[blackcat] L1 Banker Move█ OVERVIEW
The Pine Script is an indicator designed to analyze market signals for institutional and short-term investors. It calculates and plots three main signals: Institutional Signal, Institutional Build, and Short-Term Investor Signal. The script uses a combination of price, volume, and moving average data to generate these signals, which can help traders identify potential buying or selling opportunities.
█ LOGICAL FRAMEWORK
The script is structured into several main sections:
1 — Input Parameters
The script does not explicitly define any input parameters, relying on default values for calculations.
2 — Custom Functions
• reference_value(values, length) : Retrieves the first non-NA value from a specified number of past values.
• calculate_institutional_and_short_term_signals(low, close, open, volume) : Calculates the institutional and short-term investor signals based on price, volume, and moving average data.
3 — Calculations
• Price and Volume Metrics: The script calculates various smoothed price changes, lowest and highest values over different periods, and volume-weighted prices.
• Moving Averages: It computes simple moving averages (SMA) and exponential moving averages (EMA) for different periods.
• RSI Calculation: The script calculates a custom RSI for different periods.
• Signal Generation: It generates the institutional and short-term investor signals based on the calculated metrics.
4 — Plotting
The script plots the three main signals on the chart using the plot function.
The flow of data and logic is as follows:
• The reference_value function is used to find reference values for calculations.
• The calculate_institutional_and_short_term_signals function performs the core calculations and returns the institutional and short-term investor signals.
• The main script calls this function and plots the results.
█ CUSTOM FUNCTIONS
1 — reference_value(values, length)
• Purpose : Retrieves the first non-NA value from a specified number of past values.
• Parameters :
• values: An array of values.
• length: The number of past values to consider.
• Return Value : The first non-NA value found or na if no valid value is found.
• Functionality : Iterates through the specified number of past values and returns the first non-NA value.
2 — calculate_institutional_and_short_term_signals(low, close, open, volume)
• Purpose : Calculates the institutional and short-term investor signals based on price, volume, and moving average data.
• Parameters :
• low: Low price series.
• close: Close price series.
• open: Open price series.
• volume: Volume series.
• Return Values :
• institutional_signal: The institutional signal.
• institutional_build: The institutional build signal.
• short_term_investor_signal: The short-term investor signal.
• Functionality :
• Computes various price and volume metrics.
• Calculates moving averages and volume-weighted prices.
• Generates the institutional and short-term investor signals based on these metrics.
█ KEY POINTS AND TECHNIQUES
1 — Advanced Pine Script Features
• Custom Functions: The script defines and uses custom functions to encapsulate complex logic.
• Conditional Statements: Extensive use of iff and if statements to control the flow of calculations.
• Looping Constructs: The for loop in reference_value function to iterate through past values.
• Exponential Moving Averages (EMA): Used to smooth out price and signal changes.
• Volume-Weighted Price (VWP): Calculated to factor in volume in price analysis.
• Custom RSI Calculation: A custom RSI formula is used, which differs from the standard RSI calculation.
2 — Optimization Techniques
• Efficient Data Handling: The reference_value function efficiently finds the first non-NA value without unnecessary computations.
• Smoothed Signals: Using EMAs to smooth out noisy signals for better trend identification.
3 — Unique Approaches
• Combination of Metrics: The script combines multiple metrics (price, volume, moving averages, and custom RSI) to generate comprehensive signals.
• Institutional Build Signal: A unique approach to detect institutional activity by comparing current price levels with historical lows and smoothed price changes.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
1 — Potential Modifications
• Input Parameters: Add input parameters to allow users to customize the lengths and thresholds used in the calculations.
• Strategy Version: Convert the indicator into a strategy by adding buy/sell signals based on the generated signals.
• Additional Indicators: Integrate other technical indicators (e.g., MACD, Bollinger Bands) to enhance the signal generation process.
2 — Similar Trading Scenarios
• Institutional Activity Analysis: Use similar techniques to analyze institutional activity in other markets or assets.
• Volume Analysis: Apply the volume-weighted price and volume analysis to identify significant price movements.
