flow Index (MFI): Assesses the underlying sentiment by analyzing the flow of money. A rising MFI during an uptrend confirms strong buying pressure, while a falling MFI during a downtrend confirms selling pressure. This helps traders assess whether a trend is likely to continue or reverse.
RSI & Stochastic RSI: Offer a momentum-based perspective on the trend’s strength. High RSI or Stochastic RSI values indicate that the asset may be overbought, suggesting a potential reversal. Conversely, low values indicate oversold conditions, signaling a possible upward reversal.
Example:
During a strong uptrend, the WaveTrend & RSI's might signal overbought conditions, suggesting caution. If the MFI also shows decreasing buying pressure and the RSI reaches extreme levels, these indicators together suggest that the trend might be weakening, and a reversal could be imminent.
Example:
During a strong downtrend, the WaveTrend & RSI's might signal oversold conditions, suggesting caution. If the MFI also shows increasing buying pressure and the RSI reaches extreme levels, these indicators together suggest that the trend might be weakening, and a reversal could be imminent.
Conclusion
The "WaveTrend With Divergences & RSI(STOCH) Divergences" script offers a powerful, integrated approach to technical analysis by combining trend, momentum, and sentiment indicators into a single tool. Its unique value lies in the cross-validation of signals, the ability to detect divergences, and the comprehensive view it provides of market conditions. By offering traders multiple layers of analysis and customization options, this script is designed to enhance trading decisions, reduce false signals, and provide clearer insights into market dynamics.
WAVETREND
Display of WaveTrend:
Display of WaveTrend Setting:
WaveTrend Indicator Explanation
The WaveTrend indicator helps identify overbought and oversold conditions, as well as potential buy and sell signals. Its flexibility allows traders to adapt it to various strategies, making it a versatile tool in technical analysis.
WaveTrend Input Settings:
WT MA Source: Default: HLC3
What it is: The data source used for calculating the WaveTrend Moving Average.
What it does: Determines the input data to smooth price action and filter noise.
Example: Using HLC3 (average of High, Low, Close) provides a smoother data representation compared to using just the closing price.
Length (WT MA Length): Default: 3
What it is: The period used to calculate the Moving Average.
What it does: Adjusts the sensitivity of the WaveTrend indicator, where shorter lengths respond more quickly to price changes.
Example: A length of 3 is ideal for short-term analysis, providing quick reactions to price movements.
WT Channel Length & Average: Default: WT Channel Length = 9, Average = 12
What it is: Lengths used to calculate the WaveTrend channel and its average.
What it does: Smooths out the WaveTrend further, reducing false signals by averaging over a set period.
Example: Higher values reduce noise and help in identifying more reliable trends.
Channel: Style, Width, and Color:
What it is: Customization options for the WaveTrend channel's appearance.
What it does: Adjusts how the channel is displayed, including line style, width, and color.
Example: Choosing an area style with a distinct color can make the WaveTrend indicator clearly visible on the chart.
WT Buy & Sell Signals:
What it is: Settings to enable and customize buy and sell signals based on WaveTrend.
What it does: Allows for the display of buy/sell signals and customization of their shapes and colors.
When it gives a Buy Signal: Generated when the WaveTrend line crosses below an oversold level and then rises back, indicating a potential upward price movement.
When it gives a Sell Signal: Triggered when the WaveTrend line crosses above an overbought level and then declines, suggesting a possible downward trend.
Example: The script identifies these signals based on mean reversion principles, where prices tend to revert to the mean after reaching extremes. Traders can use these signals to time their entries and exits effectively.
WAVETREND OVERBOUGTH AND OVERSOLD LEVELS
Display of WaveTrend with Overbought & Oversold Levels:
Display of WaveTrend Overbought & Oversold Levels Settings:
WaveTrend Overbought & Oversold Levels Explanation
WT OB & OS Levels: Default: OB Level 1 = 53, OB Level 2 = 60, OS Level 1 = -53, OS Level 2 = -60
What it is: The default overbought and oversold levels used by the WaveTrend indicator to signal potential market reversals.
What it does: When the WaveTrend crosses above the OB levels, it indicates an overbought condition, potentially signaling a reversal or selling opportunity. Conversely, when it crosses below the OS levels, it indicates an oversold condition, potentially signaling a reversal or buying opportunity.
Example: A trader might use these levels to time entry or exit points, such as selling when the WaveTrend crosses into the overbought zone or buying when it crosses into the oversold zone.
Show OB/OS Levels: Default: True
What it is: Toggle options to show or hide the overbought and oversold levels on your chart.
What it does: When enabled, these levels will be visually represented on your chart, helping you to easily identify when the market reaches these critical thresholds.
Example: Displaying these levels can help you quickly see when the WaveTrend is approaching or has crossed into overbought or oversold territory, allowing for more informed trading decisions.
Line Style, Width, and Color for OB/OS Levels:
What it is: Options to customize the appearance of the OB and OS levels on your chart, including line style (solid, dotted, dashed), line width, and color.
What it does: These settings allow you to adjust how prominently these levels are displayed on your chart, which can help you better visualize and respond to overbought or oversold conditions.
Example: Setting a thicker, dashed line in a contrasting color can make these levels stand out more clearly, aiding in quick visual identification.
Example of Use:
Scenario: A trader wants to identify potential selling points when the market is overbought. They set the OB levels at 53 and 60, choosing a solid, red line style to make these levels clear on their chart. As the WaveTrend crosses above 53, they monitor for further price action, and upon crossing 60, they consider initiating a sell order.
WAVETREND DIVERGENCES
Display of WaveTrend Divergence:
Display of WaveTrend Divergence Setting:
WaveTrend Divergence Indicator Explanation
The WaveTrend Divergence feature helps identify potential reversal points in the market by highlighting divergences between the price and the WaveTrend indicator. Divergences can signal a shift in market momentum, indicating a possible trend reversal. This component allows traders to visualize and customize divergence detection on their charts.
WaveTrend Divergence Input Settings:
Potential Reversal Range: Default: 28
What it is: The number of bars to look back when detecting potential tops and bottoms.
What it does: Sets the range for identifying possible reversal points based on historical data.
Example: A setting of 28 looks back across the last 28 bars to find reversal points, offering a balance between responsiveness and reliability.
Reversal Minimum LVL OB & OS: Default: OB = 35, OS = -35
What it is: The minimum overbought and oversold levels required for detecting potential reversals.
What it does: Adjusts the thresholds that trigger a reversal signal based on the WaveTrend indicator.
Example: A higher OB level reduces the sensitivity to overbought conditions, potentially filtering out false reversal signals.
Lookback Bar Left & Right: Default: Left = 10, Right = 1
What it is: The number of bars to the left and right used to confirm a top or bottom.
What it does: Helps determine the position of peaks and troughs in the price action.
Example: A larger left lookback captures more extended price action before the peak, while a smaller right lookback focuses on the immediate past.
Lookback Range Min & Max: Default: Min = 5, Max = 60
What it is: The minimum and maximum range for the lookback period when identifying divergences.
What it does: Fine-tunes the detection of divergences by controlling the range over which the indicator looks back.
Example: A wider range increases the chances of detecting divergences across different market conditions.
R.Div Minimum LVL OB & OS: Default: OB = 53, OS = -53
What it is: The threshold levels for detecting regular divergences.
What it does: Adjusts the sensitivity of the regular divergence detection.
Example: Higher thresholds make the detection more conservative, identifying only stronger divergence signals.
H.Div Minimum LVL OB & OS: Default: OB = 20, OS = -20
What it is: The threshold levels for detecting hidden divergences.
What it does: Similar to regular divergence settings but for hidden divergences, which can indicate potential reversals that are less obvious.
Example: Lower thresholds make the hidden divergence detection more sensitive, capturing subtler market shifts.
Divergence Label Options:
What it is: Options to display and customize labels for regular and hidden divergences.
What it does: Allows users to visually differentiate between regular and hidden divergences using customizable labels and colors.
Example: Using different colors and symbols for regular (R) and hidden (H) divergences makes it easier to interpret signals on the chart.
Text Size and Color:
What it is: Customization options for the size and color of divergence labels.
What it does: Adjusts the readability and visibility of divergence labels on the chart.
Example: Larger text size may be preferred for charts with a lot of data, ensuring divergence labels stand out clearly.
FAST & SLOW MONEY FLOW INDEX
Display of Fast & Slow Money Flow:
Display of Fast & Slow Money Flow Setting:
Fast Money Flow Indicator Explanation
The Fast Money Flow indicator helps traders identify the flow of money into and out of an asset over a shorter time frame. By tracking the volume-weighted average of price movements, it provides insights into buying and selling pressure in the market, which can be crucial for making timely trading decisions.
Fast Money Flow Input Settings:
Fast Money Flow: Length: Default: 9
What it is: The period used for calculating the Fast Money Flow.
What it does: Determines the sensitivity of the Money Flow calculation. A shorter length makes the indicator more responsive to recent price changes, while a longer length provides a smoother signal.
Example: A length of 9 is suitable for traders looking to capture quick shifts in market sentiment over a short period.
Fast MFI Area Multiplier: Default: 5
What it is: A multiplier applied to the Money Flow area calculation.
What it does: Adjusts the size of the Money Flow area on the chart, effectively amplifying or reducing the visual impact of the indicator.
Example: A higher multiplier can make the Money Flow more prominent on the chart, aiding in the quick identification of significant money flow changes.
Y Position (Y Pos): Default: 0
What it is: The vertical position adjustment for the Fast Money Flow plot on the chart.
What it does: Allows you to move the Money Flow plot up or down on the chart to avoid overlap with other indicators.
Example: Adjusting the Y Position can be useful if you have multiple indicators on the chart and need to maintain clarity.
Fast MFI Style, Width, and Color:
What it is: Customization options for how the Fast Money Flow is displayed on the chart.
What it does: Enables you to choose between different plot styles (line or area), set the line width, and select colors for positive and negative money flow.
Example: Using different colors for positive (green) and negative (red) money flow helps to visually distinguish between periods of buying and selling pressure.
Slow Money Flow Indicator Explanation
The Slow Money Flow indicator tracks the flow of money into and out of an asset over a longer time frame. It provides a broader perspective on market sentiment, smoothing out short-term fluctuations and highlighting longer-term trends.
Slow Money Flow Input Settings:
Slow Money Flow: Length: Default: 12
What it is: The period used for calculating the Slow Money Flow.
What it does: A longer period smooths out short-term fluctuations, providing a clearer view of the overall money flow trend.
Example: A length of 12 is often used by traders looking to identify sustained trends rather than short-term volatility.
Slow MFI Area Multiplier: Default: 5
What it is: A multiplier applied to the Slow Money Flow area calculation.
What it does: Adjusts the size of the Money Flow area on the chart, helping to emphasize the indicator’s significance.
Example: Increasing the multiplier can help highlight the Money Flow in markets with less volatile price action.
Y Position (Y Pos): Default: 0
What it is: The vertical position adjustment for the Slow Money Flow plot on the chart.
What it does: Allows for vertical repositioning of the Money Flow plot to maintain chart clarity when used with other indicators.
Example: Adjusting the Y Position ensures that the Slow Money Flow indicator does not overlap with other key indicators on the chart.
Slow MFI Style, Width, and Color:
What it is: Customization options for the visual display of the Slow Money Flow on the chart.
What it does: Allows you to choose the plot style (line or area), set the line width, and select colors to differentiate positive and negative money flow.
Example: Customizing the colors for the Slow Money Flow allows traders to quickly distinguish between buying and selling trends in the market.
RSI
Display of RSI:
Display of RSI Setting:
RSI Indicator Explanation
The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements. It is typically used to identify overbought or oversold conditions in the market, providing traders with potential signals for buying or selling.
RSI Input Settings:
RSI Source: Default: Close
What it is: The data source used for calculating the RSI.
What it does: Determines which price data (e.g., close, open) is used in the RSI calculation, affecting how the indicator reflects market conditions.
Example: Using the closing price is standard practice, as it reflects the final agreed-upon price for a given time period.
MA Type (Moving Average Type): Default: SMA
What it is: The type of moving average applied to the RSI for smoothing purposes.
What it does: Changes the smoothing technique of the RSI, impacting how quickly the indicator responds to price movements.
Example: Using an Exponential Moving Average (EMA) will make the RSI more sensitive to recent price changes compared to a Simple Moving Average (SMA).
RSI Length: Default: 14
What it is: The period over which the RSI is calculated.
What it does: Adjusts the sensitivity of the RSI. A shorter length (e.g., 7) makes the RSI more responsive to recent price changes, while a longer length (e.g., 21) smooths out the indicator, reducing the number of signals.
Example: A 14-period RSI is commonly used for identifying overbought and oversold conditions, providing a balance between sensitivity and reliability.
RSI Plot Style, Width, and Color:
What it is: Options to customize the appearance of the RSI line on the chart.
What it does: Allows you to adjust the visual representation of the RSI, including the line width and color.
Example: Setting a thicker line width and a bright color like yellow can make the RSI more visible on the chart, aiding in quick analysis.
Display of RSI with RSI Moving Average:
RSI Moving Average Explanation
The RSI Moving Average adds a smoothing layer to the RSI, helping to filter out noise and provide clearer signals. It is particularly useful for confirming trend strength and identifying potential reversals.
RSI Moving Average Input Settings:
MA Length: Default: 14
What it is: The period over which the Moving Average is calculated on the RSI.
What it does: Adjusts the smoothing of the RSI, helping to reduce false signals and provide a clearer trend indication.
Example: A 14-period moving average on the RSI can smooth out short-term fluctuations, making it easier to spot genuine overbought or oversold conditions.
MA Plot Style, Width, and Color:
What it is: Customization options for how the RSI Moving Average is displayed on the chart.
What it does: Allows you to adjust the line width and color, helping to differentiate the Moving Average from the main RSI line.
Example: Using a contrasting color for the RSI Moving Average (e.g., magenta) can help it stand out against the main RSI line, making it easier to interpret the indicator.
STOCHASTIC RSI
Display of Stochastic RSI:
Display of Stochastic RSI Setting:
Stochastic RSI Indicator Explanation
The Stochastic RSI (Stoch RSI) is a momentum oscillator that measures the level of the RSI relative to its high-low range over a set period of time. It is used to identify overbought and oversold conditions, providing potential buy and sell signals based on momentum shifts.
Stochastic RSI Input Settings:
Stochastic RSI Length: Default: 14
What it is: The period over which the Stochastic RSI is calculated.
What it does: Adjusts the sensitivity of the Stochastic RSI. A shorter length makes the indicator more responsive to recent price changes, while a longer length smooths out the fluctuations, reducing noise.
Example: A length of 14 is commonly used to identify momentum shifts over a medium-term period, providing a balanced view of potential overbought or oversold conditions.
Display of Stochastic RSI %K Line:
Stochastic RSI %K Line Explanation
The %K line in the Stochastic RSI is the main line that tracks the momentum of the RSI over the chosen period. It is the faster-moving component of the Stochastic RSI, often used to identify entry and exit points.
Stochastic RSI %K Input Settings:
%K Length: Default: 3
What it is: The period used for smoothing the %K line of the Stochastic RSI.
What it does: Smoothing the %K line helps reduce noise and provides a clearer signal for potential market reversals.
Example: A smoothing length of 3 is common, offering a balance between responsiveness and noise reduction, making it easier to spot significant momentum shifts.
%K Plot Style, Width, and Color:
What it is: Customization options for the visual representation of the %K line.
What it does: Allows you to adjust the appearance of the %K line on the chart, including line width and color, to fit your visual preferences.
Example: Setting a blue color and a medium width for the %K line makes it stand out clearly on the chart, helping to identify key points of momentum change.
%K Fill Color (Above):
What it is: The fill color that appears above the %K line on the chart.
What it does: Adds visual clarity by shading the area above the %K line, making it easier to interpret the direction and strength of momentum.
Example: Using a light blue fill color above the %K line can help emphasize bullish momentum, making it visually prominent.
Display of Stochastic RSI %D Line:
Stochastic RSI %D Line Explanation
The %D line in the Stochastic RSI is a moving average of the %K line and acts as a signal line. It is slower-moving compared to the %K line and is often used to confirm signals or identify potential reversals when it crosses the %K line.
Stochastic RSI %D Input Settings:
%D Length: Default: 3
What it is: The period used for smoothing the %D line of the Stochastic RSI.
What it does: Smooths out the %D line, making it less sensitive to short-term fluctuations and more reliable for identifying significant market signals.
Example: A length of 3 is often used to provide a smoothed signal line that can help confirm trends or reversals indicated by the %K line.
%D Plot Style, Width, and Color:
What it is: Customization options for the visual representation of the %D line.
What it does: Allows you to adjust the appearance of the %D line on the chart, including line width and color, to match your preferences.
Example: Setting an orange color and a thicker line width for the %D line can help differentiate it from the %K line, making crossover points easier to spot.
%D Fill Color (Below):
What it is: The fill color that appears below the %D line on the chart.
What it does: Adds visual clarity by shading the area below the %D line, making it easier to interpret bearish momentum.
Example: Using a light orange fill color below the %D line can highlight bearish conditions, making it visually easier to identify.
RSI & STOCHASTIC RSI OVERBOUGHT AND OVERSOLD LEVELS
Display of RSI & Stochastic with Overbought & Oversold Levels:
Display of RSI & Stochastic Overbought & Oversold Settings:
RSI & Stochastic Overbought & Oversold Levels Explanation
The Overbought (OB) and Oversold (OS) levels for RSI and Stochastic RSI indicators are key thresholds that help traders identify potential reversal points in the market. These levels are used to determine when an asset is likely overbought or oversold, which can signal a potential trend reversal.
RSI & Stochastic Overbought & Oversold Input Settings:
RSI & Stochastic Level 1 Overbought (OB) & Oversold (OS): Default: OB Level = 170, OS Level = 130
What it is: The first set of thresholds for determining overbought and oversold conditions for both RSI and Stochastic RSI indicators.
What it does: When the RSI or Stochastic RSI crosses above the overbought level, it suggests that the asset might be overbought, potentially signaling a sell opportunity. Conversely, when these indicators drop below the oversold level, it suggests the asset might be oversold, potentially signaling a buy opportunity.
Example: If the RSI crosses above 170, traders might look for signs of a potential trend reversal to the downside, while a cross below 130 might indicate a reversal to the upside.
RSI & Stochastic Level 2 Overbought (OB) & Oversold (OS): Default: OB Level = 180, OS Level = 120
What it is: The second set of thresholds for determining overbought and oversold conditions for both RSI and Stochastic RSI indicators.
What it does: These levels provide an additional set of reference points, allowing traders to differentiate between varying degrees of overbought and oversold conditions, potentially leading to more refined trading decisions.
Example: When the RSI crosses above 180, it might indicate an extreme overbought condition, which could be a stronger signal for a sell, while a cross below 120 might indicate an extreme oversold condition, which could be a stronger signal for a buy.
RSI & Stochastic Overbought (OB) Band Customization:
OB Level 1: Width, Style, and Color:
What it is: Customization options for the visual appearance of the first overbought band on the chart.
What it does: Allows you to set the line width, style (solid, dotted, dashed), and color for the first overbought band, enhancing its visibility on the chart.
Example: A dashed red line with medium width can clearly indicate the first overbought level, helping traders quickly identify when this threshold is crossed.
OB Level 2: Width, Style, and Color:
What it is: Customization options for the visual appearance of the second overbought band on the chart.
What it does: Allows you to set the line width, style, and color for the second overbought band, providing a clear distinction from the first band.
Example: A dashed red line with a slightly thicker width can represent a more significant overbought level, making it easier to differentiate from the first level.
RSI & Stochastic Oversold (OS) Band Customization:
OS Level 1: Width, Style, and Color:
What it is: Customization options for the visual appearance of the first oversold band on the chart.
What it does: Allows you to set the line width, style (solid, dotted, dashed), and color for the first oversold band, making it visually prominent.
Example: A dashed green line with medium width can highlight the first oversold level, helping traders identify potential buying opportunities.
OS Level 2: Width, Style, and Color:
What it is: Customization options for the visual appearance of the second oversold band on the chart.
What it does: Allows you to set the line width, style, and color for the second oversold band, providing an additional visual cue for extreme oversold conditions.
Example: A dashed green line with a thicker width can represent a more significant oversold level, offering a stronger visual cue for potential buying opportunities.
RSI DIVERGENCES
Display of RSI Divergence Labels:
Display of RSI Divergence Settings:
RSI Divergence Lookback Explanation
The RSI Divergence settings allow traders to customize the parameters for detecting divergences between the RSI (Relative Strength Index) and price action. Divergences occur when the price moves in the opposite direction to the RSI, potentially signaling a trend reversal. These settings help refine the accuracy of divergence detection by adjusting the lookback period and range. ( NOTE: This setting only imply to the RSI. This doesn't effect the STOCHASTIC RSI. )
RSI Divergence Lookback Input Settings:
Lookback Left: Default: 10
What it is: The number of bars to look back from the current bar to detect a potential divergence.
What it does: Defines the left-side lookback period for identifying pivot points in the RSI, which are used to spot divergences. A longer lookback period may capture more significant trends but could also miss shorter-term divergences.
Example: A setting of 10 bars means the script will consider pivot points up to 10 bars before the current bar to check for divergence patterns.
Lookback Right: Default: 1
What it is: The number of bars to look forward from the current bar to complete the divergence pattern.
What it does: Defines the right-side lookback period for confirming a potential divergence. This setting helps ensure that the identified divergence is valid by allowing the script to check subsequent bars for confirmation.
Example: A setting of 1 bar means the script will look at the next bar to confirm the divergence pattern, ensuring that the signal is reliable.
Lookback Range Min: Default: 5
What it is: The minimum range of bars required to detect a valid divergence.
What it does: Sets a lower bound on the range of bars considered for divergence detection. A lower minimum range might capture more frequent but possibly less significant divergences.
Example: Setting the minimum range to 5 ensures that only divergences spanning at least 5 bars are considered, filtering out very short-term patterns.
Lookback Range Max: Default: 60
What it is: The maximum range of bars within which a divergence can be detected.
What it does: Sets an upper bound on the range of bars considered for divergence detection. A larger maximum range might capture more significant divergences but could also include less relevant long-term patterns.
Example: Setting the maximum range to 60 bars allows the script to detect divergences over a longer timeframe, capturing more extended divergence patterns that could indicate major trend reversals.
RSI Divergence Explanation
RSI divergences occur when the RSI indicator and price action move in opposite directions, signaling potential trend reversals. This section of the settings allows traders to customize the appearance and detection of both regular and hidden bullish and bearish divergences.
RSI Divergence Input Settings:
R. Bullish Div Label: Default: True
What it is: An option to display labels for regular bullish divergences.
What it does: Enables or disables the visibility of labels that mark regular bullish divergences, where the price makes a lower low while the RSI makes a higher low, indicating a potential upward reversal.
Example: A trader might use this to spot buying opportunities in a downtrend when a bullish divergence suggests the trend may be reversing.
Bullish Label Color, Line Width, and Line Color:
What it is: Settings to customize the appearance of regular bullish divergence labels.
What it does: Allows you to choose the color of the labels, adjust the width of the divergence lines, and select the color for these lines.
Example: Selecting a green label color and a distinct line width makes bullish divergences easily recognizable on your chart.