• Multi-Timeframe Analysis: Extend the script to analyze signals across multiple timeframes for a more robust trading strategy.
3 — Related Pine Script Concepts
• Pine Script Functions: Understanding how to define and use custom functions effectively.
• Conditional Logic: Mastering the use of iff and if statements for complex logic.
• Looping Constructs: Familiarity with for loops for iterating through data.
• Moving Averages: Knowledge of different types of moving averages and their applications.
• Volume Analysis: Techniques for incorporating volume data into price analysis.
Volatilidad
Shannon Entropy Volatility AnalyzerThis algorithm aims to measure market uncertainty or volatility using a Shannon entropy-based approach. 🔄📊
Entropy is a measure of disorder or unpredictability, and here we use it to evaluate the structure of price returns within a defined range of periods (window length). 🧩⏳ Thus, the goal is to detect changes to identify conditions of high or low volatility. 🔍⚡
What we seek with Shannon's formula in this algorithm is to measure market uncertainty or volatility through dynamic entropy. This measure helps us understand how unpredictable price behavior is over a given period, which is key to making informed decisions. 📈🧠
Through this formula, we calculate the level of disorder or dispersion in price returns based on their probability of occurrence, enabling us to identify moments of high or low volatility. 💡💥
Shannon Entropy Calculation 📏
• Uses probabilities to measure uncertainty in returns. 🎲
• Entropy is normalized on a scale of 0 to 100, where:
o High Entropy: Unpredictable movements (high uncertainty). ⚠️💥
•
o Low Entropy: Structured movements (low uncertainty). 📉🔒
•
• With probabilities, we measure the level of dispersion or unpredictability of returns using Shannon's entropy formula. 📊🔍
________________________________________
Indicator Usefulness 🛠️
• Identify High Volatility: When the market is unpredictable, the indicator signals "High Uncertainty." ⚡🔮
• Detect Market Stability: When the market is more predictable and structured, the indicator highlights "Low Uncertainty." 🔒🧘♂️
• Neutral Zones: Helps monitor markets without extreme conditions, enabling safer entry or exit opportunities. ⚖️🚶♂️
________________________________________
Uncertainty Zones 🌀
1. High Uncertainty: When entropy exceeds the upper threshold. 🚨🔺
2. Low Uncertainty: When entropy is below the lower threshold. 🔻💡
3. Neutral: When entropy lies between both thresholds. ⚖️🔄
________________________________________
What We Aim to Achieve with the Formula in Practice 🎯
1. Detection of Volatile Moments: Shannon’s formula helps us identify when the market is unpredictable. This is a good moment to take additional precautions, such as reducing position size or avoiding trading during high volatility phases. ⚠️📉
2. Trading Opportunities in Stable Markets: With low entropy, we can identify when the market is more predictable, favoring trend or momentum strategies with a higher chance of success. 🚀📈
3. Optimization of Risk Management: By measuring market volatility in real-time, we can adjust entry and exit strategies, tailoring risk based on the level of uncertainty detected. 🔄⚖️
________________________________________
We hope this makes it easy to interpret and use. If you have any questions or comments, please feel free to reach out to us! 📬😊
Custom EMA (v4) [MacroGlide]Custom EMA (v4) is an easy-to-use tool designed for traders who want a clear and reliable way to analyze market trends. By using multiple Exponential Moving Averages (EMAs), this indicator helps you visualize the market's direction and momentum in a straightforward way. Whether you're tracking short-term movements or looking for long-term patterns, Custom EMA makes it simple to spot trends and trading opportunities.
Key Features:
• Multi-EMA System: Plots up to four EMAs on the chart with customizable lengths and colors, providing flexibility to analyze trends over different timeframes.
• Dynamic Trend Cloud: A visually intuitive cloud is generated between the fastest and slowest EMA. The cloud changes color based on market trends:
• Green Cloud: Indicates a bullish trend when shorter EMAs are above longer EMAs.
• Red Cloud: Indicates a bearish trend when shorter EMAs are below longer EMAs.