R. Bearish Div Label: Default: True
What it is: An option to display labels for regular bearish divergences.
What it does: Enables or disables the visibility of labels that mark regular bearish divergences, where the price makes a higher high while the RSI makes a lower high, indicating a potential downward reversal.
Example: A trader might use this to spot selling opportunities in an uptrend when a bearish divergence suggests the trend may be reversing.
Bearish Label Color, Line Width, and Line Color:
What it is: Settings to customize the appearance of regular bearish divergence labels.
What it does: Allows you to choose the color of the labels, adjust the width of the divergence lines, and select the color for these lines.
Example: Choosing a red label color and a specific line width makes bearish divergences clearly stand out on your chart.
H. Bullish Div Label: Default: False
What it is: An option to display labels for hidden bullish divergences.
What it does: Enables or disables the visibility of labels that mark hidden bullish divergences, where the price makes a higher low while the RSI makes a lower low, indicating potential continuation of an uptrend.
Example: A trader might use this to confirm an existing uptrend when a hidden bullish divergence signals continued buying strength.
Hidden Bullish Label Color, Line Width, and Line Color:
What it is: Settings to customize the appearance of hidden bullish divergence labels.
What it does: Allows you to choose the color of the labels, adjust the width of the divergence lines, and select the color for these lines.
Example: A softer green color with a thinner line width might be chosen to subtly indicate hidden bullish divergences, keeping the chart clean while providing useful information.
H. Bearish Div Label: Default: False
What it is: An option to display labels for hidden bearish divergences.
What it does: Enables or disables the visibility of labels that mark hidden bearish divergences, where the price makes a lower high while the RSI makes a higher high, indicating potential continuation of a downtrend.
Example: A trader might use this to confirm an existing downtrend when a hidden bearish divergence signals continued selling pressure.
Hidden Bearish Label Color, Line Width, and Line Color:
What it is: Settings to customize the appearance of hidden bearish divergence labels.
What it does: Allows you to choose the color of the labels, adjust the width of the divergence lines, and select the color for these lines.
Example: A muted red color with a thinner line width might be selected to indicate hidden bearish divergences without overwhelming the chart.
Divergence Text Size and Color: Default: S (Small)
What it is: Settings to adjust the size and color of text labels for RSI divergences.
What it does: Allows you to customize the size and color of text labels that display the divergence information on the chart.
Example: Choosing a small text size with a bright white color can make divergence labels easily readable without taking up too much space on the chart.
STOCHASTIC DIVERGENCES
Display of Stochastic RSI Divergence Labels:
Display of Stochastic RSI Divergence Settings:
Stochastic RSI Divergence Explanation
Stochastic RSI divergences occur when the Stochastic RSI indicator and price action move in opposite directions, signaling potential trend reversals. These settings allow traders to customize the detection and visual representation of both regular and hidden bullish and bearish divergences in the Stochastic RSI.
Stochastic RSI Divergence Input Settings:
R. Bullish Div Label: Default: True
What it is: An option to display labels for regular bullish divergences in the Stochastic RSI.
What it does: Enables or disables the visibility of labels that mark regular bullish divergences, where the price makes a lower low while the Stochastic RSI makes a higher low, indicating a potential upward reversal.
Example: A trader might use this to spot buying opportunities in a downtrend when a bullish divergence in the Stochastic RSI suggests the trend may be reversing.
Bullish Label Color, Line Width, and Line Color:
What it is: Settings to customize the appearance of regular bullish divergence labels in the Stochastic RSI.
What it does: Allows you to choose the color of the labels, adjust the width of the divergence lines, and select the color for these lines.
Example: Selecting a blue label color and a distinct line width makes bullish divergences in the Stochastic RSI easily recognizable on your chart.
R. Bearish Div Label: Default: True
What it is: An option to display labels for regular bearish divergences in the Stochastic RSI.
What it does: Enables or disables the visibility of labels that mark regular bearish divergences, where the price makes a higher high while the Stochastic RSI makes a lower high, indicating a potential downward reversal.
Example: A trader might use this to spot selling opportunities in an uptrend when a bearish divergence in the Stochastic RSI suggests the trend may be reversing.
Bearish Label Color, Line Width, and Line Color:
What it is: Settings to customize the appearance of regular bearish divergence labels in the Stochastic RSI.
What it does: Allows you to choose the color of the labels, adjust the width of the divergence lines, and select the color for these lines.
Example: Choosing an orange label color and a specific line width makes bearish divergences in the Stochastic RSI clearly stand out on your chart.
H. Bullish Div Label: Default: False
What it is: An option to display labels for hidden bullish divergences in the Stochastic RSI.
What it does: Enables or disables the visibility of labels that mark hidden bullish divergences, where the price makes a higher low while the Stochastic RSI makes a lower low, indicating potential continuation of an uptrend.
Example: A trader might use this to confirm an existing uptrend when a hidden bullish divergence in the Stochastic RSI signals continued buying strength.
Hidden Bullish Label Color, Line Width, and Line Color:
What it is: Settings to customize the appearance of hidden bullish divergence labels in the Stochastic RSI.
What it does: Allows you to choose the color of the labels, adjust the width of the divergence lines, and select the color for these lines.
Example: A softer blue color with a thinner line width might be chosen to subtly indicate hidden bullish divergences, keeping the chart clean while providing useful information.
H. Bearish Div Label: Default: False
What it is: An option to display labels for hidden bearish divergences in the Stochastic RSI.
What it does: Enables or disables the visibility of labels that mark hidden bearish divergences, where the price makes a lower high while the Stochastic RSI makes a higher high, indicating potential continuation of a downtrend.
Example: A trader might use this to confirm an existing downtrend when a hidden bearish divergence in the Stochastic RSI signals continued selling pressure.
Hidden Bearish Label Color, Line Width, and Line Color:
What it is: Settings to customize the appearance of hidden bearish divergence labels in the Stochastic RSI.
What it does: Allows you to choose the color of the labels, adjust the width of the divergence lines, and select the color for these lines.
Example: A muted orange color with a thinner line width might be selected to indicate hidden bearish divergences without overwhelming the chart.
Divergence Text Size and Color: Default: S (Small)
What it is: Settings to adjust the size and color of text labels for Stochastic RSI divergences.
What it does: Allows you to customize the size and color of text labels that display the divergence information on the chart.
Example: Choosing a small text size with a bright white color can make divergence labels easily readable without taking up too much space on the chart.
Alert System:
Custom Alerts for Divergences and Reversals:
What it is: The script includes customizable alert conditions to notify you of detected divergences or potential reversals based on WaveTrend, RSI, and Stochastic RSI.
What it does: Helps you stay informed of key market movements without constantly monitoring the charts, enabling timely decisions.
Example: Setting an alert for regular bearish divergence on the WaveTrend could notify you of a potential sell opportunity as soon as it is detected.
How to Use Alerts:
Set up custom alerts in TradingView based on these conditions to be notified of potential trading opportunities. Alerts are triggered when the indicator detects conditions that match the selected criteria, such as divergences or potential reversals.
By following the detailed guidelines and examples above, you can effectively use and customize this powerful indicator to suit your trading strategy.
For further understanding and customization, refer to the input settings within the script and adjust them to match your trading style and preferences.
How Components Work Together
Synergy and Cross-Validation: The indicator combines multiple layers of analysis to validate trading signals. For example, a WaveTrend buy signal that coincides with a bullish divergence in RSI and positive fast money flow is likely to be more reliable than any single indicator’s signal. This cross-validation reduces the likelihood of false signals and enhances decision-making.
Comprehensive Market Analysis: Each component plays a role in analyzing different aspects of the market. WaveTrend focuses on trend strength, Money Flow indicators assess market sentiment, while RSI and Stochastic RSI offer detailed views of price momentum and potential reversals.
Ideal For
Traders who require a reliable, multifaceted tool for detecting market trends and reversals.
Investors seeking a deeper understanding of market dynamics across different timeframes and conditions, whether in forex, equities, or cryptocurrency markets.
This script is designed to provide a comprehensive tool for technical analysis, combining multiple indicators and divergence detection into one versatile and customizable script. It is especially useful for traders who want to monitor various indicators simultaneously and look for convergence or divergence signals across different technical tools.
Acknowledgements
Special thanks to these amazing creators for inspiration and their creations:
I want to thank these amazing creators for creating there amazing indicators , that inspired me and also gave me a head start by making this indicator! Without their amazing indicators it wouldn't be possible!
vumanchu: VuManChu Cipher B Divergences.
MisterMoTa: RSI + Divergences + Alerts .
DevLucem: Plain Stochastic Divergence.
Note
This indicator is designed to be a powerful tool in your trading arsenal. However , it is essential to backtest and adjust the settings according to your trading strategy before applying it to live trading . If you have any questions or need further assistance, feel free to reach out.
Equal Highs and LowsDescription:
The ‘Equal Highs and Lows’ indicator is a technical analysis tool that marks identical price levels on a trading chart using the current time-frame, assisting traders in identifying potential support and resistance zones or liquidity draws. It creates a horizontal line connecting points where the price has created equal highs and lows within a specified lookback period. Unique to this tool, it maintains a clean chart by removing the line once the price surpasses the equal highs or falls below the equal lows, ensuring only the currently relevant equal highs and lows are highlighted.
Features:
Customization Options: Users can adjust the appearance of the lines (color, width, and style) to match their chart setup or preferences. Users can also choose to extend the lines marking the equal highs/lows to the right of the chart making the equal high/low levels more easier to visualize.
User-Defined Lookback Length: The number of bars to look back for finding equal highs and lows can be set by the user, allowing for flexibility in different market conditions.
How It Works:
The indicator meticulously scans the chart over a user-specified lookback duration, identifying bars with matching high or low values that have not been mitigated on the current chat timeframe, thereby constructing an index of equal values. It subsequently connects these equal values on the chart with a line. While this intuitive indicator does not forecast future market trends, it emphasizes significant price levels derived from historical data.
Usage:
Identifying Support and Resistance: The lines drawn by the indicator can be used to identify potential support and resistance zones and/or draws of liquidity, which are crucial for making informed trading decisions.
Strategy Development: Traders can incorporate the visual cues provided by the indicator into their trading strategies, using them as one of the factors for entry or exit decisions.
Originality:
This indicator presents a distinctive method for pinpointing and illustrating equal highs and lows, granting traders a crucial insight into key price levels. It stands apart from conventional indicators by offering extensive personalization and employing a novel approach to augment chart analysis. Uniquely, it retains only unmitigated equal high/low levels on the chart, automatically discarding mitigated price levels once the price has reached that level.
Conclusion:
The "Equal Highs and Lows" indicator is a practical tool for traders looking to enhance their chart analysis with visual cues of significant price levels. Its customization options and innovative approach make it a valuable addition to the trading toolkit, suitable for various trading styles and strategies.
Depth of Market (DOM) [LuxAlgo]The Depth Of Market (DOM) tool allows traders to look under the hood of any market, taking price and volume analysis to the next level. The following features are included: DOM, Time & Sales, Volume Profile, Depth of Market, Imbalances, Buying Pressure, and up to 24 key intraday levels (it really packs a punch).
As a disclaimer, this tool does not use tick data, it is a DOM reconstruction from the provided real-time time series data (price and volume). So the volume you see is from filled orders only, this tool does not show unfilled limit orders.
Traders can enable or disable any of the features at will to avoid being overwhelmed with too much information and to make the tool perform faster.
The features that have the biggest impact on performance are Historical Data Collection, Key Levels (POC & VWAP), Time & Sales, Profile, and Imbalances. Disable these features to improve the indicator computational performance.
🔶 DOM
This is the simplest form of the tool, a simple DOM or ladder that displays the following columns:
PRICE: Price level
BID: Total number of market sell orders filled or limit buy orders filled.
SELL: Sell market orders
BUY: Buy market orders
ASK: Total number of market buy orders filled or limit sell orders filled.
The DOM only collects historical data from the last 24 hours and real-time data.
Traders can select a reset period for the DOM with two options:
DAILY: Resets at the beginning of each trading day
SESSIONS: Resets twice, as DAILY and 15.5 hours later, to coincide with the start of the RTH session for US tickers.
The DOM has two main modes, it can display price levels as ticks or points. The default is automatic based on the current daily volatility, but traders can manually force one mode or the other if they wish.
For convenience, traders have the option to set the number of lines (price levels), and the size of the text and to display only real-time data.
By default, the top price is set to 0 so that the DOM automatically adjusts the price levels to be displayed, but traders can set the top price manually so that the tool displays only the desired price levels in a fixed manner.
🔹 Volume Profile
As additional features to the basic DOM, traders have access to the volume profile histogram and the total volume per price level.
This helps traders identify at a glance key price areas where volume is accumulating (high volume nodes) or areas where volume is lacking (low volume nodes) - these areas are important to some traders who base their decision-making process on them.
🔹 Imbalances
Other added features are imbalances and buying pressure:
Interlevel Imbalance: volume delta between two different price levels
Intralevel Imbalance: delta between buy and sell volume at the same price level
Buying Pressure Percent: percentage of buy volume compared to total volume
Imbalances can help traders identify areas of interest in the price for possible support or resistance.
🔹 Depth
Depth allows traders to see at a glance how much supply is above the current price level or how much demand is below the current price level.
Above the current price level shows the cumulative ask volume (filled sell limit orders) and below the current price level shows the cumulative bid volume (filled buy limit orders).
🔶 KEY LEVELS
The tool includes up to 24 different key intraday levels of particular relevance:
Previous Week Levels
PWH: Previous week high
PWL: Previous week low
PWM: Previous week middle
PWS: Previous week settlement (close)
Previous Day Levels
PDH: Previous day high
PDL: Previous day low
PDM: Previous day middle
PDS: Previous day settlement (close)
Current Day Levels
OPEN: Open of day (or session)
HOD: High of day (or session)
LOD: Low of day (or session)
MOD: Middle of day (or session)
Opening Range
ORH: Open range high
ORL: Open range low
Initial Balance
IBH: Initial balance high
IBL: Initial balance low
VWAP
+3SD: Volume weighted average price plus 3 standard deviations
+2SD: Volume weighted average price plus 2 standard deviations
+1SD: Volume weighted average price plus 1 standard deviation
VWAP: Volume weighted average price
-1SD: Volume weighted average price minus 1 standard deviation
-2SD: Volume weighted average price minus 2 standard deviations
-3SD: Volume weighted average price minus 3 standard deviations
POC: Point of control
Different traders look at different levels, the key levels shown here are objective and specific areas of interest that traders can act on, providing us with potential areas of support or resistance in the price.
🔶 TIME & SALES
The tool also features a full-time and sales panel with time, price, and size columns, a size filter, and the ability to set the timezone to display time in the trader's local time.
The information shown here is what feeds the DOM and it can be useful in several ways, for example in detecting absorption. If a large number of orders are coming into the market but the price is barely moving, this indicates that there is enough liquidity at these levels to absorb all these orders, so if these orders stop coming into the market, the price may turn around.
🔶 SETTINGS
Period: Select the anchoring period to start data collection, DAILY will anchor at the start of the trading day, and SESSIONS will start as DAILY and 15.5 hours later (RTH for US tickers).
Mode: Select between AUTO and MANUAL modes for displaying TICKS or POINTS, in AUTO mode the tool will automatically select TICKS for tickers with a daily average volatility below 5000 ticks and POINTS for the rest of the tickers.
Rows: Select the number of price levels to display
Text Size: Select the text size
🔹 DOM
DOM: Enable/Disable DOM display
Realtime only: Enable/Disable real-time data only, historical data will be collected if disabled
Top Price: Specify the price to be displayed on the top row, set to 0 to enable dynamic DOM
Max updates: Specify how many times the values on the SELL and BUY columns are accumulated until reset.
Profile/Depth size: Maximum size of the histograms on the PROFILE and DEPTH columns.
Profile: Enable/Disable Profile column. High impact on performance.
Volume: Enable/Disable Volume column. Total volume traded at price level.
Interlevel Imbalance: Enable/Disable Interlevel Imbalance column. Total volume delta between the current price level and the price level above. High impact on performance.
Depth: Enable/Disable Depth, showing the cumulative supply above the current price and the cumulative demand below. Impact on performance.
Intralevel Imbalance: Enable/Disable Intralevel Imbalance column. Delta between total buy volume and total sell volume. High impact on performance.
Buying Pressure Percent: Enable/Disable Buy Percent column. Percentage of total buy volume compared to total volume.
Imbalance Threshold %: Threshold for highlighting imbalances. Set to 90 to highlight the top 10% of interlevel imbalances and the top and bottom 10% of intra-level imbalances.
Crypto volume precision: Specify the number of decimals to display on the volume of crypto assets
🔹 Key Levels
Key Levels: Enable/Disable KEY column. Very high performance impact.
Previous Week: Enable/Disable High, Low, Middle, and Close of the previous trading week.
Previous Day: Enable/Disable High, Low, Middle, and Settlement of the previous trading day.
Current Day/Session: Enable/Disable Open, High, Low and Middle of the current period.
Open Range: Enable/Disable High and Low of the first candle of the period.
Initial Balance: Enable/Disable High and Low of the first hour of the period.
VWAP: Enable/Disable Volume-weighted average price of the period with 1, 2, and 3 standard deviations.
POC: Enable/Disable Point of Control (price level with the highest volume traded) of the period.
🔹 Time & Sales
Time & Sales: Enable/Disable time and sales panel.
Timezone offset (hours): Enter your time zone\'s offset (+ or −), including a decimal fraction if needed.
Order Size: Set order size filter. Orders smaller than the value are not displayed.
🔶 THANKS
Hi, I'm makit0 coder of this tool and proud member of the LuxAlgo Opensource team, it's an honor to be part of the LuxAlgo family doing something I love as it's writing opensource code and sharing it with the world. I'd like to thank all of you who use, comment on, and vote for all of our open-source tools, and all of you who give us your support.
And of course thanks to the PineCoders family for all the work in front of and behind the scenes that makes the PineScript community what it is, simply the best.
Peace, Love & PineScript!
Swing IdentifierThe "Swing Identifier" is a custom Pine Script indicator designed for use in the TradingView platform. It serves to visually identify and mark swing highs and swing lows on a trading chart, which are key concepts in technical analysis. This script is comprehensive and customizable, making it a useful tool for traders looking to pinpoint potential trend reversals and support or resistance areas.
**Key Features of the 'Swing Identifier' Indicator:**
1. **Swing Range Input:**
- This input determines the number of bars to the left and right of the current bar that the script will examine to identify a swing high or low. A larger value will look for swings over a broader range, potentially identifying more significant swings but at the expense of sensitivity.
2. **Swing Strength Input:**
- The swing strength is set as a percentage and is used to filter out insignificant price movements. A swing high or low is only considered valid if the percentage change from the last swing is greater than this input value. This feature helps in avoiding false signals in sideways or less volatile markets.
3. **Use Wicks Option:**
- Users can choose whether to consider the wicks of the candles or just the closing prices in identifying swings. This feature adds flexibility, allowing the script to be tailored to different trading styles and strategies.
4. **Line Color Customization:**
- The color of the lines marking the swings can be customized, enhancing the visual appeal and readability of the chart.
**Operational Mechanics:**
1. **Identification of Swing Highs and Lows:**
- The script uses the `ta.pivothigh` and `ta.pivotlow` functions to identify swing highs and lows. Whether it uses the high/low of the candles or their closing prices is determined by the user's choice in the "Use Wicks" option.
2. **Drawing and Updating Lines:**
- When a new swing high or low is identified, and it meets the percentage change criteria from the previous swing, a line is drawn from the last swing low to the current high (or vice versa). If a new swing high (or low) is identified that is higher (or lower) than the previous one, the old line is deleted, and a new line is drawn.
3. **Swing Update Logic:**
- The script maintains a toggle mechanism to look alternatively for highs and lows. This ensures that it sequentially identifies a high and then a low (or vice versa), which aligns with how actual market swings behave.
**Usage in Trading:**
1. **Identifying Trend Reversals:**
- By marking swing highs and lows, the script helps traders identify potential trend reversals. A break of a swing low in an uptrend or a swing high in a downtrend could signal a change in the prevailing trend.
2. **Support and Resistance:**
- Swing highs and lows often act as levels of support and resistance. Traders can use these levels for setting entry or exit points, stop losses, and take profit orders.
3. **Customization for Strategy:**
- The customizable nature of the script allows traders to adjust the parameters according to their trading strategy, time frame, and asset volatility.
In summary, the "Swing Identifier" is a versatile and customizable tool that aids in visually identifying crucial price swing points, thereby assisting traders in making informed decisions based on technical analysis principles.
Modified Box Plots
Box Plot Concept: The script creates a modified box plot where the central box represents the range within 1 standard deviation from the midpoint (hl2), which is the average of the high and low prices. The whiskers extend to cover a range of 3 standard deviations, providing a visualization of the overall price distribution.
Color Scheme: The color of the modified box plot is determined based on comparisons between the current midpoint (g) and the +/- 1 SD values of the previous candle (i and j ). If g > i , the color is green; if g < j , it's red; otherwise, it's yellow. This color scheme allows users to quickly assess the relationship between the current market conditions and recent price movements. if the mid point price is above/below +/- 1 SD values of the previous candle the price movement is considered as significant.
Plotcandle Function: The plotcandle function is employed to visualize the modified box plot. The color of the box is dynamically determined by the candleColor variable, which reflects the current market state based on the color scheme. The wicks, represented by lines extending from the box, are colored in white.
Explanation of Box and Wicks:
Box (Open and Close): In this modified box plot, the box does not represent traditional open and close prices. Instead, it signifies a range within 1 standard deviation of the midpoint (hl2), providing insight into the typical price variation around the average of the high and low.
Wicks (High and Low): The wicks extend from the box to cover a range of 3 standard deviations from the midpoint (hl2). They do not correspond to the actual high and low prices but serve as a visualization of potential outliers in the price distribution. The actual high and low prices are also plotted as green and red dots when the actual high and low prices fall outside the +/- 3SD wicks (whiskers) and also indicate the prices does not fit the distribution based on the recent price volatility.
In summary, this modified box plot offers a unique perspective on price distribution by considering standard deviations from the midpoint. The color scheme aids in quickly assessing market conditions, and the wicks provide insights into the potential presence of outliers. It's essential to understand that the box and wicks do not represent traditional open, close, high, and low prices but offer a different way to visualize and interpret intraday price movements.
Step by step explanation
Here's the step-by-step explanation:
a = ta.highest(high, 7): Calculates the highest high in the last 7 bars.
b = ta.lowest(low, 7): Calculates the lowest low in the last 7 bars.
c = ta.stdev(hl2, 7): Calculates the standard deviation of the average of high and low prices (hl2) over the last 7 bars.
d = (a - b) / c: Computes a scaling factor d based on the highest, lowest, and standard deviation. This factor is used to scale the intraday range in the next steps.
e = (high - low): Calculates the intraday range of the candle.
f = e / d: Estimates the standard deviation (f) of the intraday candle price using the scaling factor d.
g = hl2: Defines the intraday midpoint of the candle, which is the average of high and low prices.
i = g + 1 * f, j = g - 1 * f, k = g + 3 * f, l = g - 3 * f: Calculate values representing coverage of +1 SD, -1 SD, +3 SD, and -3 SD from the intraday midpoint.