• Highlighting Zones: Background shading helps distinguish bullish and bearish conditions, further clarifying the prevailing trend in the market.
How to Use:
• Add the Indicator: Load the indicator onto your chart and customize the EMA lengths to suit your trading style.
• Interpret the Cloud: Observe the color of the trend cloud to identify bullish (green) or bearish (red) market conditions.
• Combine with Highlighting Zones: Use the background shading in conjunction with the cloud to confirm trend strength and direction.
• Customize to Fit Your Strategy: Adjust the lengths and colors of the EMAs to align with your preferred analysis timeframe.
Methodology:
This indicator leverages a layered EMA approach, using up to four EMAs to calculate the trend cloud and define market conditions. By comparing the relative positions of the EMAs, it identifies bullish and bearish trends and visually represents them with a color-coded cloud. The inclusion of highlighting zones enhances the trader's ability to quickly grasp market sentiment.
Originality and Usefulness:
Custom EMA (v4) sets itself apart by integrating a trend cloud that adapts dynamically to EMA positions, providing traders with a clean and intuitive way to visualize market trends. The combination of multi-EMA plotting, background shading, and trend cloud offers comprehensive insight into both short-term and long-term market movements.
Charts:
The indicator plots four customizable EMAs alongside a trend cloud that visually captures market direction. Whether you're monitoring short-term price action or identifying long-term trends, the Custom EMA (v4) provides clarity and simplicity for traders at all levels.
Enjoy the game!
Standard Deviation of Returns: DivergencePurpose:
The "Standard Deviation of Returns: Divergence" indicator is designed to help traders identify potential trend reversals or continuation signals by analyzing divergences between price action and the statistical volatility of returns. Divergences can signal weakening momentum in the prevailing trend, offering insight into potential buying or selling opportunities.
Key Components
1. Returns Calculation:
* The indicator uses logarithmic returns (log(close / close )) to measure relative price changes in a normalized manner.
* Log returns are more effective than simple price differences when analyzing data across varying price levels, as they account for percentage-based changes.
2. Standard Deviation of Returns:
* The script computes the standard deviation of returns over a user-defined lookback period (ta.stdev(returns, lookback)).
* Standard deviation measures the dispersion of returns around their average, effectively quantifying market volatility.
* A higher standard deviation indicates increased volatility, while lower standard deviation reflects a calmer market.
3. Price Action:
* Detects higher highs (new peaks in price) and lower lows (new troughs in price) over the lookback period.
* Price trends are compared to the behavior of the standard deviation.
4. Divergence Detection:
A divergence occurs when price action (higher highs or lower lows) is not confirmed by a corresponding movement in standard deviation:
Bullish Divergence: Price makes a lower low, but the standard deviation does not, signaling potential upward momentum.
Bearish Divergence: Price makes a higher high, but the standard deviation does not, signaling potential downward momentum.
5. Visual Cues:
The script highlights divergence regions directly on the chart:
Green Background: Indicates a bullish divergence (potential buy signal).
Red Background: Indicates a bearish divergence (potential sell signal).
How It Works
Inputs:
* The user specifies the lookback period (lookback) for calculating the standard deviation and detecting divergences.
Calculation:
* Each bar’s returns are computed and used to calculate the standard deviation over the specified lookback period.
* The indicator evaluates price highs/lows and compares these with the highest and lowest values of the standard deviation within the same lookback period.
Highlight of Divergences:
When divergences are detected:
Bullish Divergence: The background of the chart is shaded green.
Bearish Divergence: The background of the chart is shaded red.
Trading Application
Bullish Divergence:
* Occurs when the market is oversold, or downward momentum is weakening.
* Suggests a potential reversal to an uptrend, signaling a buying opportunity.
Bearish Divergence:
* Occurs when the market is overbought, or upward momentum is weakening.
* Suggests a potential reversal to a downtrend, signaling a selling opportunity.
Contextual Use:
* Use this indicator in conjunction with other technical tools like RSI, MACD, or moving averages to confirm signals.
* Effective in volatile or ranging markets to help anticipate shifts in momentum.
Summary
The "Standard Deviation of Returns: Divergence" indicator is a robust tool for spotting divergences that can signal weakening market trends. It combines statistical volatility with price action analysis to highlight key areas of potential reversals. By integrating this tool into your trading strategy, you can gain additional confirmation for entries or exits while keeping a close watch on momentum shifts.
Disclaimer: This is not a financial advise; please consult your financial advisor for personalized advice.
Relative PerformanceSimple relative performance of a token compared to BTC, with display of normalized performance velocity line.
Rolling VWAP with Optional Kalman FilterThis script provides an advanced and customizable Rolling VWAP (Volume-Weighted Average Price) indicator, designed for traders who want to refine their trend analysis and improve decision-making. With a unique option to apply a Kalman Filter, you can smooth out VWAP values to reduce noise in volatile markets, making it easier to identify actionable trends.
Key Features:
Dynamic Rolling VWAP:
Choose the rolling window size (number of bars) to match your trading style, whether you’re an intraday scalper or a swing trader.
Kalman Filter Toggle:
Enable the Kalman filter to smooth VWAP values and eliminate market noise.
Adjustable Kalman Gain to control the level of smoothing, making it suitable for both fast and slow markets.
Price Source Flexibility:
Use the Typical Price ((H+L+C)/3) or the Close Price as the basis for VWAP calculation.
Visual Enhancements:
Background shading highlights whether the price is above (bullish) or below (bearish) the VWAP, helping traders make quick visual assessments.
A legend dynamically updates the current VWAP value.
Dual View Option:
Compare the raw Rolling VWAP and the Kalman-filtered VWAP when the filter is enabled, giving you deeper insight into market trends.
Use Cases:
Intraday Traders: Identify key price levels for re-entry or exits using a short rolling window and responsive filtering.
Swing Traders: Analyze broader trends with a longer rolling window and smoother VWAP output.
Volatile Markets: Use the Kalman filter to reduce noise and avoid false signals during high market volatility.
How to Use:
Adjust the Rolling Window to set the number of bars for VWAP calculation.
Toggle Kalman Filter on/off depending on your preference for raw or smoothed VWAP values.
Fine-tune the Kalman Gain for the desired level of smoothing.
Use the shading to quickly assess whether the price is trading above or below the VWAP for potential entry/exit signals.
DCA Strategy with Mean Reversion and Bollinger BandDCA Strategy with Mean Reversion and Bollinger Band
The Dollar-Cost Averaging (DCA) Strategy with Mean Reversion and Bollinger Bands is a sophisticated trading strategy that combines the principles of DCA, mean reversion, and technical analysis using Bollinger Bands. This strategy aims to capitalize on market corrections by systematically entering positions during periods of price pullbacks and reversion to the mean.
Key Concepts and Principles
1. Dollar-Cost Averaging (DCA)
DCA is an investment strategy that involves regularly purchasing a fixed dollar amount of an asset, regardless of its price. The idea behind DCA is that by spreading out investments over time, the impact of market volatility is reduced, and investors can avoid making large investments at inopportune times. The strategy reduces the risk of buying all at once during a market high and can smooth out the cost of purchasing assets over time.
In the context of this strategy, the Investment Amount (USD) is set by the user and represents the amount of capital to be invested in each buy order. The strategy executes buy orders whenever the price crosses below the lower Bollinger Band, which suggests a potential market correction or pullback. This is an effective way to average the entry price and avoid the emotional pitfalls of trying to time the market perfectly.
2. Mean Reversion
Mean reversion is a concept that suggests prices will tend to return to their historical average or mean over time. In this strategy, mean reversion is implemented using the Bollinger Bands, which are based on a moving average and standard deviation. The lower band is considered a potential buy signal when the price crosses below it, indicating that the asset has become oversold or underpriced relative to its historical average. This triggers the DCA buy order.
Mean reversion strategies are popular because they exploit the natural tendency of prices to revert to their mean after experiencing extreme deviations, such as during market corrections or panic selling.