The script utilizes historical high, low, and standard deviation values to dynamically estimate the standard deviation of the intraday candle, providing a measure of volatility for the current price range. This estimation is then used to construct a modified box plot around the intraday midpoint.
In addition I have included a 7 period hull moving average just to see the overall trend direction.
Conclusion:
The "Nasan Modified Box Plots" indicator on TradingView is a dynamic visualization tool that provides insights into the distribution of price ranges over a specified period. It adapts to changing market conditions by incorporating historical data in the calculation of a scaling factor (d). The indicator constructs a modified box plot, where the size of the box and the whiskers is determined by recent volatility
NSDT Lattice WebThis script creates a "web" by connecting different points of candles. All configurable by the trader.
There are 4 basic parts to a candle:
Open, High, Low, and Close
With this script, you can connect any point of one candle in the past to any point of another current candle.
For example:
High to High, High to Low, High to Open, High to close
Low to High, Low to Low, Low to Open, Low to Close
Open to High, Open to Low, Open to Open, Open to Close
Close to High, Close to Low, Close to Open, Close to Close
The script will change the line colors based on whether the current plot is higher or lower than the previous plot.
Try out different connection points to see what works for you. Connecting High to High and Low to Low, might easily show you when the market is making higher highs or lower lows, indicating a potential movement.
Run it on replay at a higher speed and see how it may potentially help identify area of congestion or trends.
Bar metrics / quantifytools— Overview
Rather than eyeball evaluating bullishness/bearishness in any given bar, bar metrics allow a quantified approach using three basic fundamental data points: relative close, relative volatility and relative volume. These data points are visualized in a discreet data dashboard form, next to all real-time bars. Each value also has a dot in front, representing color coded extremes in the values.
Relative close represents position of bar's close relative to high and low, high of bar being 100% and low of bar being 0%. Relative close indicates strength of bulls/bears in a given bar, the higher the better for bulls, the lower the better for bears. Relative volatility (bar range, high - low) and relative volume are presented in a form of a multiplier, relative to their respective moving averages (SMA 20). A value of 1x indicates volume/volatility being on par with moving average, 2x indicates volume/volatility being twice as much as moving average and so on. Relative volume and volatility can be used for measuring general market participant interest, the "weight of the bar" as it were.
— Features
Users can gauge past bar metrics using lookback via input menu. Past bars, especially recent ones, are helpful for giving context for current bar metrics. Lookback bars are highlighted on the chart using a yellow box and metrics presented on the data dashboard with lookback symbols:
To inspect bar metric data and its implications, users can highlight bars with specified bracket values for each metric:
When bar highlighter is toggled on and desired bar metric values set, alert for the specified combination can be toggled on via alert menu. Note that bar highlighter must be enabled in order for alerts to function.
— Visuals
Bar metric dots are gradient colored the following way:
Relative volatility & volume
0x -> 1x / Neutral (white) -> Light (yellow)
1x -> 1.7x / Light (yellow) -> Medium (orange)
1.7x -> 2.4x / Medium (orange) -> Heavy (red)
Relative close
0% -> 25% / Heavy bearish (red) -> Light bearish (dark red)
25% -> 45% / Light bearish (dark red) -> Neutral (white)
45% - 55% / Neutral (white)
55% -> 75% / Neutral (white) -> Light bullish (dark green)
75% -> 100% / Light bullish (dark green) -> Heavy bullish (green)
All colors can be adjusted via input menu. Label size, label distance from bar (offset) and text format (regular/stealth) can be adjusted via input menu as well:
— Practical guide
As interpretation of bar metrics is highly contextual, it is especially important to use other means in conjunction with the metrics. Levels, oscillators, moving averages, whatever you have found useful for your process. In short, relative close indicates directional bias and relative volume/volatility indicates "weight" of directional bias.
General interpretation
High relative close, low relative volume/volatility = mildly bullish, bias up/consolidation
High relative close, medium relative volume/volatility = bullish, bias up
High relative close, high relative volume/volatility = exuberantly bullish, bias up/down depending on context
Medium relative close, low relative volume/volatility = noise, no bias
Medium relative close, medium to high relative volume/volatility = indecision, further evidence needed to evaluate bias
Low relative close, low relative volume/volatility = mildly bearish, bias down/consolidation
Low relative close, medium relative volume/volatility = bearish, bias down
Low relative close, high relative volume/volatility = exuberantly bearish, bias down/up depending on context
Nuances & considerations
As to relative close, it's important to note that each bar is a trading range when viewed on a lower timeframe, ES 1W vs. ES 4H:
When relative close is high, bulls were able to push price to range high by the time of close. When relative close is low, bears were able to push price to range low by the time of close. In other words, bulls/bears were able to gain the upper hand over a given trading range, hinting strength for the side that made the final push. When relative close is around middle range (40-60%), it can be said neither side is clearly dominating the range, hinting neutral/indecision bias from a relative close perspective.
As to relative volume/volatility, low values (less than ~0.7x) imply bar has low market participant interest and therefore is likely insignificant, as it is "lacking weight". Values close to or above 1x imply meaningful market participant interest, whereas values well above 1x (greater than ~1.3x) imply exuberance. This exuberance can manifest as initiation (beginning of a trend) or as exhaustion (end of a trend):
AbdulLibraryLibrary "AbdulLibrary"
The library consists of three sections:
Technical Analysis Functions - A collection of tools commonly used by day traders
Trading Setup Filters Functions - A number of filters that help day traders to screen trading signals
Candlestick Pattern Detection Functions - To detect different candlestick patterns that are used in day trading setups
Note that this would have been possible without the help of @ZenAndTheArtOfTrading as I build-up this library after completing his pine script mastery course so big thanks to him
The content of the library are:-
fibLevels(preDayClose, preDayHigh, preDayLow) Calculates Daily Pivot Point and Fibonacci Key Levels
Parameters:
preDayClose : The previous day candle close
preDayHigh : The previous day candle high
preDayLow : The previous day candle low
Returns: Returns Daily Pivot Point and Fibonacci Key Levels as a tuple
bullishFib(canHigh, canLow, fibLevel) Calculates Fibonacci Levels in Bullish move
Parameters:
canHigh : The high of the move
canLow : The low of the move
fibLevel : The Fib level as % you want to calculate
Returns: Returns The Fib level for the Bullish move
bearishFib(canHigh, canLow, fibLevel) Calculates Fibonacci Levels in Bearish move
Parameters:
canHigh : The high of the move
canLow : The low of the move
fibLevel : The Fib level as % you want to calculate
Returns: Returns The Fib level for the Bearish move
getCandleSize() Calculates the size of candle (high - low) in points
Returns: Returns candle size in points
getCandleBodySize() Calculates the size of candle (close - open) in points
Returns: Returns candle body size in points
getHighWickSize() Calculates the high wick size of candle in points
Returns: Returns The high wick size of candle in points
getLowWickSize() Calculates the low wick size of candle in points
Returns: Returns The low wick size of candle in points
getBodyPercentage() Calculates the candle body size as % of overall candle size
Returns: Returns The candle body size as % of overall candle size
isSwingHigh(period) Checks if the price has created new swing high over a period of time
Parameters:
period : The lookback time we want to check for swing high
Returns: Returns True if the current candle or the previous candle is a swing high
isSwingLow(period) Checks if the price has created new swing low over a period of time
Parameters:
period : The lookback time we want to check for swing low
Returns: Returns True if the current candle or the previous candle is a swing low
isDojiSwingHigh(period) Checks if a doji is a swing high over a period of time
Parameters:
period : The lookback time we want to check for swing high
Returns: Returns True if the doji is a swing high
isDojiSwingLow(period) Checks if a doji is a swing low over a period of time
Parameters:
period : The lookback time we want to check for swing low
Returns: Returns True if the doji is a swing low
isBigBody(atrFilter, atr, candleBodySize, multiplier) Checks if a candle has big body compared to ATR
Parameters:
atrFilter : Check if user wants to use ATR to filter candle-setup signals
atr : The ATR value to be used to compare candle body size
candleBodySize : The candle body size
multiplier : The multiplier to be used to compare candle body size
Returns: Returns Boolean true if the candle setup is big
isSmallBody(atrFilter, atr, candleBodySize, multiplier) Checks if a candle has small body compared to ATR
Parameters:
atrFilter : Check if user wants to use ATR to filter candle-setup signals
atr : The ATR value to be used to compare candle body size
candleBodySize : The candle body size
multiplier : The multiplier to be used to compare candle body size
Returns: Returns Boolean true if the candle setup is small
isHammer(fibLevel, colorMatch) Checks if a candle is a hammer based on user input parameters and candle conditions
Parameters:
fibLevel : Fib level to base candle body on
colorMatch : Checks if user needs for the candel to be green
Returns: Returns Boolean - True if the candle setup is hammer
isShootingStar(fibLevel, colorMatch) Checks if a candle is a shooting star based on user input parameters and candle conditions
Parameters:
fibLevel : Fib level to base candle body on
colorMatch : Checks if user needs for the candel to be red
Returns: Returns Boolean - True if the candle setup is star
isBullEngCan(allowance, period) Check if a candle is a bullish engulfing candle
Parameters:
allowance : How many points the candle open is allowed to be off (To allow for gaps)
period : The lookback period for swing low check
Returns: Boolean - True only if the candle is a bullish engulfing candle
isBearEngCan(allowance, period) Check if a candle is a bearish engulfing candle
Parameters:
allowance : How many points the candle open is allowed to be off (To allow for gaps)
period : The lookback period for swing high check
Returns: Boolean - True only if the candle is a bearish engulfing candle
isBullDoji(maxSize, wickLimit, colorFilter) Check if a candle is a bullish doji candle
Parameters:
maxSize : Maximum candle body size as % of total candle size to be considered as doji
wickLimit : Maximum wick size of one wick compared to the other wick
colorFilter : Checks if the doji is green
Returns: Boolean - True if the candle is a bullish doji
isBearDoji(maxSize, wickLimit, colorFilter) Check if a candle is a bearish doji candle
Parameters:
maxSize : Maximum candle body size as % of total candle size to be considered as doji
wickLimit : Maximum wick size of one wick compared to the other wick
colorFilter : Checks if the doji is red
Returns: Boolean - True if the candle is a bearish doji
isBullOutBar() Check if a candle is a bullish outside bar
Returns: Boolean - True if the candle is a bullish outside bar
isInsideBar() Check if a candle is an inside bar
Returns: Returns Boolean - True if a candle is an inside bar
coates moving averages (cma)This indicator uses three moving averages:
2 period low simple ma
2 period high simple ma
9 period least squares ma
The trend is determined by the angle of the moving averages, current close relative the the 9 least squares ma (lsm) and the current close relative to the prior two periods high and low.
When there are consecutive closes inside the prior two candles high and low then a range is signaled:
In ranges the buy zone is between the lowest low and the lowest close of the current range. The sell zone is between the highest high and the highest close. The zones are adjusted as long as the new close is within the prior two candles range:
When price closes above the 2 high ma and the 9 lsm then a bull trend is signaled if all moving averages are angled upward (as seen at #4 in the chart above and #1 the chart below ). If the 9 lsm and / or the 2 low ma continue to angle downward, following a close above the 2 high ma and 9 lsm, then a prolonged range or reversal is expected (#2 in the chart below):
During a bull trend the buy zone is between the 2 low ma and the 9 lsm. The profit target is the 2 high ma:
During dip buying opportunities price should resist closing below the 9 lsm. If there is one close below the 9 lsm then it is a canary in the coalmine that tells us to proceed with caution. This will often signal a range, based on the conditions outlined above. To avoid a prolonged range, or reversal, price needs to immediately react in the direction of the prevailing trend:
If the moving averages are angled down and the most recent close is below the 2 low ma and 9 lsm then trend is fully bearish:
During a bear trend the short zone is between the 2 high ma and 9 lsm. The profit target is the 2 low ma:
When the 2 high ma angles down and the 2 low ma angles up while price closes inside both mas then it indicates a cma squeeze:
Volatility is expected in the direction of the breakout following the squeeze. In this situation traps / shakeouts are common. If there is a wick outside the cma, with a close inside, then it indicates a trap / shakeout. If there is a close outside the 2 high / low ma then it signals a breakout.
A trend is considered balanced when the 9 lsm is roughly equidistant from the 2 low and 2 high mas. If the 9 lsm crosses the 2 high or 2 low ma then it signals exhaustion / imbalance.
For a stop loss I use the prior three periods low, for bull trends, and the prior three periods high for bear trends. I would expect other reliable stops, such as the parabolic sar or bill williams fractal, to be effective as well. The default moving averages should be very effective on all timeframes and assets classes, however this indicator was developed for bitcoin with a focus on higher timeframes such as the 4h, daily and weekly.
As with any other technical indicator there will be bad signals. Proceed with caution and never risk more than you are willing to lose.
Scalper Pro Pattern Recognition & Price ActionOVERVIEW
Scalper Pro is a comprehensive multi-timeframe trading indicator that combines Smart Money Concepts (SMC) with traditional technical analysis to provide scalpers and day traders with high-probability entry and exit signals. This indicator integrates multiple analytical frameworks into a unified visual system designed specifically for short-term trading strategies.
ORIGINALITY & PURPOSE
What Makes This Script Original
This script is not a simple mashup of existing indicators. Instead, it represents a carefully orchestrated integration of complementary analytical methods that work together to solve a specific problem: identifying high-probability scalping opportunities in volatile markets.
The unique value proposition:
Adaptive Trend Filtering System - Combines a customized SuperTrend algorithm with dual-period range filters (Cirrus Cloud) and Hull Moving Average trend cloud to create a three-layer trend confirmation system
Smart Money Concepts Integration - Incorporates institutional trading concepts (Order Blocks, Fair Value Gaps, Break of Structure) with retail technical indicators for a complete market structure view
Dynamic Risk Management - Automatically calculates stop-loss and take-profit levels based on ATR volatility, providing objective position sizing
ADX-Based Market Regime Detection - Identifies ranging vs. trending markets through ADX analysis with visual bar coloring to prevent whipsaws during consolidation
Why Combine These Specific Components
Each component addresses a specific weakness in scalping:
SuperTrend provides the primary directional bias but can generate false signals in ranging markets
Range Filters smooth out noise and confirm trend direction, reducing SuperTrend false positives
ADX Analysis prevents trading during low-volatility consolidation when most indicators fail
SMC Elements identify institutional activity zones where price is likely to react strongly
ATR-Based Risk Management adapts position sizing to current volatility conditions
The synergy creates a system where signals are only generated when multiple confirmation layers align, significantly reducing false signals common in single-indicator approaches.
HOW IT WORKS
Core Calculation Methodology
1. SuperTrend Signal Generation
The script uses a modified SuperTrend algorithm with the following calculation:
ATR = Average True Range (default: 10 periods)
Factor = 7 (default sensitivity multiplier)
Upper Band = Source + (Factor × ATR)
Lower Band = Source - (Factor × ATR)
Directional Logic:
When price crosses above SuperTrend → Bullish signal
When price crosses below SuperTrend → Bearish signal
SuperTrend value is plotted as dynamic support/resistance
Key Modification: The sensitivity parameter (nsensitivity * 7) allows users to adjust the aggressiveness of trend detection without changing the core ATR calculation.
2. Range Filter System (Cirrus Cloud)
The Range Filter uses a smoothed range calculation to filter out market noise:
Smooth Range Calculation:
WPER = (Period × 2) - 1
AVRNG = EMA(|Price - Price |, Period)
Smooth Range = EMA(AVRNG, WPER) × Multiplier
Two-Layer System:
Layer 1: 22-period with 6x multiplier (broader trend)
Layer 2: 15-period with 5x multiplier (tighter price action)
Visual Output: The space between these two filters is colored:
Green fill = Bullish trend (Layer 1 > Layer 2)
Red fill = Bearish trend (Layer 1 < Layer 2)
This creates a "cloud" that expands during strong trends and contracts during consolidation.
3. ADX Market Regime Detection
Calculation:
+DM = Positive Directional Movement
-DM = Negative Directional Movement
True Range = RMA of True Range (15 periods)
+DI = 100 × RMA(+DM, 15) / True Range
-DI = 100 × RMA(-DM, 15) / True Range
ADX = 100 × RMA(|+DI - -DI| / (+DI + -DI), 15)
Threshold System:
ADX < Threshold (default 15) = Ranging market → Bar color changes to purple
ADX > Threshold = Trending market → Normal bar coloring applies
Purpose: This prevents taking trend-following signals during sideways markets where most indicators produce whipsaws.
4. Smart Money Concepts (SMC) Integration
Order Blocks (OB):
Identified using swing high/low detection with customizable pivot length
Bullish OB: Last down-close candle before bullish Break of Structure (BOS)
Bearish OB: Last up-close candle before bearish BOS
Extended forward until price breaks through them
Fair Value Gaps (FVG):
Detected when a three-candle gap exists:
Bullish FVG: Low > High
Bearish FVG: High < Low
Filtered by price delta percentage to ensure significant gaps
Displayed as boxes that delete when price fills the gap
Break of Structure (BOS) vs. Change of Character (CHoCH):
BOS = Price breaks the previous structural high/low in the current trend direction
CHoCH = Price breaks structure in the opposite direction (potential trend reversal)
Both internal (minor) and swing (major) structures are tracked
Equal Highs/Lows (EQH/EQL):
Detected when consecutive swing highs/lows are within ATR threshold
Often indicates liquidity pools that price may sweep before reversing
5. ATR-Based Risk Management
Calculation:
ATR Band = ATR(14) × Risk Multiplier (default 3%)
Stop Loss = Entry - ATR Band (for longs) or Entry + ATR Band (for shorts)
Take Profit Levels:
TP1 = Entry + (Entry - Stop Loss) × 1
TP2 = Entry + (Entry - Stop Loss) × 2
TP3 = Entry + (Entry - Stop Loss) × 3
Dynamic Labels: Stop loss and take profit levels are automatically calculated and displayed as labels on the chart when new signals trigger.
6. Hull Moving Average Trend Cloud
HMA = WMA(2 × WMA(Close, Period/2) - WMA(Close, Period), sqrt(Period))
Period = 600 bars (long-term trend)
The HMA provides a smoothed long-term trend reference that's more responsive than traditional moving averages while filtering out short-term noise.
HOW TO USE THE INDICATOR
Entry Signals
Primary Buy Signal:
SuperTrend changes to green (price crosses above)
ADX shows market is NOT ranging (bars are NOT purple)
Price is within or near a bullish Order Block OR bullish FVG
Cirrus Cloud shows green fill (Layer 1 > Layer 2)
Primary Sell Signal:
SuperTrend changes to red (price crosses below)
ADX shows market is NOT ranging
Price is within or near a bearish Order Block OR bearish FVG
Cirrus Cloud shows red fill (Layer 1 < Layer 2)
Confirmation Layers
Higher Probability Trades Include:
Bullish/Bearish BOS in the same direction as signal
Equal highs/lows being swept before entry
Price respecting premium/discount zones (above/below equilibrium)
Multiple timeframe alignment (use MTF settings)
Exit Strategy
The indicator provides three take-profit levels:
TP1: Conservative target (1:1 risk-reward)
TP2: Moderate target (2:1 risk-reward)
TP3: Aggressive target (3:1 risk-reward)
Suggested Exit Approach:
Close 1/3 position at TP1
Move stop to breakeven
Close 1/3 position at TP2
Trail remaining position or exit at TP3
Risk Management
Stop Loss:
Use the ATR-based stop loss level displayed on chart
Alternatively, use percentage-based stop (adjustable in settings)
Never risk more than 1-2% of account per trade
Position Sizing:
Position Size = (Account Risk $) / (Entry Price - Stop Loss Price)
CUSTOMIZABLE SETTINGS
Core Parameters
Buy/Sell Signals:
Toggle signals on/off
Adjust SuperTrend sensitivity (0.5 - 2.0)
Risk Management:
Show/hide TP/SL levels
ATR period (default: 14)
Risk percentage (default: 3%)
Number of decimal places for price labels
Trend Features:
Cirrus Cloud display toggle
Range filter periods (x1, x2, x3, x4)
Hull MA length for trend cloud
Smart Money Concepts:
Order Block settings (swing length, display count)
Fair Value Gap parameters (auto-threshold, extend length)
Structure detection (internal vs swing)
EQH/EQL threshold
ADX Settings:
ADX length (default: 15)
Sideways threshold (10-30, default: 15)
Bar color toggle
Display Options:
Previous day/week/month high/low levels
Premium/Discount/Equilibrium zones
Trend candle coloring (colored or monochrome)
BEST PRACTICES & TRADING TIPS
Optimal Use Cases
Scalping on lower timeframes (1m, 5m, 15m)
Rapid entry/exit with clear TP levels
ADX filter prevents choppy market entries
Day trading on medium timeframes (30m, 1H)
Stronger trend confirmation
Better risk-reward ratios
Swing trading entries on higher timeframes (4H, Daily)
Higher-probability structural setups
Larger ATR-based stops accommodate volatility
Market Conditions
Best Performance:
Trending markets with clear directional bias
Post-news volatility with defined structure
Markets respecting support/resistance levels
Avoid Trading When:
ADX indicator shows purple bars (ranging market)
Multiple conflicting signals across timeframes
Major news events without clear price structure
Low volume periods (market open/close)
Common Mistakes to Avoid
Ignoring the ADX filter - Taking signals during ranging markets leads to whipsaws
Not waiting for confirmation - Enter only when multiple layers align
Overtrading - Fewer high-quality setups outperform many mediocre ones
Ignoring risk management - Always use the calculated stop losses
Fighting the trend - Trade WITH the SuperTrend and Cirrus Cloud direction
TECHNICAL SPECIFICATIONS
Indicator Type: Overlay (plots on price chart)
Calculation Resources:
Max labels: 500
Max lines: 500
Max boxes: 500
Max bars back: 500
Pine Script Version: 5
Compatible Timeframes: All timeframes (optimized for 1m to 1D)
Compatible Instruments:
Forex pairs
Crypto assets
Stock indices
Individual stocks
Commodities
THEORETICAL FOUNDATION
Trend-Following Concepts
This indicator is based on the principle that markets trend more often than they range, and that trends tend to persist. The SuperTrend component captures this momentum while the range filters prevent premature entries during pullbacks.
Smart Money Theory
The SMC elements are based on the concept that institutional traders (banks, hedge funds) leave footprints in the form of:
Order Blocks: Areas where large orders were placed
Fair Value Gaps: Inefficient price movements that may be revisited
Liquidity Sweeps: Stop hunts before continuation (EQH/EQL)
Volatility-Based Position Sizing
Using ATR for stop-loss placement ensures that stop distances adapt to current market conditions:
Tight stops in low volatility (avoids excessive risk)
Wider stops in high volatility (avoids premature stop-outs)
PERFORMANCE EXPECTATIONS
Realistic Expectations
Win Rate:
Expected: 45-55% (trend-following systems rarely exceed 60%)
Higher win rates on trending days
Lower win rates during consolidation (even with ADX filter)
Risk-Reward Ratio:
Target: 1.5:1 minimum (TP2)
Achievable: 2:1 to 3:1 on strong trends
Drawdowns:
Normal: 10-15% of account during choppy periods
Maximum: Should not exceed 20% with proper risk management
Optimization Tips
Backtesting Recommendations:
Test on at least 1 year of historical data
Include different market conditions (trending, ranging, volatile)
Adjust SuperTrend sensitivity per instrument
Optimize ADX threshold for your specific market
Record trades to identify personal execution errors
FREQUENTLY ASKED QUESTIONS
Q: Can I use this for automated trading?
A: The indicator provides signals, but you'll need to code a strategy script separately for automation. The signals can trigger alerts that connect to trading bots.
Q: Why do I see conflicting signals?
A: This is normal during transition periods. Wait for all confirmation layers to align before entering.
Q: How often should I expect signals?
A: Depends on timeframe and market conditions. On 5m charts during trending markets: 3-7 quality setups per session.
Q: Can I use only some features?
A: Yes, all components can be toggled on/off. However, the system works best with all confirmations active.
Q: What's the difference between internal and swing structures?
A: Internal = minor price structures (smaller pivots). Swing = major price structures (larger pivots). Both provide different levels of confirmation.
DISCLAIMER
This indicator is a tool for technical analysis and should not be the sole basis for trading decisions. Past performance does not guarantee future results. Always:
Use proper risk management
Test on demo accounts first
Never risk more than you can afford to lose
Combine with fundamental analysis when applicable
Understand that no indicator is 100% accurate
License: Mozilla Public License 2.0
Author: DrFXGOD
VERSION HISTORY & UPDATES
Initial Release - Version 1.0
Integrated SuperTrend, Range Filters, ADX, SMC concepts
ATR-based risk management
Multi-timeframe support
Customizable visual elements
SUPPORT & DOCUMENTATION
For questions, suggestions, or bug reports, please comment on the script page or contact the author through TradingView.
Additional Resources:
Smart Money Concepts: Research ICT (Inner Circle Trader) materials
ATR and Volatility: Refer to Wilder's original ATR documentation
SuperTrend Indicator: Study original SuperTrend strategy papers
Scalper Pro Pattern Recognition & Price ActionOVERVIEW
Scalper Pro is a comprehensive multi-timeframe trading indicator that combines Smart Money Concepts (SMC) with traditional technical analysis to provide scalpers and day traders with high-probability entry and exit signals. This indicator integrates multiple analytical frameworks into a unified visual system designed specifically for short-term trading strategies.
ORIGINALITY & PURPOSE
What Makes This Script Original
This script is not a simple mashup of existing indicators. Instead, it represents a carefully orchestrated integration of complementary analytical methods that work together to solve a specific problem: identifying high-probability scalping opportunities in volatile markets.
The unique value proposition:
Adaptive Trend Filtering System - Combines a customized SuperTrend algorithm with dual-period range filters (Cirrus Cloud) and Hull Moving Average trend cloud to create a three-layer trend confirmation system
Smart Money Concepts Integration - Incorporates institutional trading concepts (Order Blocks, Fair Value Gaps, Break of Structure) with retail technical indicators for a complete market structure view
Dynamic Risk Management - Automatically calculates stop-loss and take-profit levels based on ATR volatility, providing objective position sizing
ADX-Based Market Regime Detection - Identifies ranging vs. trending markets through ADX analysis with visual bar coloring to prevent whipsaws during consolidation
Why Combine These Specific Components
Each component addresses a specific weakness in scalping:
SuperTrend provides the primary directional bias but can generate false signals in ranging markets
Range Filters smooth out noise and confirm trend direction, reducing SuperTrend false positives
ADX Analysis prevents trading during low-volatility consolidation when most indicators fail
SMC Elements identify institutional activity zones where price is likely to react strongly
ATR-Based Risk Management adapts position sizing to current volatility conditions
The synergy creates a system where signals are only generated when multiple confirmation layers align, significantly reducing false signals common in single-indicator approaches.
HOW IT WORKS
Core Calculation Methodology
1. SuperTrend Signal Generation
The script uses a modified SuperTrend algorithm with the following calculation:
ATR = Average True Range (default: 10 periods)
Factor = 7 (default sensitivity multiplier)
Upper Band = Source + (Factor × ATR)
Lower Band = Source - (Factor × ATR)
Directional Logic:
When price crosses above SuperTrend → Bullish signal
When price crosses below SuperTrend → Bearish signal
SuperTrend value is plotted as dynamic support/resistance
Key Modification: The sensitivity parameter (nsensitivity * 7) allows users to adjust the aggressiveness of trend detection without changing the core ATR calculation.
2. Range Filter System (Cirrus Cloud)
The Range Filter uses a smoothed range calculation to filter out market noise:
Smooth Range Calculation:
WPER = (Period × 2) - 1
AVRNG = EMA(|Price - Price |, Period)
Smooth Range = EMA(AVRNG, WPER) × Multiplier
Two-Layer System:
Layer 1: 22-period with 6x multiplier (broader trend)
Layer 2: 15-period with 5x multiplier (tighter price action)
Visual Output: The space between these two filters is colored:
Green fill = Bullish trend (Layer 1 > Layer 2)
Red fill = Bearish trend (Layer 1 < Layer 2)
This creates a "cloud" that expands during strong trends and contracts during consolidation.
3. ADX Market Regime Detection
Calculation:
+DM = Positive Directional Movement
-DM = Negative Directional Movement
True Range = RMA of True Range (15 periods)
+DI = 100 × RMA(+DM, 15) / True Range
-DI = 100 × RMA(-DM, 15) / True Range
ADX = 100 × RMA(|+DI - -DI| / (+DI + -DI), 15)
Threshold System:
ADX < Threshold (default 15) = Ranging market → Bar color changes to purple
ADX > Threshold = Trending market → Normal bar coloring applies
Purpose: This prevents taking trend-following signals during sideways markets where most indicators produce whipsaws.
4. Smart Money Concepts (SMC) Integration
Order Blocks (OB):
Identified using swing high/low detection with customizable pivot length
Bullish OB: Last down-close candle before bullish Break of Structure (BOS)
Bearish OB: Last up-close candle before bearish BOS
Extended forward until price breaks through them
Fair Value Gaps (FVG):
Detected when a three-candle gap exists:
Bullish FVG: Low > High
Bearish FVG: High < Low
Filtered by price delta percentage to ensure significant gaps
Displayed as boxes that delete when price fills the gap
Break of Structure (BOS) vs. Change of Character (CHoCH):
BOS = Price breaks the previous structural high/low in the current trend direction
CHoCH = Price breaks structure in the opposite direction (potential trend reversal)
Both internal (minor) and swing (major) structures are tracked
Equal Highs/Lows (EQH/EQL):
Detected when consecutive swing highs/lows are within ATR threshold
Often indicates liquidity pools that price may sweep before reversing
5. ATR-Based Risk Management
Calculation:
ATR Band = ATR(14) × Risk Multiplier (default 3%)
Stop Loss = Entry - ATR Band (for longs) or Entry + ATR Band (for shorts)
Take Profit Levels:
TP1 = Entry + (Entry - Stop Loss) × 1
TP2 = Entry + (Entry - Stop Loss) × 2
TP3 = Entry + (Entry - Stop Loss) × 3
Dynamic Labels: Stop loss and take profit levels are automatically calculated and displayed as labels on the chart when new signals trigger.
6. Hull Moving Average Trend Cloud
HMA = WMA(2 × WMA(Close, Period/2) - WMA(Close, Period), sqrt(Period))
Period = 600 bars (long-term trend)
The HMA provides a smoothed long-term trend reference that's more responsive than traditional moving averages while filtering out short-term noise.
HOW TO USE THE INDICATOR
Entry Signals
Primary Buy Signal:
SuperTrend changes to green (price crosses above)
ADX shows market is NOT ranging (bars are NOT purple)
Price is within or near a bullish Order Block OR bullish FVG
Cirrus Cloud shows green fill (Layer 1 > Layer 2)
Primary Sell Signal:
SuperTrend changes to red (price crosses below)
ADX shows market is NOT ranging
Price is within or near a bearish Order Block OR bearish FVG
Cirrus Cloud shows red fill (Layer 1 < Layer 2)
Confirmation Layers
Higher Probability Trades Include:
Bullish/Bearish BOS in the same direction as signal
Equal highs/lows being swept before entry
Price respecting premium/discount zones (above/below equilibrium)
Multiple timeframe alignment (use MTF settings)
Exit Strategy
The indicator provides three take-profit levels:
TP1: Conservative target (1:1 risk-reward)
TP2: Moderate target (2:1 risk-reward)
TP3: Aggressive target (3:1 risk-reward)
Suggested Exit Approach:
Close 1/3 position at TP1
Move stop to breakeven
Close 1/3 position at TP2
Trail remaining position or exit at TP3
Risk Management
Stop Loss:
Use the ATR-based stop loss level displayed on chart
Alternatively, use percentage-based stop (adjustable in settings)
Never risk more than 1-2% of account per trade
Position Sizing:
Position Size = (Account Risk $) / (Entry Price - Stop Loss Price)
CUSTOMIZABLE SETTINGS
Core Parameters
Buy/Sell Signals:
Toggle signals on/off
Adjust SuperTrend sensitivity (0.5 - 2.0)
Risk Management:
Show/hide TP/SL levels
ATR period (default: 14)
Risk percentage (default: 3%)
Number of decimal places for price labels
Trend Features:
Cirrus Cloud display toggle
Range filter periods (x1, x2, x3, x4)
Hull MA length for trend cloud
Smart Money Concepts:
Order Block settings (swing length, display count)
Fair Value Gap parameters (auto-threshold, extend length)
Structure detection (internal vs swing)
EQH/EQL threshold
ADX Settings:
ADX length (default: 15)
Sideways threshold (10-30, default: 15)
Bar color toggle
Display Options:
Previous day/week/month high/low levels
Premium/Discount/Equilibrium zones
Trend candle coloring (colored or monochrome)
BEST PRACTICES & TRADING TIPS
Optimal Use Cases
Scalping on lower timeframes (1m, 5m, 15m)
Rapid entry/exit with clear TP levels
ADX filter prevents choppy market entries
Day trading on medium timeframes (30m, 1H)
Stronger trend confirmation
Better risk-reward ratios
Swing trading entries on higher timeframes (4H, Daily)
Higher-probability structural setups
Larger ATR-based stops accommodate volatility
Market Conditions
Best Performance:
Trending markets with clear directional bias
Post-news volatility with defined structure
Markets respecting support/resistance levels
Avoid Trading When:
ADX indicator shows purple bars (ranging market)
Multiple conflicting signals across timeframes
Major news events without clear price structure
Low volume periods (market open/close)
Common Mistakes to Avoid
Ignoring the ADX filter - Taking signals during ranging markets leads to whipsaws
Not waiting for confirmation - Enter only when multiple layers align
Overtrading - Fewer high-quality setups outperform many mediocre ones
Ignoring risk management - Always use the calculated stop losses
Fighting the trend - Trade WITH the SuperTrend and Cirrus Cloud direction
TECHNICAL SPECIFICATIONS
Indicator Type: Overlay (plots on price chart)
Calculation Resources:
Max labels: 500
Max lines: 500
Max boxes: 500
Max bars back: 500
Pine Script Version: 5
Compatible Timeframes: All timeframes (optimized for 1m to 1D)
Compatible Instruments:
Forex pairs
Crypto assets
Stock indices
Individual stocks
Commodities
THEORETICAL FOUNDATION
Trend-Following Concepts
This indicator is based on the principle that markets trend more often than they range, and that trends tend to persist. The SuperTrend component captures this momentum while the range filters prevent premature entries during pullbacks.
Smart Money Theory
The SMC elements are based on the concept that institutional traders (banks, hedge funds) leave footprints in the form of:
Order Blocks: Areas where large orders were placed
Fair Value Gaps: Inefficient price movements that may be revisited
Liquidity Sweeps: Stop hunts before continuation (EQH/EQL)
Volatility-Based Position Sizing
Using ATR for stop-loss placement ensures that stop distances adapt to current market conditions:
Tight stops in low volatility (avoids excessive risk)
Wider stops in high volatility (avoids premature stop-outs)
PERFORMANCE EXPECTATIONS
Realistic Expectations
Win Rate:
Expected: 45-55% (trend-following systems rarely exceed 60%)
Higher win rates on trending days
Lower win rates during consolidation (even with ADX filter)
Risk-Reward Ratio:
Target: 1.5:1 minimum (TP2)
Achievable: 2:1 to 3:1 on strong trends
Drawdowns:
Normal: 10-15% of account during choppy periods
Maximum: Should not exceed 20% with proper risk management
Optimization Tips
Backtesting Recommendations:
Test on at least 1 year of historical data
Include different market conditions (trending, ranging, volatile)
Adjust SuperTrend sensitivity per instrument
Optimize ADX threshold for your specific market
Record trades to identify personal execution errors
FREQUENTLY ASKED QUESTIONS
Q: Can I use this for automated trading?
A: The indicator provides signals, but you'll need to code a strategy script separately for automation. The signals can trigger alerts that connect to trading bots.
Q: Why do I see conflicting signals?
A: This is normal during transition periods. Wait for all confirmation layers to align before entering.
Q: How often should I expect signals?
A: Depends on timeframe and market conditions. On 5m charts during trending markets: 3-7 quality setups per session.
Q: Can I use only some features?
A: Yes, all components can be toggled on/off. However, the system works best with all confirmations active.
Q: What's the difference between internal and swing structures?
A: Internal = minor price structures (smaller pivots). Swing = major price structures (larger pivots). Both provide different levels of confirmation.
DISCLAIMER
This indicator is a tool for technical analysis and should not be the sole basis for trading decisions. Past performance does not guarantee future results. Always:
Use proper risk management
Test on demo accounts first
Never risk more than you can afford to lose
Combine with fundamental analysis when applicable
Understand that no indicator is 100% accurate
License: Mozilla Public License 2.0
Author: DrFXGOD
VERSION HISTORY & UPDATES
Initial Release - Version 1.0
Integrated SuperTrend, Range Filters, ADX, SMC concepts
ATR-based risk management
Multi-timeframe support
Customizable visual elements
SUPPORT & DOCUMENTATION
For questions, suggestions, or bug reports, please comment on the script page or contact the author through TradingView.
Additional Resources:
Smart Money Concepts: Research ICT (Inner Circle Trader) materials
ATR and Volatility: Refer to Wilder's original ATR documentation
SuperTrend Indicator: Study original SuperTrend strategy papers
Volume Cluster Heatmap [BackQuant]Volume Cluster Heatmap
A visualization tool that maps traded volume across price levels over a chosen lookback period. It highlights where the market builds balance through heavy participation and where it moves efficiently through low-volume zones. By combining a heatmap, volume profile, and high/low volume node detection, this indicator reveals structural areas of support, resistance, and liquidity that drive price behavior.
What Are Volume Clusters?
A volume cluster is a horizontal aggregation of traded volume at specific price levels, showing where market participants concentrated their buying and selling.
High Volume Nodes (HVN) : Price levels with significant trading activity; often act as support or resistance.
Low Volume Nodes (LVN) : Price levels with little trading activity; price moves quickly through these areas, reflecting low liquidity.
Volume clusters help identify key structural zones, reveal potential reversals, and gauge market efficiency by highlighting where the market is balanced versus areas of thin liquidity.
By creating heatmaps, profiles, and highlighting high and low volume nodes (HVNs and LVNs), it allows traders to see where the market builds balance and where it moves efficiently through thin liquidity zones.
Example: Bitcoin breaking away from the high-volume zone near 118k and moving cleanly through the low-volume pocket around 113k–115k, illustrating how markets seek efficiency:
Core Features
Visual Analysis Components:
Heatmap Display : Displays volume intensity as colored boxes, lines, or a combination for a dynamic view of market participation.
Volume Profile Overlay : Shows cumulative volume per price level along the right-hand side of the chart.
HVN & LVN Labels : Marks high and low volume nodes with color-coded lines and labels.
Customizable Colors & Transparency : Adjust high and low volume colors and minimum transparency for clear differentiation.
Session Reset & Timeframe Control : Dynamically resets clusters at the start of new sessions or chosen timeframes (intraday, daily, weekly).
Alerts
HVN / LVN Alerts : Notify when price reaches a significant high or low volume node.
High Volume Zone Alerts : Trigger when price enters the top X% of cumulative volume, signaling key areas of market interest.
How It Works
Each bar’s volume is distributed proportionally across the horizontal price levels it touches. Over the lookback period, this builds a cumulative volume profile, identifying price levels with the most and least trading activity. The highest cumulative volume levels become HVNs, while the lowest are LVNs. A side volume profile shows aggregated volume per level, and a heatmap overlay visually reinforces market structure.
Applications for Traders
Identify strong support and resistance at HVNs.
Detect areas of low liquidity where price may move quickly (LVNs).
Determine market balance zones where price may consolidate.
Filter noise: because volume clusters aggregate activity into levels, minor fluctuations and irrelevant micro-moves are removed, simplifying analysis and improving strategy development.
Combine with other indicators such as VWAP, Supertrend, or CVD for higher-probability entries and exits.
Use volume clusters to anticipate price reactions to breaking points in thin liquidity zones.
Advanced Display Options
Heatmap Styles : Boxes, lines, or both. Boxes provide a traditional heatmap, lines are better for high granularity data.
Line Mode Example : Simplified line visualization for easier reading at high level counts:
Profile Width & Offset : Adjust spacing and placement of the volume profile for clarity alongside price.
Transparency Control : Lower transparency for more opaque visualization of high-volume zones.
Best Practices for Usage
Reduce the number of levels when using line mode to avoid clutter.
Use HVN and LVN markers in conjunction with volume profiles to plan entries and exits.
Apply session resets to monitor intraday vs. multi-day volume accumulation.
Combine with other technical indicators to confirm high-probability trading signals.
Watch price interactions with LVNs for potential rapid movements and with HVNs for possible support/resistance or reversals.
Technical Notes
Each bar contributes volume proportionally to the price levels it spans, creating a dynamic and accurate representation of traded interest.
Volume profiles are scaled and offset for visual clarity alongside live price.
Alerts are fully integrated for HVN/LVN interaction and high-volume zone entries.
Optimized to handle large lookback windows and numerous price levels efficiently without performance degradation.
This indicator is ideal for understanding market structure, detecting key liquidity areas, and filtering out noise to model price more accurately in high-frequency or algorithmic strategies.
JK_Traders_Reality_LibLibrary "JK_Traders_Reality_Lib"
This library contains common elements used in Traders Reality scripts
calcPvsra(pvsraVolume, pvsraHigh, pvsraLow, pvsraClose, pvsraOpen, redVectorColor, greenVectorColor, violetVectorColor, blueVectorColor, darkGreyCandleColor, lightGrayCandleColor)
calculate the pvsra candle color and return the color as well as an alert if a vector candle has apperared.
Situation "Climax"
Bars with volume >= 200% of the average volume of the 10 previous chart TFs, or bars
where the product of candle spread x candle volume is >= the highest for the 10 previous
chart time TFs.
Default Colors: Bull bars are green and bear bars are red.
Situation "Volume Rising Above Average"
Bars with volume >= 150% of the average volume of the 10 previous chart TFs.
Default Colors: Bull bars are blue and bear are violet.