3. Bollinger Bands
Bollinger Bands are a technical analysis tool that consists of three lines:
Middle Band: The moving average, usually a 200-period Exponential Moving Average (EMA) in this strategy. This serves as the "mean" or baseline.
Upper Band: The middle band plus a certain number of standard deviations (multiplier). The upper band is used to identify overbought conditions.
Lower Band: The middle band minus a certain number of standard deviations (multiplier). The lower band is used to identify oversold conditions.
In this strategy, the Bollinger Bands are used to identify potential entry points for DCA trades. When the price crosses below the lower band, this is seen as a potential opportunity for mean reversion, suggesting that the asset may be oversold and could reverse back toward the middle band (the EMA). Conversely, when the price crosses above the upper band, it indicates overbought conditions and signals potential market exhaustion.
4. Time-Based Entry and Exit
The strategy has specific entry and exit points defined by time parameters:
Open Date: The date when the strategy begins opening positions.
Close Date: The date when all positions are closed.
This time-bound approach ensures that the strategy is active only during a specified window, which can be useful for testing specific market conditions or focusing on a particular time frame.
5. Position Sizing
Position sizing is determined by the Investment Amount (USD), which is the fixed amount to be invested in each buy order. The quantity of the asset to be purchased is calculated by dividing the investment amount by the current price of the asset (investment_amount / close). This ensures that the amount invested remains constant despite fluctuations in the asset's price.
6. Closing All Positions
The strategy includes an exit rule that closes all positions once the specified close date is reached. This allows for controlled exits and limits the exposure to market fluctuations beyond the strategy's timeframe.
7. Background Color Based on Price Relative to Bollinger Bands
The script uses the background color of the chart to provide visual feedback about the price's relationship with the Bollinger Bands:
Red background indicates the price is above the upper band, signaling overbought conditions.
Green background indicates the price is below the lower band, signaling oversold conditions.
This provides an easy-to-interpret visual cue for traders to assess the current market environment.
Postscript: Configuring Initial Capital for Backtesting
To ensure the backtest results align with the actual investment scenario, users must adjust the Initial Capital in the TradingView strategy properties. This is done by calculating the Initial Capital as the product of the Total Closed Trades and the Investment Amount (USD). For instance:
If the user is investing 100 USD per trade and has 10 closed trades, the Initial Capital should be set to 1,000 USD.
Similarly, if the user is investing 200 USD per trade and has 24 closed trades, the Initial Capital should be set to 4,800 USD.
This adjustment ensures that the backtesting results reflect the actual capital deployed in the strategy and provides an accurate representation of potential gains and losses.
Conclusion
The DCA strategy with Mean Reversion and Bollinger Bands is a systematic approach to investing that leverages the power of regular investments and technical analysis to reduce market timing risks. By combining DCA with the insights offered by Bollinger Bands and mean reversion, this strategy offers a structured way to navigate volatile markets while targeting favorable entry points. The clear entry and exit rules, coupled with time-based constraints, make it a robust and disciplined approach to long-term investing.
ATR SL Band (No-Repaint, Multi-Timeframe) + Risk per ContractThis indicator draws a non-repainting band for ATR-based Stoploss placement.
If used on Futures, it shows the distance + risk from the previous candle close, as well as from the current price.
The risk value is automatically calculated for the following symbols:
(Micro) ES (S&P 500)
(Micro) NQ (NASDAQ 100)
(Micro) YM (Dow Jones Industrial Average / US30)
The timeframe can be set individually. It is not recommended to use a lower timeframe than the chart timeframe as values differ from the actual timeframe's ATR SL in this case.
Visual ATR StopThis indicator uses the Average True Range (ATR) to display a visual range for stop placement. Two multiplier values (example, 1 and 3) can be set to create a filled area below the price. This area represents the range between the two ATR levels, adjusted by subtracting the current price, providing a simple way to visualize stop-loss placement based on volatility.
The indicator is customizable; for example, negative values can place the area above the price for short positions. The filled color can also be removed, which allows precise levels to be marked above and below.