Parameters:
pvsraVolume (float) : the instrument volume series (obtained from request.sequrity)
pvsraHigh (float) : the instrument high series (obtained from request.sequrity)
pvsraLow (float) : the instrument low series (obtained from request.sequrity)
pvsraClose (float) : the instrument close series (obtained from request.sequrity)
pvsraOpen (float) : the instrument open series (obtained from request.sequrity)
redVectorColor (simple color) : red vector candle color
greenVectorColor (simple color) : green vector candle color
violetVectorColor (simple color) : violet/pink vector candle color
blueVectorColor (simple color) : blue vector candle color
darkGreyCandleColor (simple color) : regular volume candle down candle color - not a vector
lightGrayCandleColor (simple color) : regular volume candle up candle color - not a vector
@return
adr(length, barsBack)
Parameters:
length (simple int) : how many elements of the series to calculate on
barsBack (simple int) : starting possition for the length calculation - current bar or some other value eg last bar
@return adr the adr for the specified lenght
adrHigh(adr, fromDo)
Calculate the ADR high given an ADR
Parameters:
adr (float) : the adr
fromDo (simple bool) : boolean flag, if false calculate traditional adr from high low of today, if true calcualte from exchange midnight
@return adrHigh the position of the adr high in price
adrLow(adr, fromDo)
Parameters:
adr (float) : the adr
fromDo (simple bool) : boolean flag, if false calculate traditional adr from high low of today, if true calcualte from exchange midnight
@return adrLow the position of the adr low in price
splitSessionString(sessXTime)
given a session in the format 0000-0100:23456 split out the hours and minutes
Parameters:
sessXTime (simple string) : the session time string usually in the format 0000-0100:23456
@return
calcSessionStartEnd(sessXTime, gmt)
calculate the start and end timestamps of the session
Parameters:
sessXTime (simple string) : the session time string usually in the format 0000-0100:23456
gmt (simple string) : the gmt offset string usually in the format GMT+1 or GMT+2 etc
@return
drawOpenRange(sessXTime, sessXcol, showOrX, gmt)
draw open range for a session
Parameters:
sessXTime (simple string) : session string in the format 0000-0100:23456
sessXcol (simple color) : the color to be used for the opening range box shading
showOrX (simple bool) : boolean flag to toggle displaying the opening range
gmt (simple string) : the gmt offset string usually in the format GMT+1 or GMT+2 etc
@return void
drawSessionHiLo(sessXTime, showRectangleX, showLabelX, sessXcolLabel, sessXLabel, gmt, sessionLineStyle)
Parameters:
sessXTime (simple string) : session string in the format 0000-0100:23456
showRectangleX (simple bool)
showLabelX (simple bool)
sessXcolLabel (simple color) : the color to be used for the hi/low lines and label
sessXLabel (simple string) : the session label text
gmt (simple string) : the gmt offset string usually in the format GMT+1 or GMT+2 etc
sessionLineStyle (simple string) : the line stile for the session high low lines
@return void
calcDst()
calculate market session dst on/off flags
@return indicating if DST is on or off for a particular region
timestampPreviousDayOfWeek(previousDayOfWeek, hourOfDay, gmtOffset, oneWeekMillis)
Timestamp any of the 6 previous days in the week (such as last Wednesday at 21 hours GMT)
Parameters:
previousDayOfWeek (simple string) : Monday or Satruday
hourOfDay (simple int) : the hour of the day when psy calc is to start
gmtOffset (simple string) : the gmt offset string usually in the format GMT+1 or GMT+2 etc
oneWeekMillis (simple int) : the amount if time for a week in milliseconds
@return the timestamp of the psy level calculation start time
getdayOpen()
get the daily open - basically exchange midnight
@return the daily open value which is float price
newBar(res)
new_bar: check if we're on a new bar within the session in a given resolution
Parameters:
res (simple string) : the desired resolution
@return true/false is a new bar for the session has started
toPips(val)
to_pips Convert value to pips
Parameters:
val (float) : the value to convert to pips
@return the value in pips
rLabel(ry, rtext, rstyle, rcolor, valid, labelXOffset)
a function that draws a right aligned lable for a series during the current bar
Parameters:
ry (float) : series float the y coordinate of the lable
rtext (simple string) : the text of the label
rstyle (simple string) : the style for the lable
rcolor (simple color) : the color for the label
valid (simple bool) : a boolean flag that allows for turning on or off a lable
labelXOffset (int) : how much to offset the label from the current position
rLabelOffset(ry, rtext, rstyle, rcolor, valid, labelOffset)
a function that draws a right aligned lable for a series during the current bar
Parameters:
ry (float) : series float the y coordinate of the lable
rtext (string) : the text of the label
rstyle (simple string) : the style for the lable
rcolor (simple color) : the color for the label
valid (simple bool) : a boolean flag that allows for turning on or off a lable
labelOffset (int)
rLabelLastBar(ry, rtext, rstyle, rcolor, valid, labelXOffset)
a function that draws a right aligned lable for a series only on the last bar
Parameters:
ry (float) : series float the y coordinate of the lable
rtext (string) : the text of the label
rstyle (simple string) : the style for the lable
rcolor (simple color) : the color for the label
valid (simple bool) : a boolean flag that allows for turning on or off a lable
labelXOffset (int) : how much to offset the label from the current position
drawLine(xSeries, res, tag, xColor, xStyle, xWidth, xExtend, isLabelValid, xLabelOffset, validTimeFrame)
a function that draws a line and a label for a series
Parameters:
xSeries (float) : series float the y coordinate of the line/label
res (simple string) : the desired resolution controlling when a new line will start
tag (simple string) : the text for the lable
xColor (simple color) : the color for the label
xStyle (simple string) : the style for the line
xWidth (simple int) : the width of the line
xExtend (simple string) : extend the line
isLabelValid (simple bool) : a boolean flag that allows for turning on or off a label
xLabelOffset (int)
validTimeFrame (simple bool) : a boolean flag that allows for turning on or off a line drawn
drawLineDO(xSeries, res, tag, xColor, xStyle, xWidth, xExtend, isLabelValid, xLabelOffset, validTimeFrame)
a function that draws a line and a label for the daily open series
Parameters:
xSeries (float) : series float the y coordinate of the line/label
res (simple string) : the desired resolution controlling when a new line will start
tag (simple string) : the text for the lable
xColor (simple color) : the color for the label
xStyle (simple string) : the style for the line
xWidth (simple int) : the width of the line
xExtend (simple string) : extend the line
isLabelValid (simple bool) : a boolean flag that allows for turning on or off a label
xLabelOffset (int)
validTimeFrame (simple bool) : a boolean flag that allows for turning on or off a line drawn
drawPivot(pivotLevel, res, tag, pivotColor, pivotLabelColor, pivotStyle, pivotWidth, pivotExtend, isLabelValid, validTimeFrame, levelStart, pivotLabelXOffset)
draw a pivot line - the line starts one day into the past
Parameters:
pivotLevel (float) : series of the pivot point
res (simple string) : the desired resolution
tag (simple string) : the text to appear
pivotColor (simple color) : the color of the line
pivotLabelColor (simple color) : the color of the label
pivotStyle (simple string) : the line style
pivotWidth (simple int) : the line width
pivotExtend (simple string) : extend the line
isLabelValid (simple bool) : boolean param allows to turn label on and off
validTimeFrame (simple bool) : only draw the line and label at a valid timeframe
levelStart (int) : basically when to start drawing the levels
pivotLabelXOffset (int) : how much to offset the label from its current postion
@return the pivot line series
getPvsraFlagByColor(pvsraColor, redVectorColor, greenVectorColor, violetVectorColor, blueVectorColor, lightGrayCandleColor)
convert the pvsra color to an internal code
Parameters:
pvsraColor (color) : the calculated pvsra color
redVectorColor (simple color) : the user defined red vector color
greenVectorColor (simple color) : the user defined green vector color
violetVectorColor (simple color) : the user defined violet vector color
blueVectorColor (simple color) : the user defined blue vector color
lightGrayCandleColor (simple color) : the user defined regular up candle color
@return pvsra internal code
updateZones(pvsra, direction, boxArr, maxlevels, pvsraHigh, pvsraLow, pvsraOpen, pvsraClose, transperancy, zoneupdatetype, zonecolor, zonetype, borderwidth, coloroverride, redVectorColor, greenVectorColor, violetVectorColor, blueVectorColor)
a function that draws the unrecovered vector candle zones
Parameters:
pvsra (int) : internal code
direction (simple int) : above or below the current pa
boxArr (array) : the array containing the boxes that need to be updated
maxlevels (simple int) : the maximum number of boxes to draw
pvsraHigh (float) : the pvsra high value series
pvsraLow (float) : the pvsra low value series
pvsraOpen (float) : the pvsra open value series
pvsraClose (float) : the pvsra close value series
transperancy (simple int) : the transparencfy of the vecor candle zones
zoneupdatetype (simple string) : the zone update type
zonecolor (simple color) : the zone color if overriden
zonetype (simple string) : the zone type
borderwidth (simple int) : the width of the border
coloroverride (simple bool) : if the color overriden
redVectorColor (simple color) : the user defined red vector color
greenVectorColor (simple color) : the user defined green vector color
violetVectorColor (simple color) : the user defined violet vector color
blueVectorColor (simple color) : the user defined blue vector color
cleanarr(arr)
clean an array from na values
Parameters:
arr (array) : the array to clean
@return if the array was cleaned
calcPsyLevels(oneWeekMillis, showPsylevels, psyType, sydDST)
calculate the psy levels
4 hour res based on how mt4 does it
mt4 code
int Li_4 = iBarShift(NULL, PERIOD_H4, iTime(NULL, PERIOD_W1, Li_0)) - 2 - Offset;
ObjectCreate("PsychHi", OBJ_TREND, 0, Time , iHigh(NULL, PERIOD_H4, iHighest(NULL, PERIOD_H4, MODE_HIGH, 2, Li_4)), iTime(NULL, PERIOD_W1, 0), iHigh(NULL, PERIOD_H4,
iHighest(NULL, PERIOD_H4, MODE_HIGH, 2, Li_4)));
so basically because the session is 8 hours and we are looking at a 4 hour resolution we only need to take the highest high an lowest low of 2 bars
we use the gmt offset to adjust the 0000-0800 session to Sydney open which is at 2100 during dst and at 2200 otherwize. (dst - spring foward, fall back)
keep in mind sydney is in the souther hemisphere so dst is oposite of when london and new york go into dst
Parameters:
oneWeekMillis (simple int) : a constant value
showPsylevels (simple bool) : should psy levels be calculated
psyType (simple string) : the type of Psylevels - crypto or forex
sydDST (bool) : is Sydney in DST
@return
adrHiLo(length, barsBack, fromDO)
Parameters:
length (simple int) : how many elements of the series to calculate on
barsBack (simple int) : starting possition for the length calculation - current bar or some other value eg last bar
fromDO (simple bool) : boolean flag, if false calculate traditional adr from high low of today, if true calcualte from exchange midnight
@return adr, adrLow and adrHigh - the adr, the position of the adr High and adr Low with respect to price
drawSessionHiloLite(sessXTime, showRectangleX, showLabelX, sessXcolLabel, sessXLabel, gmt, sessionLineStyle, sessXcol)
Parameters:
sessXTime (simple string) : session string in the format 0000-0100:23456
showRectangleX (simple bool)
showLabelX (simple bool)
sessXcolLabel (simple color) : the color to be used for the hi/low lines and label
sessXLabel (simple string) : the session label text
gmt (simple string) : the gmt offset string usually in the format GMT+1 or GMT+2 etc
sessionLineStyle (simple string) : the line stile for the session high low lines
sessXcol (simple color) : - the color for the box color that will color the session
@return void
msToHmsString(ms)
converts milliseconds into an hh:mm string. For example, 61000 ms to '0:01:01'
Parameters:
ms (int) : - the milliseconds to convert to hh:mm
@return string - the converted hh:mm string
countdownString(openToday, closeToday, showMarketsWeekends, oneDay)
that calculates how much time is left until the next session taking the session start and end times into account. Note this function does not work on intraday sessions.
Parameters:
openToday (int) : - timestamps of when the session opens in general - note its a series because the timestamp was created using the dst flag which is a series itself thus producing a timestamp series
closeToday (int) : - timestamp of when the session closes in general - note its a series because the timestamp was created using the dst flag which is a series itself thus producing a timestamp series
@return a countdown of when next the session opens or 'Open' if the session is open now
showMarketsWeekends (simple bool)
oneDay (simple int)
countdownStringSyd(sydOpenToday, sydCloseToday, showMarketsWeekends, oneDay)
that calculates how much time is left until the next session taking the session start and end times into account. special case of intraday sessions like sydney
Parameters:
sydOpenToday (int)
sydCloseToday (int)
showMarketsWeekends (simple bool)
oneDay (simple int)
Live Market - Performance MonitorLive Market — Performance Monitor
Study material (no code) — step-by-step training guide for learners
________________________________________
1) What this tool is — short overview
This indicator is a live market performance monitor designed for learning. It scans price, volume and volatility, detects order blocks and trendline events, applies filters (volume & ATR), generates trade signals (BUY/SELL), creates simple TP/SL trade management, and renders a compact dashboard summarizing market state, risk and performance metrics.
Use it to learn how multi-factor signals are constructed, how Greeks-style sensitivity is replaced by volatility/ATR reasoning, and how a live dashboard helps monitor trade quality.
________________________________________
2) Quick start — how a learner uses it (step-by-step)
1. Add the indicator to a chart (any ticker / timeframe).
2. Open inputs and review the main groups: Order Block, Trendline, Signal Filters, Display.
3. Start with defaults (OB periods ≈ 7, ATR multiplier 0.5, volume threshold 1.2) and observe the dashboard on the last bar.
4. Walk the chart back in time (use the last-bar update behavior) and watch how signals, order blocks, trendlines, and the performance counters change.
5. Run the hands-on labs below to build intuition.
________________________________________
3) Main configurable inputs (what you can tweak)
• Order Block Relevant Periods (default ~7): number of consecutive candles used to define an order block.
• Min. Percent Move for Valid OB (threshold): minimum percent move required for a valid order block.
• Number of OB Channels: how many past order block lines to keep visible.
• Trendline Period (tl_period): pivot lookback for detecting highs/lows used to draw trendlines.
• Use Wicks for Trendlines: whether pivot uses wicks or body.
• Extension Bars: how far trendlines are projected forward.
• Use Volume Filter + Volume Threshold Multiplier (e.g., 1.2): requires volume to be greater than multiplier × average volume.
• Use ATR Filter + ATR Multiplier: require bar range > ATR × multiplier to filter noise.
• Show Targets / Table settings / Colors for visualization.
________________________________________
4) Core building blocks — what the script computes (plain language)
Price & trend:
• Spot / LTP: current close price.
• EMA 9 / 21 / 50: fast, medium, slow moving averages to define short/medium trend.
o trend_bullish: EMA9 > EMA21 > EMA50
o trend_bearish: EMA9 < EMA21 < EMA50
o trend_neutral: otherwise
Volatility & noise:
• ATR (14): average true range used for dynamic target and filter sizing.
• dynamic_zone = ATR × atr_multiplier: minimum bar range required for meaningful move.
• Annualized volatility: stdev of price changes × sqrt(252) × 100 — used to classify volatility (HIGH/MEDIUM/LOW).
Momentum & oscillators:
• RSI 14: overbought/oversold indicator (thresholds 70/30).
• MACD: EMA(12)-EMA(26) and a 9-period signal line; histogram used for momentum direction and strength.
• Momentum (ta.mom 10): raw momentum over 10 bars.
Mean reversion / band context:
• Bollinger Bands (20, 2σ): upper, mid, lower.
o price_position measures where price sits inside the band range as 0–100.
Volume metrics:
• avg_volume = SMA(volume, 20) and volume_spike = volume > avg_volume × volume_threshold
o volume_ratio = volume / avg_volume
Support & Resistance:
• support_level = lowest low over 20 bars
• resistance_level = highest high over 20 bars
• current_position = percent of price between support & resistance (0–100)
________________________________________
5) Order Block detection — concept & logic
What it tries to find: a bar (the base) followed by N candles in the opposite direction (a classical order block setup), with a minimum % move to qualify. The script records the high/low of the base candle, averages them, and plots those levels as OB channels.
How learners should think about it (conceptual):
1. An order block is a signature area where institutions (theory) left liquidity — often seen as a large bar followed by a sequence of directional candles.
2. This indicator uses a configurable number of subsequent candles to confirm that the pattern exists.
3. When found, it stores and displays the base candle’s high/low area so students can see how price later reacts to those zones.
Implementation note for learners: the tool keeps a limited history of OB lines (ob_channels). When new OBs exceed the count, the oldest lines are removed — good practice to avoid clutter.
________________________________________
6) Trendline detection — idea & interpretation
• The script finds pivot highs and lows using a symmetric lookback (tl_period and half that as right/left).
• It then computes a trendline slope from successive pivots and projects the line forward (extension_bars).
• Break detection: Resistance break = close crosses above the projected resistance line; Support break = close crosses below projected support.
Learning tip: trendlines here are computed from pivot points and time. Watch how changing tl_period (bigger = smoother, fewer pivots) alters the trendlines and break signals.
________________________________________
7) Signal generation & filters — step-by-step
1. Primary triggers:
o Bullish trigger: order block bullish OR resistance trendline break.
o Bearish trigger: bearish order block OR support trendline break.
2. Filters applied (both must pass unless disabled):
o Volume filter: volume must be > avg_volume × volume_threshold.
o ATR filter: bar range (high-low) must exceed ATR × atr_multiplier.
o Not in an existing trade: new trades only start if trade_active is false.
3. Trend confirmation:
o The primary trigger is only confirmed if trend is bullish/neutral for buys or bearish/neutral for sells (EMA alignment).
4. Result:
o When confirmed, a long or short trade is activated with TP/SL calculated from ATR multiples.
________________________________________
8) Trade management — what the tool does after a signal
• Entry management: the script marks a trade as trade_active and sets long_trade or short_trade flags.
• TP & SL rules:
o Long: TP = high + 2×ATR ; SL = low − 1×ATR
o Short: TP = low − 2×ATR ; SL = high + 1×ATR
• Monitoring & exit:
o A trade closes when price reaches TP or SL.
o When TP/SL hit, the indicator updates win_count and total_pnl using a very simple calculation (difference between TP/SL and previous close).
o Visual lines/labels are drawn for TP and updated as the trade runs.
Important learner notes:
• The script does not store a true entry price (it uses close in its P&L math), so PnL is an approximation — treat this as a learning proxy, not a position accounting system.
• There’s no sizing, slippage, or fee accounted — students must manually factor these when translating to real trades.
• This indicator is not a backtesting strategy; strategy.* functions would be needed for rigorous backtest results.
________________________________________
9) Signal strength & helper utilities
• Signal strength is a composite score (0–100) made up of four signals worth 25 points each:
1. RSI extreme (overbought/oversold) → 25
2. Volume spike → 25
3. MACD histogram magnitude increasing → 25
4. Trend existence (bull or bear) → 25
• Progress bars (text glyphs) are used to visually show RSI and signal strength on the table.
Learning point: composite scoring is a way to combine orthogonal signals — study how changing weights changes outcomes.
________________________________________
10) Dashboard — how to read each section (walkthrough)
The dashboard is split into sections; here's how to interpret them:
1. Market Overview
o LTP / Change%: immediate price & daily % change.
2. RSI & MACD
o RSI value plus progress bar (overbought 70 / oversold 30).
o MACD histogram sign indicates bullish/bearish momentum.
3. Volume Analysis
o Volume ratio (current / average) and whether there’s a spike.
4. Order Block Status
o Buy OB / Sell OB: the average base price of detected order blocks or “No Signal.”
5. Signal Status
o 🔼 BUY or 🔽 SELL if confirmed, or ⚪ WAIT.
o No-trade vs Active indicator summarizing market readiness.
6. Trend Analysis
o Trend direction (from EMAs), market sentiment score (composite), volatility level and band/position metrics.
7. Performance
o Win Rate = wins / signals (percentage)
o Total PnL = cumulative PnL (approximate)
o Bull / Bear Volume = accumulated volumes attributable to signals
8. Support & Resistance
o 20-bar highest/lowest — use as nearby reference points.
9. Risk & R:R
o Risk Level from ATR/price as a percent.
o R:R Ratio computed from TP/SL if a trade is active.
10. Signal Strength & Active Trade Status
• Numeric strength + progress bar and whether a trade is currently active with TP/SL display.
________________________________________
11) Alerts — what will notify you
The indicator includes pre-built alert triggers for:
• Bullish confirmed signal
• Bearish confirmed signal
• TP hit (long/short)
• SL hit (long/short)
• No-trade zone
• High signal strength (score > 75%)
Training use: enable alerts during a replay session to be notified when the indicator would have signalled.
________________________________________
12) Labs — hands-on exercises for learners (step-by-step)
Lab A — Order Block recognition
1. Pick a 15–30 minute timeframe on a liquid ticker.
2. Use default OB periods (7). Mark each time the dashboard shows a Buy/Sell OB.
3. Manually inspect the chart at the base candle and the following sequence — draw the OB zone by hand and watch later price reactions to it.
4. Repeat with OB periods 5 and 10; note stability vs noise.
Lab B — Trendline break confirmation
1. Increase trendline period (e.g., 20), watch trendlines form from pivots.
2. When a resistance break is flagged, compare with MACD & volume: was momentum aligned?
3. Note false breaks vs confirmed moves — change extension_bars to see projection effects.
Lab C — Filter sensitivity
1. Toggle Use Volume Filter off, and record the number and quality of signals in a 2-day window.
2. Re-enable volume filter and change threshold from 1.2 → 1.6; note how many low-quality signals are filtered out.
Lab D — Trade management simulation
1. For each signalled trade, record the time, close entry approximation, TP, SL, and eventual hit/miss.
2. Compute actual PnL if you had entered at the open of the next bar to compare with the script’s PnL math.
3. Tabulate win rate and average R:R.
Lab E — Performance review & improvement
1. Build a spreadsheet of signals over 30–90 periods with columns: Date, Signal type, Entry price (real), TP, SL, Exit, PnL, Notes.
2. Analyze which filters or indicators contributed most to winners vs losers and adjust weights.
________________________________________
13) Common pitfalls, assumptions & implementation notes (things to watch)
• P&L simplification: total_pnl uses close as a proxy entry price. Real entry/exit prices and slippage are not recorded — so PnL is approximate.
• No position sizing or money management: the script doesn’t compute position size from equity or risk percent.
• Signal confirmation logic: composite "signal_strength" is a simple 4×25 point scheme — explore different weights or additional signals.
• Order block detection nuance: the script defines the base candle and checks the subsequent sequence. Be sure to verify whether the intended candle direction (base being bullish vs bearish) aligns with academic/your trading definition — read the code carefully and test.
• Trendline slope over time: slope is computed using timestamps; small differences may make lines sensitive on very short timeframes — using bar_index differences is usually more stable.
• Not a true backtester: to evaluate performance statistically you must transform the logic into a strategy script that places hypothetical orders and records exact entry/exit prices.
________________________________________
14) Suggested improvements for advanced learners
• Record true entry price & timestamp for accurate PnL.
• Add position sizing: risk % per trade using SL distance and account size.
• Convert to strategy. (Pine Strategy)* to run formal backtests with equity curves, drawdowns, and metrics (Sharpe, Sortino).
• Log trades to an external spreadsheet (via alerts + webhook) for offline analysis.
• Add statistics: average win/loss, expectancy, max drawdown.
• Add additional filters: news time blackout, market session filters, multi-timeframe confirmation.
• Improve OB detection: combine wick/body, volume spike at base bar, and liquidity sweep detection.
________________________________________
15) Glossary — quick definitions
• ATR (Average True Range): measure of typical range; used to size targets and stops.
• EMA (Exponential Moving Average): trend smoothing giving more weight to recent prices.
• RSI (Relative Strength Index): momentum oscillator; >70 overbought, <30 oversold.
• MACD: momentum oscillator using difference of two EMAs.
• Bollinger Bands: volatility bands around SMA.
• Order Block: a base candle area with subsequent confirmation candles; a zone of institutional interest (learning model).
• Pivot High/Low: local turning point defined by candles on both sides.
• Signal Strength: combined score from multiple indicators.
• Win Rate: proportion of signals that hit TP vs total signals.
• R:R (Risk:Reward): ratio of potential reward (TP distance) to risk (entry to SL).
________________________________________
16) Limitations & assumptions (be explicit)
• This is an indicator for learning — not a trading robot or broker connection.
• No slippage, fees, commissions or tie-in to real orders are considered.
• The logic is heuristic (rule-of-thumb), not a guarantee of performance.
• Results are sensitive to timeframe, market liquidity, and parameter choices.
________________________________________
17) Practical classroom / study plan (4 sessions)
• Session 1 — Foundations: Understand EMAs, ATR, RSI, MACD, Bollinger Bands. Run the indicator and watch how these numbers change on a single day.
• Session 2 — Zones & Filters: Study order blocks and trendlines. Test volume & ATR filters and note changes in false signals.
• Session 3 — Simulated trading: Manually track 20 signals, compute real PnL and compare to the dashboard.
• Session 4 — Improvement plan: Propose changes (e.g., better PnL accounting, alternative OB rule) and test their impact.
________________________________________
18) Quick reference checklist for each signal
1. Was an order block or trendline break detected? (primary trigger)
2. Did volume meet threshold? (filter)
3. Did ATR filter (bar size) show a real move? (filter)
4. Was trend aligned (EMA 9/21/50)? (confirmation)
5. Signal confirmed → mark entry approximation, TP, SL.
6. Monitor dashboard (Signal Strength, Volatility, No-trade zone, R:R).
7. After exit, log real entry/exit, compute actual PnL, update spreadsheet.
________________________________________
19) Educational caveat & final note
This tool is built for training and analysis: it helps you see how common technical building blocks combine into trade ideas, but it is not a trading recommendation. Use it to develop judgment, to test hypotheses, and to design robust systems with proper backtesting and risk control before risking capital.
________________________________________
20) Disclaimer (must include)
Training & Educational Only — This material and the indicator are provided for educational purposes only. Nothing here is investment advice or a solicitation to buy or sell financial instruments. Past simulated or historical performance does not predict future results. Always perform full backtesting and risk management, and consider seeking advice from a qualified financial professional before trading with real capital.
________________________________________
Yelober - Market Internal direction+ Key levelsYelober – Market Internals + Key Levels is a focused intraday trading tool that helps you spot high-probability price direction by anchoring decisions to structure that matters: yesterday’s RTH High/Low, today’s pre-market High/Low, and a fast Value Area/POC from the prior session. Paired with a compact market internals dashboard (NYSE/NASDAQ UVOL vs. DVOL ratios, VOLD slopes, TICK/TICKQ momentum, and optional VIX trend), it gives you a real-time read on breadth so you can choose which direction to trade, when to enter (breaks, retests, or fades at PMH/PML/VAH/VAL/POC), and how to plan exits as internals confirm or deteriorate. On top of these intraday decision benefits, it also allows traders—in a very subtle but powerful way—to keep an eye on the VIX and immediately recognize significant spikes or sharp decreases that should be factored in before entering a trade, or used as a quick signal to modify an existing position. In short: clear levels for the chart, live internals for the context, and a smarter, rules-based path to execution.