Precision Trading Strategy: Golden EdgeThe PTS: Golden Edge strategy is designed for scalping Gold (XAU/USD) on lower timeframes, such as the 1-minute chart. It captures high-probability trade setups by aligning with strong trends and momentum, while filtering out low-quality trades during consolidation or low-volatility periods.
The strategy uses a combination of technical indicators to identify optimal entry points:
1. Exponential Moving Averages (EMAs): A fast EMA (3-period) and a slow EMA (33-period) are used to detect short-term trend reversals via crossover signals.
2. Hull Moving Average (HMA): A 66-period HMA acts as a higher-timeframe trend filter to ensure trades align with the overall market direction.
3. Relative Strength Index (RSI): A 12-period RSI identifies momentum. The strategy requires RSI > 55 for long trades and RSI < 45 for short trades, ensuring entries are backed by strong buying or selling pressure.
4. Average True Range (ATR): A 14-period ATR ensures trades occur only during volatile conditions, avoiding choppy or low-movement markets.
By combining these tools, the PTS: Golden Edge strategy creates a precise framework for scalping and offers a systematic approach to capitalize on Gold’s price movements efficiently.
[blackcat] L1 Abnormal Volume Monitor█ OVERVIEW
The script is an indicator designed to monitor abnormal volume patterns in the market. It calculates and plots moving average volumes, identifies triple volume bars, and detects potential large order entries based on specific conditions.
█ FEATURES
• Input Parameters: The script defines parameters M1, M2, and lbk which control the calculation of moving averages and the lookback period for detecting abnormal volume.
• Calculations: The script calculates two moving averages of volume (MAVOL1 and MAVOL2), a smoothed price level (mm), and identifies conditions for triple volume bars and large order entries.
• Plotting: The script plots volume histograms for up and down bars, moving average volumes, and highlights triple volume bars with and without large order entries.
• Conditional Statements: The script uses conditional statements to determine when to plot certain data points and labels based on the calculated conditions.
█ LOGICAL FRAMEWORK
• xfl(cond, lbk): This function checks if a condition (cond) has been true within a specified lookback period (lbk). It returns true if the condition has been met and false otherwise.
• Parameters: cond (condition to check), lbk (lookback period).
• Return Value: outb (boolean indicating if the condition was met within the lookback period).
• abnormal_vol_monitor(close, open, high, low, volume, M1, M2, lbk): This function calculates moving average volumes, identifies triple volume bars, and detects large order entries.
• Parameters: close, open, high, low, volume (price and volume data), M1, M2 (periods for moving averages), lbk (lookback period).
• Return Value: A tuple containing MAVOL1, MAVOL2, xa (large order entry condition), and tripleVolume (triple volume condition).
█ KEY POINTS AND TECHNIQUES
• Moving Averages: The script uses simple moving averages (sma) and exponential moving averages (ema) to smooth volume data.
• Volume Analysis: The script identifies triple volume bars and large order entries based on specific conditions, such as volume doubling and price increases.
• Lookback Period: The xfl function uses a lookback period to ensure the accuracy of the detected conditions.
• Plotting Techniques: The script uses different plot styles and colors to distinguish between up bars, down bars, moving averages, and abnormal volume patterns.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
• Modifications: The script could be modified to include additional conditions for detecting other types of abnormal volume patterns or to adjust the sensitivity of the detection.
• Extensions: Similar techniques could be applied to other financial instruments or timeframes to identify unusual trading activity.
• Related Concepts: The script utilizes concepts such as moving averages, exponential moving averages, and conditional plotting, which are fundamental in Pine Script and technical analysis.
Volume-Weighted Delta Strategy[Kopottaja]Volume-Weighted Delta Strategy
The Volume-Weighted Delta Strategy combines price movement and trading volume to identify potential bullish and bearish market conditions. The strategy calculates a delta value that measures the difference between the close and open prices, weighted by volume over a specified period. This delta is compared against its moving average (SMA) to determine potential trend changes. Key features include:
Volume-Weighted Delta Calculation:
The delta is calculated by summing up the volume-weighted differences between close and open prices over the defined length (Delta Length).