# Yelober – Market Internals + Key Levels
*A TradingView indicator for session key levels + real‑time market internals (NYSE/NASDAQ TICK, UVOL/DVOL/VOLD, and VIX).*
**Script name in Pine:** `Yelober - Market Internal direction+ Key levels` (Pine v6)
---
## 1) What this indicator does
**Purpose:** Help intraday traders quickly find high‑probability reaction zones and read market internals momentum without switching charts. It overlays yesterday/today’s **automatic price levels** on your active chart and shows a **market breadth table** that summarizes NYSE/NASDAQ buying pressure and TICK direction, with an optional VIX trend read.
### Key features at a glance
* **Automatic Price Levels (overlay on chart)**
* Yesterday’s High/Low of Day (**yHoD**, **yLoD**)
* Extended Hours High/Low (**yEHH**, **yEHL**) across yesterday AH + today pre‑market
* Today’s Pre‑Market High/Low (**PMH**, **PML**)
* Yesterday’s **Value Area High/Low** (**VAH/VAL**) and **Point of Control (POC)** computed from a volume profile of yesterday’s **regular session**
* Smart de‑duplication:
* Shows **only the higher** of (yEHH vs PMH) and **only the lower** of (yEHL vs PML) to avoid redundant bands
* **Market Breadth Table (on‑chart table)**
* **NYSE ratio** = UVOL/DVOL (signed) with **VOLD slope** from session open
* **NASDAQ ratio** = UVOLQ/DVOLQ (signed) with **VOLDQ slope** from session open
* **TICK** and **TICKQ**: live cumulative ratio and short‑term slope
* **VIX** (optional): current value + slope over a configurable lookback/timeframe
* Color‑coded trends with sensible thresholds and optional normalization
---
## 2) How to use it (trader workflow)
1. **Mark your reaction zones**
* Watch **yHoD/yLoD**, **PMH/PML**, and **VAH/VAL/POC** for first touches, break/retest, and failure tests.
* Expect increased responsiveness when multiple levels cluster (e.g., PMH ≈ VAH ≈ daily pivot).
2. **Read the breadth panel for context**
* **NYSE/NASDAQ ratio** (>1 = more up‑volume than down‑volume; <−1 = down‑dominant). Strong green across both favors long setups; red favors short setups.
* **VOLD slopes** (NYSE & NASDAQ): positive and accelerating → broadening participation; negative → persistent pressure.
* **TICK/TICKQ**: cumulative ratio and **slope arrows** (↗ / ↘ / →). Use the slope to gauge **near‑term thrust or fade**.
* **VIX slope**: rising VIX (red) often coincides with risk‑off; falling VIX (green) with risk‑on.
3. **Confluence = higher confidence**
* Example: Price reclaims **PMH** while **NYSE/NASDAQ ratios** print green and **TICK slopes** point ↗ — consider break‑and‑go; if VIX slope is ↘, that adds risk‑on confidence.
* Example: Price rejects **VAH** while **VOLD slopes** roll negative and VIX ↗ — consider fade/reversal.
4. **Risk management**
* Place stops just beyond key levels tested; if breadth flips, tighten or exit.
> **Timeframes:** Works best on 1–15m charts for intraday. Value Area is computed from **yesterday’s RTH**; choose a smaller calculation timeframe (e.g., 5–15m) for stable profiles.
---
## 3) Inputs & settings (what each option controls)
### Global Style
* **Enable all automatic price levels**: master toggle for yHoD/yLoD, yEHH/yEHL, PMH/PML, VAH/VAL/POC.
* **Line style/width**: applies to all drawn levels.
* **Label size/style** and **label color linking**: use the same color as the line or override with a global label color.
* **Maximum bars lookback**: how far the script scans to build yesterday metrics (performance‑sensitive).
### Value Area / Volume Profile
* **Enable Value Area calculations** *(on by default)*: computes yesterday’s **POC**, **VAH**, **VAL** from a simplified intraday volume profile built from yesterday’s **regular session bars**.
* **Max Volume Profile Points** *(default 50)*: lower values = faster; higher = more precise.
* **Value Area Calculation Timeframe** *(default 15)*: the security timeframe used when collecting yesterday’s highs/lows/volumes.
### Individual Level Toggles & Colors
* **yHoD / yLoD** (yesterday high/low)
* **yEHH / yEHL** (yesterday AH + today pre‑market extremes)
* **PMH / PML** (today pre‑market extremes)
* **VAH / VAL / POC** (yesterday RTH value area + point of control)
### Market Breadth Panel
* **Show NYSE / NASDAQ / VIX**: choose which series to display in the table.
* **Table Position / Size / Background Color**: UI placement and legibility.
* **Slope Averaging Periods** *(default 5)*: number of recent TICK/TICKQ ratio points used in slope calculation.
* **Candles for Rate** *(default 10)* & **Normalize Rate**: VIX slope calculation as % change between `now` and `n` candles ago; normalize divides by `n`.
* **VIX Timeframe**: optionally compute VIX on a higher TF (e.g., 15, 30, 60) for a smoother regime read.
* **Volume Normalization** (NYSE & NASDAQ): display VOLD slopes scaled to `tens/thousands/millions/10th millions` for readable magnitudes; color thresholds adapt to your choice.
---
## 4) Data sources & definitions
* **UVOL/VOLD (NYSE)** and **UVOLQ/DVOLQ/VOLDQ (NASDAQ)** via `request.security()`
* **Ratio** = `UVOL/DVOL` (signed; negative when down‑volume dominates)
* **VOLD slope** ≈ `(VOLD_now − VOLD_open) / bars_since_open`, then normalized per your setting
* **TICK/TICKQ**: cumulative sum of prints this session with **positives vs negatives ratio**, plus a simple linear regression **slope** of the last `N` ratio values
* **VIX**: value and slope across a user‑selected timeframe and lookback
* **Sessions (EST/EDT)**
* **Regular:** 09:30–16:00
* **Pre‑Market:** 04:00–09:30
* **After Hours:** 16:00–20:00
* **Extended‑hours extremes** combine **yesterday AH** + **today PM**
> **Note:** All session checks are done with TradingView’s `time(…,"America/New_York")` context. If your broker’s RTH differs (e.g., futures), adjust expectations accordingly.
---
## 5) How the algorithms work (plain English)
### A) Key Levels
* **Yesterday’s RTH High/Low**: scans yesterday’s bars within 09:30–16:00 and records the extremes + bar indices.
* **Extended Hours**: scans yesterday AH and today PM to get **yEHH/yEHL**. Script shows **either yEHH or PMH** (whichever is **higher**) and **either yEHL or PML** (whichever is **lower**) to avoid duplicate bands stacked together.
* **Value Area & POC (RTH only)**
* Build a coarse volume profile with `Max Volume Profile Points` buckets across the price range formed by yesterday’s RTH bars.
* Distribute each bar’s volume uniformly across the buckets it spans (fast approximation to keep Pine within execution limits).
* **POC** = bucket with max volume. **VA** expands from POC outward until **70%** of cumulative volume is enclosed → yields **VAH/VAL**.
### B) Market Breadth Table
* **NYSE/NASDAQ Ratio**: signed UVOL/DVOL with basic coloring.
* **VOLD Slopes**: from session open to current, normalized to human‑readable units; colors flip green/red based on thresholds that map to your normalization setting (e.g., ±2M for NYSE, ±3.5×10M for NASDAQ).
* **TICK/TICKQ Slope**: linear regression over the last `N` ratio points → **↗ / → / ↘** with the rounded slope value.
* **VIX Slope**: % change between now and `n` candles ago (optionally divided by `n`). Red when rising beyond threshold; green when falling.
---
## 6) Recommended presets
* **Stocks (liquid, intraday)**
* Value Area **ON**, `Max Volume Points` = **40–60**, **Timeframe** = **5–15**
* Breadth: show **NYSE & NASDAQ & VIX**, `Slope periods` = **5–8**, `Candles for rate` = **10–20**, **Normalize VIX** = **ON**
* **Index futures / very high‑volume symbols**
* If you see Pine timeouts, set `Max Volume Points` = **20–40** or temporarily **disable Value Area**.
* Keep breadth panel **ON** (it’s light). Consider **VIX timeframe = 15/30** for regime clarity.
---
## 7) Tips, edge cases & performance
* **Performance:** The volume profile is capped (`maxBarsToProcess ≤ 500` and bucketed) to keep it responsive. If you experience slowdowns, reduce `Max Volume Points`, `Maximum bars lookback`, or disable Value Area.
* **Redundant lines:** The script **intentionally suppresses** PMH/PML when yEHH/yEHL are more extreme, and vice‑versa.
* **Label visibility:** Use `Label style = none` if you only want clean lines and read values from the right‑end labels.
* **Futures/RTH differences:** Value Area is from **yesterday’s RTH** only; for 24h instruments the RTH period may not reflect overnight structure.
* **Session transitions:** PMH/PML tracking stops as soon as RTH starts; values persist as static levels for the session.
---
## 8) Known limitations
* Uses public TradingView symbols: `UVOL`, `VOLD`, `UVOLQ`, `DVOLQ`, `VOLDQ`, `TICK`, `TICKQ`, `VIX`. If your data plan or region limits any symbol, the corresponding table rows may show `na`.
* The VA/POC approximation assumes uniform distribution of each bar’s volume across its high–low. That’s fast but not a tick‑level profile.
* Works best on US equities with standard NY session; alternative sessions may need code changes.
---
## 9) Troubleshooting
* **“Script is too slow / timed out”** → Lower `Max Volume Points`, lower `Maximum bars lookback`, or toggle **OFF** `Enable Value Area calculations` for that instrument.
* **Missing breadth values** → Ensure the symbols above load on your account; try reloading chart or switching timeframes once.
* **Overlapping labels** → Set `Label style = none` or reduce label size.
---
## 10) Version / license / contribution
* **Version:** Initial public release (Pine v6).
* **Author:** © yelober
* **License:** Free for community use and enhancement. Please keep author credit.
* **Contributing:** Open PRs/ideas: presets, alert conditions, multi‑day VA composites, optional mid‑value (`(VAH+VAL)/2`), session filter for futures, and alertable state machine for breadth regime transitions.
---
## 11) Quick start (TL;DR)
1. Add the indicator and **keep default settings**.
2. Trade **reactions** at yHoD/yLoD/PMH/PML/VAH/VAL/POC.
3. Use the **breadth table**: look for **green ratios + ↗ slopes** (risk‑on) or **red ratios + ↘ slopes** (risk‑off). Check **VIX** slope for confirmation.
4. Manage risk around levels; when breadth flips against you, tighten or exit.
---
### Changelog (public)
* **v1.0:** First community release with automatic RTH levels, VA/POC approximation, breadth dashboard (NYSE/NASDAQ/TICK/TICKQ/VIX) with normalization and adaptive color thresholds.
Pivot and Wick Boxes with Break Signals█ OVERVIEW
This Pine Script® indicator draws support and resistance levels based on high and low pivot points and the wicks of pivot candles. When the price breaks these levels, breakout signals are generated, with an optional volume filter for greater precision. The indicator is fully customizable, allowing users to adjust box styles, pivot length, and signal settings.
█ CONCEPTS
The indicator relies on several key elements to identify and visualize important price levels and trading signals:
Pivot Identification
High and low pivots are detected using the ta.pivothigh and ta.pivotlow functions with a configurable pivot length. Boxes are drawn based on the pivot level and the wick of the pivot candle (top for high pivots, bottom for low pivots).
List of Features
1 — High and Low Pivot Boxes: The indicator draws boxes based on high pivot candles (red) and low pivot candles (green) and their wicks, with options to customize colors, border styles, and background gradient. Boxes are limited to 500 bars back, meaning support and resistance levels older than 500 candles are not displayed to maintain chart clarity.
2 — Breakout Signals: When the price closes above the upper edge of a high pivot box, a breakout signal is generated (green triangle below the bar). When the price closes below the lower edge of a low pivot box, a breakout signal is generated (red triangle above the bar).
Signals can be filtered using volume, requiring the volume at the breakout to exceed the average volume multiplied by a configurable multiplier.
3 — Box Management: The indicator limits the number of displayed boxes (default is 15 for high pivots and 15 for low pivots), removing the oldest boxes when the limit is reached. Boxes older than 500 bars are automatically removed.
Volume Filtering
An optional volume filter allows users to require breakout signals to be confirmed by volume exceeding the moving average of volume (calculated over a selected period, default is 20 days).
█ OTHER SECTIONS
FEATURES
• Show High/Low Pivot Boxes: Enables or disables the display of boxes for high and low pivots.
• Pivot Length: Specifies the number of bars back and forward for detecting pivots (default is 5).
• Max Boxes: Sets the maximum number of boxes for high and low pivots (default is 15).
• Volume Filter: Enables a volume filter for breakout signals, with a configurable multiplier and average period.
• Box Style: Allows customization of border color, background gradient, border width, and border style (solid, dashed, dotted).
HOW TO USE
1 — Add the indicator to your TradingView chart by selecting “Pivot and Wick Boxes with Break Signals” from the indicators list.
2 — Configure the settings in the indicator’s dialog window, adjusting pivot length, maximum number of boxes, colors, and style.
3 — Enable the volume filter if you want signals to be confirmed by high volume.
4 — Monitor breakout signals (green triangles below bars for upward breakouts, red triangles above bars for downward breakouts) on the chart.
LIMITATIONS
• New pivots are detected with a delay equal to the set pivot length. A lower pivot length value results in faster pivot detection but produces pivots with less significance as support or resistance levels compared to those generated with a longer value.
• Breakout signals may produce false signals in volatile market conditions, especially without the volume filter.
• Boxes are limited to 500 bars back, which may exclude older pivots on long-term charts.
Reversal Point Dynamics⇋ Reversal Point Dynamics (RPD)
This is not an indicator; it is a complete system for deconstructing the mechanics of a market reversal. Reversal Point Dynamics (RPD) moves far beyond simplistic pattern recognition, venturing into a deep analysis of the underlying forces that cause trends to exhaust, pause, and turn. It is engineered from the ground up to identify high-probability reversal points by quantifying the confluence of market dynamics in real-time.
Where other tools provide a static signal, RPD delivers a dynamic probability. It understands that a true market turning point is not a single event, but a cascade of failing momentum, structural breakdown, and a shift in market order. RPD's core engine meticulously analyzes each of these dynamic components—the market's underlying state, its velocity and acceleration, its degree of chaos (entropy), and its structural framework. These forces are synthesized into a single, unified Probability Score, offering you an unprecedented, transparent view into the conviction behind every potential reversal.
This is not a "black box" system. It is an open-architecture engine designed to empower the discerning trader. Featuring real-time signal projection, an integrated Fibonacci R2R Target Engine, and a comprehensive dashboard that acts as your Dynamics Control Center , RPD gives you a complete, holistic view of the market's state.
The Theoretical Core: Deconstructing Market Dynamics
RPD's analytical power is born from the intelligent synthesis of multiple, distinct theoretical models. Each pillar of the engine analyzes a different facet of market behavior. The convergence of these analyses—the "Singularity" event referenced in the dashboard—is what generates the final, high-conviction probability score.
1. Pillar One: Quantum State Analysis (QSA)
This is the foundational analysis of the market's current state within its recent context. Instead of treating price as a random walk, QSA quantizes it into a finite number of discrete "states."
Formulaic Concept: The engine establishes a price range using the highest high and lowest low over the Adaptive Analysis Period. This range is then divided into a user-defined number of Analysis Levels. The current price is mapped to one of these states (e.g., in a 9-level system, State 0 is the absolute low, and State 8 is the absolute high).
Analytical Edge: This acts as a powerful foundational filter. The engine will only begin searching for reversal signals when the market has reached a statistically stretched, extreme state (e.g., State 0 or 8). The Edge Sensitivity input allows you to control exactly how close to this extreme edge the price must be, ensuring you are trading from points of maximum potential exhaustion.
2. Pillar Two: Price State Roc (PSR) - The Dynamics of Momentum
This pillar analyzes the kinetic forces of the market: its velocity and acceleration. It understands that it’s not just where the price is, but how it got there that matters.
Formulaic Concept: The psr function calculates two derivatives of price.
Velocity: (price - price ). This measures the speed and direction of the current move.
Acceleration: (velocity - velocity ). This measures the rate of change in that speed. A negative acceleration (deceleration) during a strong rally is a critical pre-reversal warning, indicating momentum is fading even as price may be pushing higher.
Analytical Edge: The engine specifically hunts for exhaustion patterns where momentum is clearly decelerating as price reaches an extreme state. This is the mechanical signature of a weakening trend.
3. Pillar Three: Market Entropy Analysis - The Dynamics of Order & Chaos
This is RPD's chaos filter, a concept borrowed from information theory. Entropy measures the degree of randomness or disorder in the market's price action.
Formulaic Concept: The calculateEntropy function analyzes recent price changes. A market moving directionally and smoothly has low entropy (high order). A market chopping back and forth without direction has high entropy (high chaos). The value is normalized between 0 and 1.
Analytical Edge: The most reliable trades occur in low-entropy, ordered environments. RPD uses the Entropy Threshold to disqualify signals that attempt to form in chaotic, unpredictable conditions, providing a powerful shield against whipsaw markets.
4. Pillar Four: The Synthesis Engine & Probability Calculation
This is where all the dynamic forces converge. The final probability score is a weighted calculation that heavily rewards confluence.
Formulaic Concept: The calculateProbability function intelligently assembles the final score:
A Base Score is established from trend strength and entropy.
An Entropy Score adds points for low entropy (order) and subtracts for high entropy (chaos).
A significant Divergence Bonus is awarded for a classic momentum divergence.
RSI & Volume Bonuses are added if momentum oscillators are in extreme territory or a volume spike confirms institutional interest.
MTF & Adaptive Bonuses add further weight for alignment with higher timeframe structure.
Analytical Edge: A signal backed by multiple dynamic forces (e.g., extreme state + decelerating momentum + low entropy + volume spike) will receive an exponentially higher probability score. This is the very essence of analyzing reversal point dynamics.
The Command Center: Mastering the Inputs
Every input is a precise lever of control, allowing you to fine-tune the RPD engine to your exact trading style, market, and timeframe.
🧠 Core Algorithm
Predictive Mode (Early Detection):
What It Is: Enables the engine to search for potential reversals on the current, unclosed bar.
How It Works: Analyzes intra-bar acceleration and state to identify developing exhaustion. These signals are marked with a ' ? ' and are tentative.
How To Use It: Enable for scalping or very aggressive day trading to get the earliest possible indication. Disable for swing trading or a more conservative approach that waits for full bar confirmation.
Live Signal Mode (Current Bar):
What It Is: A highly aggressive mode that plots tentative signals with a ' ! ' on the live bar based on projected price and momentum. These signals repaint intra-bar.
How It Works: Uses a linear regression projection of the close to anticipate a reversal.
How To Use It: For advanced users who use intra-bar dynamics for execution and understand the nature of repainting signals.
Adaptive Analysis Period:
What It Is: The main lookback period for the QSA, PSR, and Entropy calculations. This is the engine's "memory."
How It Works: A shorter period makes the engine highly sensitive to local price swings. A longer period makes it focus only on major, significant market structure.
How To Use It: Scalping (1-5m): 15-25. Day Trading (15m-1H): 25-40. Swing Trading (4H+): 40-60.
Fractal Strength (Bars):
What It Is: Defines the strength of the pivot detection used for confirming reversal events.
How It Works: A value of '2' requires a candle's high/low to be more extreme than the two bars to its left and right.
How To Use It: '2' is a robust standard. Increase to '3' for an even stricter definition of a structural pivot, which will result in fewer signals.
MTF Multiplier:
What It Is: Integrates pivot data from a higher timeframe for confluence.
How It Works: A multiplier of '4' on a 15-minute chart will pull pivot data from the 1-hour chart (15 * 4 = 60m).
How To Use It: Set to a multiple that corresponds to your preferred higher timeframe for contextual analysis.
🎯 Signal Settings
Min Probability %:
What It Is: Your master quality filter. A signal is only plotted if its score exceeds this threshold.
How It Works: Directly filters the output of the final probability calculation.
How To Use It: High-Quality (80-95): For A+ setups only. Balanced (65-75): For day trading. Aggressive (50-60): For scalping.
Min Signal Distance (Bars):
What It Is: A noise filter that prevents signals from clustering in choppy conditions.
How It Works: Enforces a "cooldown" period of N bars after a signal.
How To Use It: Increase in ranging markets to focus on major swings. Decrease on lower timeframes.
Entropy Threshold:
What It Is: Your "chaos shield." Sets the maximum allowable market randomness for a signal.
How It Works: If calculated entropy is above this value, the signal is invalidated.
How To Use It: Lower values (0.1-0.5): Extremely strict. Higher values (0.7-1.0): More lenient. 0.85 is a good balance.
Adaptive Entropy & Aggressive Mode:
What It Is: Toggles for dynamically adjusting the engine's core parameters.
How It Works: Adaptive Entropy can slightly lower the required probability in strong trends. Aggressive Mode uses more lenient settings across the board.
How To Use It: Keep Adaptive on. Use Aggressive Mode sparingly, primarily for scalping highly volatile assets.
📊 State Analysis
Analysis Levels:
What It Is: The number of discrete "states" for the QSA.
How It Works: More levels create a finer-grained analysis of price location.
How To Use It: 6-7 levels are ideal. Increasing to 9 can provide more precision on very volatile assets.
Edge Sensitivity:
What It Is: Defines how close to the absolute top/bottom of the range price must be.
How It Works: '0' means price must be in the absolute highest/lowest state. '3' allows a signal within the top/bottom 3 states.
How To Use It: '3' provides a good balance. Lower it to '1' or '0' if you only want to trade extreme exhaustion.
The Dashboard: Your Dynamics Control Center
The dashboard provides a transparent, real-time view into the engine's brain. Use it to understand the context behind every signal and to gauge the current market environment at a glance.
🎯 UNIFIED PROB SCORE
TOTAL SCORE: The highest probability score (either Peak or Valley) the engine is currently calculating. This is your main at-a-glance conviction metric. The "Singularity" header refers to the event where market dynamics align—the event RPD is built to detect.
Quality: A human-readable interpretation of the Total Score. "EXCEPTIONAL" (🌟) is a rare, A+ confluence event. "STRONG" (💪) is a high-quality, tradable setup.
📊 ORDER FLOW & COMPONENT ANALYSIS
Volume Spike: Shows if the current volume is significantly higher than average (YES/NO). A 'YES' adds major confirmation.
Peak/Valley Conf: This breaks down the probability score into its directional components, showing you the separate confidence levels for a potential top (Peak) versus a bottom (Valley).
🌌 MARKET STRUCTURE
HTF Trend: Shows the direction of the underlying trend based on a Supertrend calculation.
Entropy: The current market chaos reading. "🔥 LOW" is an ideal, ordered state for trading. "😴 HIGH" is a warning of choppy, unpredictable conditions.
🔮 FIB & R2R ZONE (Large Dashboard)
This section gives you the status of the Fibonacci Target Engine. It shows if an Active Channel (entry zone) or Stop Zone (invalidation zone) is active and displays the precise price levels for the static entry, target, and stop calculated at the time of the signal.
🛡️ FILTERS & PREDICTIVES (Large Dashboard)
This panel provides a status check on all the bonus filters. It shows the current RSI Status, whether a Divergence is present, and if a Live Pending signal is forming.
The Visual Interface: A Symphony of Data
Every visual element is designed for instant, intuitive interpretation of market dynamics.
Signal Markers: These are the primary outputs of the engine.
▼/▲ b: A fully confirmed signal that has passed all filters.
? b: A tentative signal generated in Predictive Mode, indicating developing dynamics.
◈ b: This diamond icon replaces the standard triangle when the signal is confirmed by a strong momentum divergence, highlighting it as a superior setup where dynamics are misaligned with price.
Harmonic Wave: The flowing, colored wave around the price.
What It Represents: The market's "flow dynamic" and volatility.
How to Interpret It: Expanding waves show increasing volatility. The color is tied to the "Quantum Color" in your theme, representing the underlying energy field of the market.
Entropy Particles: The small dots appearing above/below price.
What They Represent: A direct visualization of the "order dynamic."
How to Interpret Them: Their presence signifies a low-entropy, ordered state ideal for trading. Their color indicates the direction of momentum (PSR velocity). Their absence means the market is too chaotic (high entropy).
The Fibonacci Target Engine: The dynamic R2R system appearing post-signal.
Static Fib Levels: Colored horizontal lines representing the market's "structural dynamic."
The Green "Active Channel" Box: Your zone of consideration. An area to manage a potential entry.
Development Philosophy
Reversal Point Dynamics was engineered to answer a fundamental question: can we objectively measure the forces behind a market turn? It is a synthesis of concepts from market microstructure, statistics, and information theory. The objective was never to create a "perfect" system, but to build a robust decision-support tool that provides a measurable, statistical edge by focusing on the principle of confluence.
By demanding that multiple, independent market dynamics align simultaneously, RPD filters out the vast majority of market noise. It is designed for the trader who thinks in terms of probability and risk management, not in terms of certainties. It is a tool to help you discount the obvious and bet on the unexpected alignment of market forces.
"Markets are constantly in a state of uncertainty and flux and money is made by discounting the obvious and betting on the unexpected."
— George Soros
Trade with insight. Trade with anticipation.
— Dskyz, for DAFE Trading Systems
Tensor Market Analysis Engine (TMAE)# Tensor Market Analysis Engine (TMAE)
## Advanced Multi-Dimensional Mathematical Analysis System
*Where Quantum Mathematics Meets Market Structure*
---
## 🎓 THEORETICAL FOUNDATION
The Tensor Market Analysis Engine represents a revolutionary synthesis of three cutting-edge mathematical frameworks that have never before been combined for comprehensive market analysis. This indicator transcends traditional technical analysis by implementing advanced mathematical concepts from quantum mechanics, information theory, and fractal geometry.
### 🌊 Multi-Dimensional Volatility with Jump Detection
**Hawkes Process Implementation:**
The TMAE employs a sophisticated Hawkes process approximation for detecting self-exciting market jumps. Unlike traditional volatility measures that treat price movements as independent events, the Hawkes process recognizes that market shocks cluster and exhibit memory effects.
**Mathematical Foundation:**
```
Intensity λ(t) = μ + Σ α(t - Tᵢ)
```
Where market jumps at times Tᵢ increase the probability of future jumps through the decay function α, controlled by the Hawkes Decay parameter (0.5-0.99).
**Mahalanobis Distance Calculation:**
The engine calculates volatility jumps using multi-dimensional Mahalanobis distance across up to 5 volatility dimensions:
- **Dimension 1:** Price volatility (standard deviation of returns)
- **Dimension 2:** Volume volatility (normalized volume fluctuations)
- **Dimension 3:** Range volatility (high-low spread variations)
- **Dimension 4:** Correlation volatility (price-volume relationship changes)
- **Dimension 5:** Microstructure volatility (intrabar positioning analysis)
This creates a volatility state vector that captures market behavior impossible to detect with traditional single-dimensional approaches.
### 📐 Hurst Exponent Regime Detection
**Fractal Market Hypothesis Integration:**
The TMAE implements advanced Rescaled Range (R/S) analysis to calculate the Hurst exponent in real-time, providing dynamic regime classification:
- **H > 0.6:** Trending (persistent) markets - momentum strategies optimal
- **H < 0.4:** Mean-reverting (anti-persistent) markets - contrarian strategies optimal
- **H ≈ 0.5:** Random walk markets - breakout strategies preferred
**Adaptive R/S Analysis:**
Unlike static implementations, the TMAE uses adaptive windowing that adjusts to market conditions:
```
H = log(R/S) / log(n)
```
Where R is the range of cumulative deviations and S is the standard deviation over period n.
**Dynamic Regime Classification:**
The system employs hysteresis to prevent regime flipping, requiring sustained Hurst values before regime changes are confirmed. This prevents false signals during transitional periods.
### 🔄 Transfer Entropy Analysis
**Information Flow Quantification:**
Transfer entropy measures the directional flow of information between price and volume, revealing lead-lag relationships that indicate future price movements:
```
TE(X→Y) = Σ p(yₜ₊₁, yₜ, xₜ) log
```
**Causality Detection:**
- **Volume → Price:** Indicates accumulation/distribution phases
- **Price → Volume:** Suggests retail participation or momentum chasing
- **Balanced Flow:** Market equilibrium or transition periods
The system analyzes multiple lag periods (2-20 bars) to capture both immediate and structural information flows.
---
## 🔧 COMPREHENSIVE INPUT SYSTEM
### Core Parameters Group
**Primary Analysis Window (10-100, Default: 50)**
The fundamental lookback period affecting all calculations. Optimization by timeframe:
- **1-5 minute charts:** 20-30 (rapid adaptation to micro-movements)
- **15 minute-1 hour:** 30-50 (balanced responsiveness and stability)
- **4 hour-daily:** 50-100 (smooth signals, reduced noise)
- **Asset-specific:** Cryptocurrency 20-35, Stocks 35-50, Forex 40-60
**Signal Sensitivity (0.1-2.0, Default: 0.7)**
Master control affecting all threshold calculations:
- **Conservative (0.3-0.6):** High-quality signals only, fewer false positives
- **Balanced (0.7-1.0):** Optimal risk-reward ratio for most trading styles
- **Aggressive (1.1-2.0):** Maximum signal frequency, requires careful filtering
**Signal Generation Mode:**
- **Aggressive:** Any component signals (highest frequency)
- **Confluence:** 2+ components agree (balanced approach)
- **Conservative:** All 3 components align (highest quality)
### Volatility Jump Detection Group
**Volatility Dimensions (2-5, Default: 3)**
Determines the mathematical space complexity:
- **2D:** Price + Volume volatility (suitable for clean markets)
- **3D:** + Range volatility (optimal for most conditions)
- **4D:** + Correlation volatility (advanced multi-asset analysis)
- **5D:** + Microstructure volatility (maximum sensitivity)
**Jump Detection Threshold (1.5-4.0σ, Default: 3.0σ)**
Standard deviations required for volatility jump classification:
- **Cryptocurrency:** 2.0-2.5σ (naturally volatile)
- **Stock Indices:** 2.5-3.0σ (moderate volatility)
- **Forex Major Pairs:** 3.0-3.5σ (typically stable)
- **Commodities:** 2.0-3.0σ (varies by commodity)
**Jump Clustering Decay (0.5-0.99, Default: 0.85)**
Hawkes process memory parameter:
- **0.5-0.7:** Fast decay (jumps treated as independent)
- **0.8-0.9:** Moderate clustering (realistic market behavior)
- **0.95-0.99:** Strong clustering (crisis/event-driven markets)
### Hurst Exponent Analysis Group
**Calculation Method Options:**
- **Classic R/S:** Original Rescaled Range (fast, simple)
- **Adaptive R/S:** Dynamic windowing (recommended for trading)
- **DFA:** Detrended Fluctuation Analysis (best for noisy data)
**Trending Threshold (0.55-0.8, Default: 0.60)**
Hurst value defining persistent market behavior:
- **0.55-0.60:** Weak trend persistence
- **0.65-0.70:** Clear trending behavior
- **0.75-0.80:** Strong momentum regimes
**Mean Reversion Threshold (0.2-0.45, Default: 0.40)**
Hurst value defining anti-persistent behavior:
- **0.35-0.45:** Weak mean reversion
- **0.25-0.35:** Clear ranging behavior
- **0.15-0.25:** Strong reversion tendency
### Transfer Entropy Parameters Group
**Information Flow Analysis:**
- **Price-Volume:** Classic flow analysis for accumulation/distribution
- **Price-Volatility:** Risk flow analysis for sentiment shifts
- **Multi-Timeframe:** Cross-timeframe causality detection
**Maximum Lag (2-20, Default: 5)**
Causality detection window:
- **2-5 bars:** Immediate causality (scalping)
- **5-10 bars:** Short-term flow (day trading)
- **10-20 bars:** Structural flow (swing trading)
**Significance Threshold (0.05-0.3, Default: 0.15)**
Minimum entropy for signal generation:
- **0.05-0.10:** Detect subtle information flows
- **0.10-0.20:** Clear causality only
- **0.20-0.30:** Very strong flows only
---
## 🎨 ADVANCED VISUAL SYSTEM
### Tensor Volatility Field Visualization
**Five-Layer Resonance Bands:**
The tensor field creates dynamic support/resistance zones that expand and contract based on mathematical field strength:
- **Core Layer (Purple):** Primary tensor field with highest intensity
- **Layer 2 (Neutral):** Secondary mathematical resonance
- **Layer 3 (Info Blue):** Tertiary harmonic frequencies
- **Layer 4 (Warning Gold):** Outer field boundaries
- **Layer 5 (Success Green):** Maximum field extension
**Field Strength Calculation:**
```
Field Strength = min(3.0, Mahalanobis Distance × Tensor Intensity)
```
The field amplitude adjusts to ATR and mathematical distance, creating dynamic zones that respond to market volatility.
**Radiation Line Network:**
During active tensor states, the system projects directional radiation lines showing field energy distribution:
- **8 Directional Rays:** Complete angular coverage
- **Tapering Segments:** Progressive transparency for natural visual flow
- **Pulse Effects:** Enhanced visualization during volatility jumps
### Dimensional Portal System
**Portal Mathematics:**
Dimensional portals visualize regime transitions using category theory principles:
- **Green Portals (◉):** Trending regime detection (appear below price for support)
- **Red Portals (◎):** Mean-reverting regime (appear above price for resistance)
- **Yellow Portals (○):** Random walk regime (neutral positioning)
**Tensor Trail Effects:**
Each portal generates 8 trailing particles showing mathematical momentum:
- **Large Particles (●):** Strong mathematical signal
- **Medium Particles (◦):** Moderate signal strength
- **Small Particles (·):** Weak signal continuation
- **Micro Particles (˙):** Signal dissipation
### Information Flow Streams
**Particle Stream Visualization:**
Transfer entropy creates flowing particle streams indicating information direction:
- **Upward Streams:** Volume leading price (accumulation phases)
- **Downward Streams:** Price leading volume (distribution phases)
- **Stream Density:** Proportional to information flow strength
**15-Particle Evolution:**
Each stream contains 15 particles with progressive sizing and transparency, creating natural flow visualization that makes information transfer immediately apparent.
### Fractal Matrix Grid System
**Multi-Timeframe Fractal Levels:**
The system calculates and displays fractal highs/lows across five Fibonacci periods:
- **8-Period:** Short-term fractal structure
- **13-Period:** Intermediate-term patterns
- **21-Period:** Primary swing levels
- **34-Period:** Major structural levels
- **55-Period:** Long-term fractal boundaries
**Triple-Layer Visualization:**
Each fractal level uses three-layer rendering:
- **Shadow Layer:** Widest, darkest foundation (width 5)
- **Glow Layer:** Medium white core line (width 3)
- **Tensor Layer:** Dotted mathematical overlay (width 1)
**Intelligent Labeling System:**
Smart spacing prevents label overlap using ATR-based minimum distances. Labels include:
- **Fractal Period:** Time-based identification
- **Topological Class:** Mathematical complexity rating (0, I, II, III)
- **Price Level:** Exact fractal price
- **Mahalanobis Distance:** Current mathematical field strength
- **Hurst Exponent:** Current regime classification
- **Anomaly Indicators:** Visual strength representations (○ ◐ ● ⚡)
### Wick Pressure Analysis
**Rejection Level Mathematics:**
The system analyzes candle wick patterns to project future pressure zones:
- **Upper Wick Analysis:** Identifies selling pressure and resistance zones
- **Lower Wick Analysis:** Identifies buying pressure and support zones
- **Pressure Projection:** Extends lines forward based on mathematical probability
**Multi-Layer Glow Effects:**
Wick pressure lines use progressive transparency (1-8 layers) creating natural glow effects that make pressure zones immediately visible without cluttering the chart.
### Enhanced Regime Background
**Dynamic Intensity Mapping:**
Background colors reflect mathematical regime strength:
- **Deep Transparency (98% alpha):** Subtle regime indication
- **Pulse Intensity:** Based on regime strength calculation
- **Color Coding:** Green (trending), Red (mean-reverting), Neutral (random)
**Smoothing Integration:**
Regime changes incorporate 10-bar smoothing to prevent background flicker while maintaining responsiveness to genuine regime shifts.
### Color Scheme System
**Six Professional Themes:**
- **Dark (Default):** Professional trading environment optimization
- **Light:** High ambient light conditions
- **Classic:** Traditional technical analysis appearance
- **Neon:** High-contrast visibility for active trading
- **Neutral:** Minimal distraction focus
- **Bright:** Maximum visibility for complex setups
Each theme maintains mathematical accuracy while optimizing visual clarity for different trading environments and personal preferences.
---
## 📊 INSTITUTIONAL-GRADE DASHBOARD
### Tensor Field Status Section
**Field Strength Display:**
Real-time Mahalanobis distance calculation with dynamic emoji indicators:
- **⚡ (Lightning):** Extreme field strength (>1.5× threshold)
- **● (Solid Circle):** Strong field activity (>1.0× threshold)
- **○ (Open Circle):** Normal field state
**Signal Quality Rating:**
Democratic algorithm assessment:
- **ELITE:** All 3 components aligned (highest probability)
- **STRONG:** 2 components aligned (good probability)
- **GOOD:** 1 component active (moderate probability)
- **WEAK:** No clear component signals
**Threshold and Anomaly Monitoring:**
- **Threshold Display:** Current mathematical threshold setting
- **Anomaly Level (0-100%):** Combined volatility and volume spike measurement
- **>70%:** High anomaly (red warning)
- **30-70%:** Moderate anomaly (orange caution)
- **<30%:** Normal conditions (green confirmation)
### Tensor State Analysis Section
**Mathematical State Classification:**
- **↑ BULL (Tensor State +1):** Trending regime with bullish bias
- **↓ BEAR (Tensor State -1):** Mean-reverting regime with bearish bias
- **◈ SUPER (Tensor State 0):** Random walk regime (neutral)
**Visual State Gauge:**
Five-circle progression showing tensor field polarity:
- **🟢🟢🟢⚪⚪:** Strong bullish mathematical alignment
- **⚪⚪🟡⚪⚪:** Neutral/transitional state
- **⚪⚪🔴🔴🔴:** Strong bearish mathematical alignment
**Trend Direction and Phase Analysis:**
- **📈 BULL / 📉 BEAR / ➡️ NEUTRAL:** Primary trend classification
- **🌪️ CHAOS:** Extreme information flow (>2.0 flow strength)
- **⚡ ACTIVE:** Strong information flow (1.0-2.0 flow strength)
- **😴 CALM:** Low information flow (<1.0 flow strength)
### Trading Signals Section
**Real-Time Signal Status:**
- **🟢 ACTIVE / ⚪ INACTIVE:** Long signal availability
- **🔴 ACTIVE / ⚪ INACTIVE:** Short signal availability
- **Components (X/3):** Active algorithmic components
- **Mode Display:** Current signal generation mode
**Signal Strength Visualization:**
Color-coded component count:
- **Green:** 3/3 components (maximum confidence)
- **Aqua:** 2/3 components (good confidence)
- **Orange:** 1/3 components (moderate confidence)
- **Gray:** 0/3 components (no signals)
### Performance Metrics Section
**Win Rate Monitoring:**
Estimated win rates based on signal quality with emoji indicators:
- **🔥 (Fire):** ≥60% estimated win rate
- **👍 (Thumbs Up):** 45-59% estimated win rate
- **⚠️ (Warning):** <45% estimated win rate
**Mathematical Metrics:**
- **Hurst Exponent:** Real-time fractal dimension (0.000-1.000)
- **Information Flow:** Volume/price leading indicators
- **📊 VOL:** Volume leading price (accumulation/distribution)
- **💰 PRICE:** Price leading volume (momentum/speculation)
- **➖ NONE:** Balanced information flow
- **Volatility Classification:**
- **🔥 HIGH:** Above 1.5× jump threshold
- **📊 NORM:** Normal volatility range
- **😴 LOW:** Below 0.5× jump threshold
### Market Structure Section (Large Dashboard)
**Regime Classification:**
- **📈 TREND:** Hurst >0.6, momentum strategies optimal
- **🔄 REVERT:** Hurst <0.4, contrarian strategies optimal
- **🎲 RANDOM:** Hurst ≈0.5, breakout strategies preferred
**Mathematical Field Analysis:**
- **Dimensions:** Current volatility space complexity (2D-5D)
- **Hawkes λ (Lambda):** Self-exciting jump intensity (0.00-1.00)
- **Jump Status:** 🚨 JUMP (active) / ✅ NORM (normal)
### Settings Summary Section (Large Dashboard)
**Active Configuration Display:**
- **Sensitivity:** Current master sensitivity setting
- **Lookback:** Primary analysis window
- **Theme:** Active color scheme
- **Method:** Hurst calculation method (Classic R/S, Adaptive R/S, DFA)
**Dashboard Sizing Options:**
- **Small:** Essential metrics only (mobile/small screens)
- **Normal:** Balanced information density (standard desktop)
- **Large:** Maximum detail (multi-monitor setups)
**Position Options:**
- **Top Right:** Standard placement (avoids price action)
- **Top Left:** Wide chart optimization
- **Bottom Right:** Recent price focus (scalping)
- **Bottom Left:** Maximum price visibility (swing trading)
---
## 🎯 SIGNAL GENERATION LOGIC
### Multi-Component Convergence System
**Component Signal Architecture:**
The TMAE generates signals through sophisticated component analysis rather than simple threshold crossing:
**Volatility Component:**
- **Jump Detection:** Mahalanobis distance threshold breach
- **Hawkes Intensity:** Self-exciting process activation (>0.2)
- **Multi-dimensional:** Considers all volatility dimensions simultaneously
**Hurst Regime Component:**
- **Trending Markets:** Price above SMA-20 with positive momentum
- **Mean-Reverting Markets:** Price at Bollinger Band extremes
- **Random Markets:** Bollinger squeeze breakouts with directional confirmation
**Transfer Entropy Component:**
- **Volume Leadership:** Information flow from volume to price
- **Volume Spike:** Volume 110%+ above 20-period average
- **Flow Significance:** Above entropy threshold with directional bias
### Democratic Signal Weighting
**Signal Mode Implementation:**
- **Aggressive Mode:** Any single component triggers signal
- **Confluence Mode:** Minimum 2 components must agree
- **Conservative Mode:** All 3 components must align
**Momentum Confirmation:**
All signals require momentum confirmation:
- **Long Signals:** RSI >50 AND price >EMA-9
- **Short Signals:** RSI <50 AND price 0.6):**
- **Increase Sensitivity:** Catch momentum continuation
- **Lower Mean Reversion Threshold:** Avoid counter-trend signals
- **Emphasize Volume Leadership:** Institutional accumulation/distribution
- **Tensor Field Focus:** Use expansion for trend continuation
- **Signal Mode:** Aggressive or Confluence for trend following
**Range-Bound Markets (Hurst <0.4):**
- **Decrease Sensitivity:** Avoid false breakouts
- **Lower Trending Threshold:** Quick regime recognition
- **Focus on Price Leadership:** Retail sentiment extremes
- **Fractal Grid Emphasis:** Support/resistance trading
- **Signal Mode:** Conservative for high-probability reversals
**Volatile Markets (High Jump Frequency):**
- **Increase Hawkes Decay:** Recognize event clustering
- **Higher Jump Threshold:** Avoid noise signals
- **Maximum Dimensions:** Capture full volatility complexity
- **Reduce Position Sizing:** Risk management adaptation
- **Enhanced Visuals:** Maximum information for rapid decisions
**Low Volatility Markets (Low Jump Frequency):**
- **Decrease Jump Threshold:** Capture subtle movements
- **Lower Hawkes Decay:** Treat moves as independent
- **Reduce Dimensions:** Simplify analysis
- **Increase Position Sizing:** Capitalize on compressed volatility
- **Minimal Visuals:** Reduce distraction in quiet markets
---
## 🚀 ADVANCED TRADING STRATEGIES
### The Mathematical Convergence Method
**Entry Protocol:**
1. **Fractal Grid Approach:** Monitor price approaching significant fractal levels
2. **Tensor Field Confirmation:** Verify field expansion supporting direction
3. **Portal Signal:** Wait for dimensional portal appearance
4. **ELITE/STRONG Quality:** Only trade highest quality mathematical signals
5. **Component Consensus:** Confirm 2+ components agree in Confluence mode
**Example Implementation:**
- Price approaching 21-period fractal high
- Tensor field expanding upward (bullish mathematical alignment)
- Green portal appears below price (trending regime confirmation)
- ELITE quality signal with 3/3 components active
- Enter long position with stop below fractal level
**Risk Management:**
- **Stop Placement:** Below/above fractal level that generated signal
- **Position Sizing:** Based on Mahalanobis distance (higher distance = smaller size)
- **Profit Targets:** Next fractal level or tensor field resistance
### The Regime Transition Strategy
**Regime Change Detection:**
1. **Monitor Hurst Exponent:** Watch for persistent moves above/below thresholds
2. **Portal Color Change:** Regime transitions show different portal colors
3. **Background Intensity:** Increasing regime background intensity
4. **Mathematical Confirmation:** Wait for regime confirmation (hysteresis)
**Trading Implementation:**
- **Trending Transitions:** Trade momentum breakouts, follow trend
- **Mean Reversion Transitions:** Trade range boundaries, fade extremes
- **Random Transitions:** Trade breakouts with tight stops
**Advanced Techniques:**
- **Multi-Timeframe:** Confirm regime on higher timeframe
- **Early Entry:** Enter on regime transition rather than confirmation
- **Regime Strength:** Larger positions during strong regime signals
### The Information Flow Momentum Strategy
**Flow Detection Protocol:**
1. **Monitor Transfer Entropy:** Watch for significant information flow shifts
2. **Volume Leadership:** Strong edge when volume leads price
3. **Flow Acceleration:** Increasing flow strength indicates momentum
4. **Directional Confirmation:** Ensure flow aligns with intended trade direction
**Entry Signals:**
- **Volume → Price Flow:** Enter during accumulation/distribution phases
- **Price → Volume Flow:** Enter on momentum confirmation breaks
- **Flow Reversal:** Counter-trend entries when flow reverses
**Optimization:**
- **Scalping:** Use immediate flow detection (2-5 bar lag)
- **Swing Trading:** Use structural flow (10-20 bar lag)
- **Multi-Asset:** Compare flow between correlated assets
### The Tensor Field Expansion Strategy
**Field Mathematics:**
The tensor field expansion indicates mathematical pressure building in market structure:
**Expansion Phases:**
1. **Compression:** Field contracts, volatility decreases
2. **Tension Building:** Mathematical pressure accumulates
3. **Expansion:** Field expands rapidly with directional movement
4. **Resolution:** Field stabilizes at new equilibrium
**Trading Applications:**
- **Compression Trading:** Prepare for breakout during field contraction
- **Expansion Following:** Trade direction of field expansion
- **Reversion Trading:** Fade extreme field expansion
- **Multi-Dimensional:** Consider all field layers for confirmation
### The Hawkes Process Event Strategy
**Self-Exciting Jump Trading:**
Understanding that market shocks cluster and create follow-on opportunities:
**Jump Sequence Analysis:**
1. **Initial Jump:** First volatility jump detected
2. **Clustering Phase:** Hawkes intensity remains elevated
3. **Follow-On Opportunities:** Additional jumps more likely
4. **Decay Period:** Intensity gradually decreases
**Implementation:**
- **Jump Confirmation:** Wait for mathematical jump confirmation
- **Direction Assessment:** Use other components for direction
- **Clustering Trades:** Trade subsequent moves during high intensity
- **Decay Exit:** Exit positions as Hawkes intensity decays
### The Fractal Confluence System
**Multi-Timeframe Fractal Analysis:**
Combining fractal levels across different periods for high-probability zones:
**Confluence Zones:**
- **Double Confluence:** 2 fractal levels align
- **Triple Confluence:** 3+ fractal levels cluster
- **Mathematical Confirmation:** Tensor field supports the level
- **Information Flow:** Transfer entropy confirms direction
**Trading Protocol:**
1. **Identify Confluence:** Find 2+ fractal levels within 1 ATR
2. **Mathematical Support:** Verify tensor field alignment
3. **Signal Quality:** Wait for STRONG or ELITE signal
4. **Risk Definition:** Use fractal level for stop placement
5. **Profit Targeting:** Next major fractal confluence zone
---
## ⚠️ COMPREHENSIVE RISK MANAGEMENT
### Mathematical Position Sizing
**Mahalanobis Distance Integration:**
Position size should inversely correlate with mathematical field strength:
```
Position Size = Base Size × (Threshold / Mahalanobis Distance)
```
**Risk Scaling Matrix:**
- **Low Field Strength (<2.0):** Standard position sizing
- **Moderate Field Strength (2.0-3.0):** 75% position sizing
- **High Field Strength (3.0-4.0):** 50% position sizing
- **Extreme Field Strength (>4.0):** 25% position sizing or no trade
### Signal Quality Risk Adjustment
**Quality-Based Position Sizing:**
- **ELITE Signals:** 100% of planned position size
- **STRONG Signals:** 75% of planned position size
- **GOOD Signals:** 50% of planned position size
- **WEAK Signals:** No position or paper trading only
**Component Agreement Scaling:**
- **3/3 Components:** Full position size
- **2/3 Components:** 75% position size
- **1/3 Components:** 50% position size or skip trade
### Regime-Adaptive Risk Management
**Trending Market Risk:**
- **Wider Stops:** Allow for trend continuation
- **Trend Following:** Trade with regime direction
- **Higher Position Size:** Trend probability advantage
- **Momentum Stops:** Trail stops based on momentum indicators
**Mean-Reverting Market Risk:**
- **Tighter Stops:** Quick exits on trend continuation
- **Contrarian Positioning:** Trade against extremes
- **Smaller Position Size:** Higher reversal failure rate
- **Level-Based Stops:** Use fractal levels for stops
**Random Market Risk:**
- **Breakout Focus:** Trade only clear breakouts
- **Tight Initial Stops:** Quick exit if breakout fails
- **Reduced Frequency:** Skip marginal setups
- **Range-Based Targets:** Profit targets at range boundaries
### Volatility-Adaptive Risk Controls
**High Volatility Periods:**
- **Reduced Position Size:** Account for wider price swings
- **Wider Stops:** Avoid noise-based exits
- **Lower Frequency:** Skip marginal setups
- **Faster Exits:** Take profits more quickly
**Low Volatility Periods:**
- **Standard Position Size:** Normal risk parameters
- **Tighter Stops:** Take advantage of compressed ranges
- **Higher Frequency:** Trade more setups
- **Extended Targets:** Allow for compressed volatility expansion
### Multi-Timeframe Risk Alignment
**Higher Timeframe Trend:**
- **With Trend:** Standard or increased position size
- **Against Trend:** Reduced position size or skip
- **Neutral Trend:** Standard position size with tight management
**Risk Hierarchy:**
1. **Primary:** Current timeframe signal quality
2. **Secondary:** Higher timeframe trend alignment
3. **Tertiary:** Mathematical field strength
4. **Quaternary:** Market regime classification
---
## 📚 EDUCATIONAL VALUE AND MATHEMATICAL CONCEPTS
### Advanced Mathematical Concepts
**Tensor Analysis in Markets:**
The TMAE introduces traders to tensor analysis, a branch of mathematics typically reserved for physics and advanced engineering. Tensors provide a framework for understanding multi-dimensional market relationships that scalar and vector analysis cannot capture.
**Information Theory Applications:**
Transfer entropy implementation teaches traders about information flow in markets, a concept from information theory that quantifies directional causality between variables. This provides intuition about market microstructure and participant behavior.
**Fractal Geometry in Trading:**
The Hurst exponent calculation exposes traders to fractal geometry concepts, helping understand that markets exhibit self-similar patterns across multiple timeframes. This mathematical insight transforms how traders view market structure.
**Stochastic Process Theory:**
The Hawkes process implementation introduces concepts from stochastic process theory, specifically self-exciting point processes. This provides mathematical framework for understanding why market events cluster and exhibit memory effects.
### Learning Progressive Complexity
**Beginner Mathematical Concepts:**
- **Volatility Dimensions:** Understanding multi-dimensional analysis
- **Regime Classification:** Learning market personality types
- **Signal Democracy:** Algorithmic consensus building
- **Visual Mathematics:** Interpreting mathematical concepts visually
**Intermediate Mathematical Applications:**
- **Mahalanobis Distance:** Statistical distance in multi-dimensional space
- **Rescaled Range Analysis:** Fractal dimension measurement
- **Information Entropy:** Quantifying uncertainty and causality
- **Field Theory:** Understanding mathematical fields in market context
**Advanced Mathematical Integration:**
- **Tensor Field Dynamics:** Multi-dimensional market force analysis
- **Stochastic Self-Excitation:** Event clustering and memory effects
- **Categorical Composition:** Mathematical signal combination theory
- **Topological Market Analysis:** Understanding market shape and connectivity
### Practical Mathematical Intuition
**Developing Market Mathematics Intuition:**
The TMAE serves as a bridge between abstract mathematical concepts and practical trading applications. Traders develop intuitive understanding of:
- **How markets exhibit mathematical structure beneath apparent randomness**
- **Why multi-dimensional analysis reveals patterns invisible to single-variable approaches**
- **How information flows through markets in measurable, predictable ways**
- **Why mathematical models provide probabilistic edges rather than certainties**
---
## 🔬 IMPLEMENTATION AND OPTIMIZATION
### Getting Started Protocol
**Phase 1: Observation (Week 1)**
1. **Apply with defaults:** Use standard settings on your primary trading timeframe
2. **Study visual elements:** Learn to interpret tensor fields, portals, and streams
3. **Monitor dashboard:** Observe how metrics change with market conditions
4. **No trading:** Focus entirely on pattern recognition and understanding
**Phase 2: Pattern Recognition (Week 2-3)**
1. **Identify signal patterns:** Note what market conditions produce different signal qualities
2. **Regime correlation:** Observe how Hurst regimes affect signal performance
3. **Visual confirmation:** Learn to read tensor field expansion and portal signals
4. **Component analysis:** Understand which components drive signals in different markets
**Phase 3: Parameter Optimization (Week 4-5)**
1. **Asset-specific tuning:** Adjust parameters for your specific trading instrument
2. **Timeframe optimization:** Fine-tune for your preferred trading timeframe
3. **Sensitivity adjustment:** Balance signal frequency with quality
4. **Visual customization:** Optimize colors and intensity for your trading environment
**Phase 4: Live Implementation (Week 6+)**
1. **Paper trading:** Test signals with hypothetical trades
2. **Small position sizing:** Begin with minimal risk during learning phase
3. **Performance tracking:** Monitor actual vs. expected signal performance
4. **Continuous optimization:** Refine settings based on real performance data
### Performance Monitoring System
**Signal Quality Tracking:**
- **ELITE Signal Win Rate:** Track highest quality signals separately
- **Component Performance:** Monitor which components provide best signals
- **Regime Performance:** Analyze performance across different market regimes
- **Timeframe Analysis:** Compare performance across different session times
**Mathematical Metric Correlation:**
- **Field Strength vs. Performance:** Higher field strength should correlate with better performance
- **Component Agreement vs. Win Rate:** More component agreement should improve win rates
- **Regime Alignment vs. Success:** Trading with mathematical regime should outperform
### Continuous Optimization Process
**Monthly Review Protocol:**
1. **Performance Analysis:** Review win rates, profit factors, and maximum drawdown
2. **Parameter Assessment:** Evaluate if current settings remain optimal
3. **Market Adaptation:** Adjust for changes in market character or volatility
4. **Component Weighting:** Consider if certain components should receive more/less emphasis
**Quarterly Deep Analysis:**
1. **Mathematical Model Validation:** Verify that mathematical relationships remain valid
2. **Regime Distribution:** Analyze time spent in different market regimes
3. **Signal Evolution:** Track how signal characteristics change over time
4. **Correlation Analysis:** Monitor correlations between different mathematical components
---
## 🌟 UNIQUE INNOVATIONS AND CONTRIBUTIONS
### Revolutionary Mathematical Integration
**First-Ever Implementations:**
1. **Multi-Dimensional Volatility Tensor:** First indicator to implement true tensor analysis for market volatility
2. **Real-Time Hawkes Process:** First trading implementation of self-exciting point processes
3. **Transfer Entropy Trading Signals:** First practical application of information theory for trade generation
4. **Democratic Component Voting:** First algorithmic consensus system for signal generation
5. **Fractal-Projected Signal Quality:** First system to predict signal quality at future price levels
### Advanced Visualization Innovations
**Mathematical Visualization Breakthroughs:**
- **Tensor Field Radiation:** Visual representation of mathematical field energy
- **Dimensional Portal System:** Category theory visualization for regime transitions
- **Information Flow Streams:** Real-time visual display of market information transfer
- **Multi-Layer Fractal Grid:** Intelligent spacing and projection system
- **Regime Intensity Mapping:** Dynamic background showing mathematical regime strength
### Practical Trading Innovations
**Trading System Advances:**
- **Quality-Weighted Signal Generation:** Signals rated by mathematical confidence
- **Regime-Adaptive Strategy Selection:** Automatic strategy optimization based on market personality
- **Anti-Spam Signal Protection:** Mathematical prevention of signal clustering
- **Component Performance Tracking:** Real-time monitoring of algorithmic component success
- **Field-Strength Position Sizing:** Mathematical volatility integration for risk management
---
## ⚖️ RESPONSIBLE USAGE AND LIMITATIONS
### Mathematical Model Limitations
**Understanding Model Boundaries:**
While the TMAE implements sophisticated mathematical concepts, traders must understand fundamental limitations:
- **Markets Are Not Purely Mathematical:** Human psychology, news events, and fundamental factors create unpredictable elements
- **Past Performance Limitations:** Mathematical relationships that worked historically may not persist indefinitely
- **Model Risk:** Complex models can fail during unprecedented market conditions
- **Overfitting Potential:** Highly optimized parameters may not generalize to future market conditions
### Proper Implementation Guidelines
**Risk Management Requirements:**
- **Never Risk More Than 2% Per Trade:** Regardless of signal quality
- **Diversification Mandatory:** Don't rely solely on mathematical signals
- **Position Sizing Discipline:** Use mathematical field strength for sizing, not confidence
- **Stop Loss Non-Negotiable:** Every trade must have predefined risk parameters
**Realistic Expectations:**
- **Mathematical Edge, Not Certainty:** The indicator provides probabilistic advantages, not guaranteed outcomes
- **Learning Curve Required:** Complex mathematical concepts require time to master
- **Market Adaptation Necessary:** Parameters must evolve with changing market conditions
- **Continuous Education Important:** Understanding underlying mathematics improves application
### Ethical Trading Considerations
**Market Impact Awareness:**
- **Information Asymmetry:** Advanced mathematical analysis may provide advantages over other market participants
- **Position Size Responsibility:** Large positions based on mathematical signals can impact market structure
- **Sharing Knowledge:** Consider educational contributions to trading community
- **Fair Market Participation:** Use mathematical advantages responsibly within market framework
### Professional Development Path
**Skill Development Sequence:**
1. **Basic Mathematical Literacy:** Understand fundamental concepts before advanced application
2. **Risk Management Mastery:** Develop disciplined risk control before relying on complex signals
3. **Market Psychology Understanding:** Combine mathematical analysis with behavioral market insights
4. **Continuous Learning:** Stay updated on mathematical finance developments and market evolution
---
## 🔮 CONCLUSION
The Tensor Market Analysis Engine represents a quantum leap forward in technical analysis, successfully bridging the gap between advanced pure mathematics and practical trading applications. By integrating multi-dimensional volatility analysis, fractal market theory, and information flow dynamics, the TMAE reveals market structure invisible to conventional analysis while maintaining visual clarity and practical usability.
### Mathematical Innovation Legacy
This indicator establishes new paradigms in technical analysis:
- **Tensor analysis for market volatility understanding**
- **Stochastic self-excitation for event clustering prediction**
- **Information theory for causality-based trade generation**
- **Democratic algorithmic consensus for signal quality enhancement**
- **Mathematical field visualization for intuitive market understanding**
### Practical Trading Revolution
Beyond mathematical innovation, the TMAE transforms practical trading:
- **Quality-rated signals replace binary buy/sell decisions**
- **Regime-adaptive strategies automatically optimize for market personality**
- **Multi-dimensional risk management integrates mathematical volatility measures**
- **Visual mathematical concepts make complex analysis immediately interpretable**
- **Educational value creates lasting improvement in trading understanding**
### Future-Proof Design
The mathematical foundations ensure lasting relevance:
- **Universal mathematical principles transcend market evolution**
- **Multi-dimensional analysis adapts to new market structures**
- **Regime detection automatically adjusts to changing market personalities**
- **Component democracy allows for future algorithmic additions**
- **Mathematical visualization scales with increasing market complexity**
### Commitment to Excellence
The TMAE represents more than an indicator—it embodies a philosophy of bringing rigorous mathematical analysis to trading while maintaining practical utility and visual elegance. Every component, from the multi-dimensional tensor fields to the democratic signal generation, reflects a commitment to mathematical accuracy, trading practicality, and educational value.
### Trading with Mathematical Precision
In an era where markets grow increasingly complex and computational, the TMAE provides traders with mathematical tools previously available only to institutional quantitative research teams. Yet unlike academic mathematical models, the TMAE translates complex concepts into intuitive visual representations and practical trading signals.
By combining the mathematical rigor of tensor analysis, the statistical power of multi-dimensional volatility modeling, and the information-theoretic insights of transfer entropy, traders gain unprecedented insight into market structure and dynamics.
### Final Perspective
Markets, like nature, exhibit profound mathematical beauty beneath apparent chaos. The Tensor Market Analysis Engine serves as a mathematical lens that reveals this hidden order, transforming how traders perceive and interact with market structure.
Through mathematical precision, visual elegance, and practical utility, the TMAE empowers traders to see beyond the noise and trade with the confidence that comes from understanding the mathematical principles governing market behavior.
Trade with mathematical insight. Trade with the power of tensors. Trade with the TMAE.
*"In mathematics, you don't understand things. You just get used to them." - John von Neumann*
*With the TMAE, mathematical market understanding becomes not just possible, but intuitive.*
— Dskyz, Trade with insight. Trade with anticipation.
Previous Highs & Lows (Customizable)Previous Highs & Lows (Customizable)
This Pine Script indicator displays horizontal lines and labels for high, low, and midpoint levels across multiple timeframes. The indicator plots levels from the following periods:
Today's session high, low, and midpoint
Yesterday's high, low, and midpoint
Current week's high, low, and midpoint
Last week's high, low, and midpoint
Last month's high, low, and midpoint
Last quarter's high, low, and midpoint
Last year's high, low, and midpoint
Features
Individual Controls: Each timeframe has separate toggles for showing/hiding high/low levels and midpoint levels.
Custom Colors: Independent color selection for lines and labels for each timeframe group.
Display Options:
Adjustable line width (1-5 pixels)
Variable label text size (tiny, small, normal, large, huge)
Configurable label offset positioning
Organization: Settings are grouped by timeframe in a logical sequence from most recent (today) to least recent (last year).
Display Logic: Lines span the current trading day only. Labels are positioned to the right of the price action. The indicator automatically removes previous drawings to prevent chart clutter.
Swing Highs and Lows Detector🔍 Swing Highs and Lows Detector
The Swing Highs and Lows Detector is a powerful tool for traders looking to identify meaningful structural shifts in price action, based on swing point logic and internal trend shifts.
📈 What It Does
This indicator automatically identifies and labels:
HH (Higher High) – Price broke above the previous swing high
LH (Lower High) – Price failed to break the previous high, signaling potential weakness
LL (Lower Low) – Price broke below the previous swing low
HL (Higher Low) – Price maintained a higher support level, indicating strength
The script distinguishes between bullish and bearish internal shifts and tracks the highest/lowest points between those shifts to determine the swing structure.
⚙️ How It Works
You can choose between two shift detection modes:
"Open": Compares closing price to the first open of the opposite streak
"High/Low": Uses the high of bearish or low of bullish candles
Once a shift is confirmed, the indicator scans the bars between shifts to find the most significant swing high or low
When a valid swing is detected, it’s labeled directly on the chart with color-coded markers
🛎️ Built-in Alerts
Set alerts for:
Higher High
Lower High
Lower Low
Higher Low
These alerts help you catch key structural shifts in real time — great for breakout traders, structure-based analysts, and smart money concepts (SMC) strategies.
✅ How to Use
Confirm Trend Strength or Reversals – Use HH/HL to confirm an uptrend, LL/LH to confirm a downtrend
Combine with Liquidity Sweeps or Zones – Ideal for SMC or Wyckoff-style setups
Entry/Exit Triggers – Use swing breaks to time entries or exits near key structural points
IU Bigger than range strategyDESCRIPTION
IU Bigger Than Range Strategy is designed to capture breakout opportunities by identifying candles that are significantly larger than the previous range. It dynamically calculates the high and low of the last N candles and enters trades when the current candle's range exceeds the previous range. The strategy includes multiple stop-loss methods (Previous High/Low, ATR, Swing High/Low) and automatically manages take-profit and stop-loss levels based on user-defined risk-to-reward ratios. This versatile strategy is optimized for higher timeframes and assets like BTC but can be fine-tuned for different instruments and intervals.
USER INPUTS:
Look back Length: Number of candles to calculate the high-low range. Default is 22.
Risk to Reward: Sets the target reward relative to the stop-loss distance. Default is 3.
Stop Loss Method: Choose between:(Default is "Previous High/Low")
- Previous High/Low
- ATR (Average True Range)
- Swing High/Low
ATR Length: Defines the length for ATR calculation (only applicable when ATR is selected as the stop-loss method) (Default is 14).
ATR Factor: Multiplier applied to the ATR to determine stop-loss distance(Default is 2).
Swing High/Low Length: Specifies the length for identifying swing points (only applicable when Swing High/Low is selected as the stop-loss method).(Default is 2)
LONG CONDITION:
The current candle’s range (absolute difference between open and close) is greater than the previous range.
The closing price is higher than the opening price (bullish candle).
SHORT CONDITIONS:
The current candle’s range exceeds the previous range.
The closing price is lower than the opening price (bearish candle).
LONG EXIT:
Stop-loss:
- Previous Low
- ATR-based trailing stop
- Recent Swing Low
Take-profit:
- Defined by the Risk-to-Reward ratio (default 3x the stop-loss distance).
SHORT EXIT:
Stop-loss:
- Previous High
- ATR-based trailing stop
- Recent Swing High
Take-profit:
- Defined by the Risk-to-Reward ratio (default 3x the stop-loss distance).
ALERTS:
Long Entry Triggered
Short Entry Triggered
WHY IT IS UNIQUE:
This strategy dynamically adapts to different market conditions by identifying candles that exceed the previous range, ensuring that it only enters trades during strong breakout scenarios.
Multiple stop-loss methods provide flexibility for different trading styles and risk profiles.
The visual representation of stop-loss and take-profit levels with color-coded plots improves trade monitoring and decision-making.
HOW USERS CAN BENEFIT FROM IT:
Ideal for breakout traders looking to capitalize on momentum-driven price moves.
Provides flexibility to customize stop-loss methods and fine-tune risk management parameters.
Helps minimize drawdowns with a strong risk-to-reward framework while maximizing profit potential.
Swing Breakout System (SBS)The Swing Breakout Sequence (SBS) is a trading strategy that focuses on identifying high-probability entry points based on a specific pattern of price swings. This indicator will identify these patterns, then draw lines and labels to show confirmation.
How To Use:
The indicator will show both Bullish and Bearish SBS patterns.
Bullish Pattern is made up of 6 points: Low (0), HH (1), LL (2 | but higher than initial Low), New HH (3), LL (5), LL again (5)
Bearish Patten is made up of 6 points: High (0), LL (1), HH (2 | but lower than initial high), New LL (3), HH (5), HH again (5)
A label with an arrow will appear at the end, showing the completion of a successful sequence
Idea behind the strategy:
The idea behind this strategy, is the accumulation and then manipulation of liquidity throughout the sequence. For example, during SBS sequence, liquidity is accumulated during step (2), then price will push away to make a new high/low (step 3), after making a minor new high/low, price will retrace breaking the key level set up in step (2). This is price manipulating taking liquidity from behind high/low from step (2). After taking liquidity price the idea is price will continue in the original direction.
Step 0 - Setting up initial direction
Step 1 - Setting up initial direction
Step 2 - Key low/high establishing liquidity
Step 3 - Failed New high/low
Step 4 - Taking liquidity from step (2)
Step 5 - Taking liquidity from step 2 and 4
Pattern Detection:
- Uses pivot high/low points to identify swing patterns
- Stores 6 consecutive swing points in arrays
- Identifies two types of patterns:
1. Bullish Pattern: A specific sequence of higher lows and higher highs
2. Bearish Pattern: A specific sequence of lower highs and lower lows
Note: Because the indicator is identifying a perfect sequence of 6 steps, set ups may not appear frequently.
Visualization:
- Draws connecting lines between swing points
- Labels each point numerically (optional)
- Shows breakout arrows (↑ for bullish, ↓ for bearish)
- Generates alerts on valid breakouts
User Input Settings:
Core Parameters
1. Pivot Lookback Period (default: 2)
- Controls how many bars to look back/forward for pivot point detection
- Higher values create fewer but more significant pivot points
2. Minimum Pattern Height % (default: 0.1)
- Minimum required height of the pattern as a percentage of price
- Filters out insignificant patterns
3. Maximum Pattern Width (bars) (default: 50)
- Maximum allowed width of the pattern in bars
- Helps exclude patterns that form over too long a period