Trend Identification:
If the delta value crosses above its SMA, the strategy interprets this as a bullish condition.
If the delta value crosses below its SMA, the strategy interprets this as a bearish condition.
EMA Integration:
A 20-period EMA is included as an additional trend indicator. The EMA line changes color based on whether the delta value is above or below its SMA:
Green: Bullish (delta > SMA)
Red: Bearish (delta < SMA)
Volume Filter:
A volume threshold can be applied to ensure trades are only executed when significant volume is present, helping to avoid false signals in low-volume conditions.
Entry Conditions:
Buy: When the delta crosses below its SMA (bearish signal).
Sell: When the delta crosses above its SMA (bullish signal).
Customizable Inputs:
Length for delta calculation (Delta Length)
Length for moving average (MA Length)
Volume threshold for trade activation
Optimal Timeframes:
This strategy works best on the 4-hour and 1-day timeframes, where volume and price trends are more stable, reducing noise from smaller timeframes.
How It Works:
This strategy is ideal for traders leveraging the relationship between price movement, volume, and trend indicators. Focusing on volume-weighted price action aims to provide a clearer picture of market sentiment, improving the accuracy of entry and exit signals.
Average Price Range Screener [KFB Quant]Average Price Range Screener
Overview:
The Average Price Range Screener is a technical analysis tool designed to provide insights into the average price volatility across multiple symbols over user-defined time periods. The indicator compares price ranges from different assets and displays them in a visual table and chart for easy reference. This can be especially helpful for traders looking to identify symbols with high or low volatility across various time frames.
Key Features:
Multiple Symbols Supported:
The script allows for analysis of up to 10 symbols, such as major cryptocurrencies and market indices. Symbols can be selected by the user and configured for tracking price volatility.
Dynamic Range Calculation:
The script calculates the average price range of each symbol over three distinct time periods (default are 30, 60, and 90 bars). The price range for each symbol is calculated as a percentage of the bar's high-to-low difference relative to its low value.
Range Visualization:
The results are visually represented using:
- A color-coded table showing the calculated average ranges of each symbol and the current chart symbol.
- A line plot that visually tracks the volatility for each symbol on the chart, with color gradients representing the range intensity from low (red/orange) to high (blue/green).
Customizable Inputs:
- Length Inputs: Users can define the time lengths (default are 30, 60, and 90 bars) for calculating average price ranges for each symbol.
- Symbol Inputs: 10 symbols can be tracked at once, with default values set to popular crypto pairs and indices.
- Color Inputs: Users can customize the color scheme for the range values displayed in the table and chart.
Real-Time Ranking:
The indicator ranks symbols by their average price range, providing a clear view of which assets are exhibiting higher volatility at any given time.
Each symbol's range value is color-coded based on its relative volatility within the selected symbols (using a gradient from low to high range).
Data Table:
The table shows the average range values for each symbol in real-time, allowing users to compare volatility across multiple assets at a glance. The table is dynamically updated as new data comes in.
Interactive Labels:
The indicator adds labels to the chart, showing the average range for each symbol. These labels adjust in real-time as the price range values change, giving users an immediate view of volatility rankings.
How to Use:
Set Time Periods: Adjust the time periods (lengths) to match your trading strategy's timeframe and volatility preference.
Symbol Selection: Add and track the price range for your preferred symbols (cryptocurrencies, stocks, indices).
Monitor Volatility: Use the visual table and plot to identify symbols with higher or lower volatility, and adjust your trading strategy accordingly.
Interpret the Table and Chart: Ranges that are color-coded from red/orange (lower volatility) to blue/green (higher volatility) allow you to quickly gauge which symbols are most volatile.
Disclaimer: This tool is provided for informational and educational purposes only and should not be considered as financial advice. Always conduct your own research and consult with a licensed financial advisor before making any investment decisions.
Volume Spike DetectorVolume Spike Detector
This script is designed to identify significant spikes in trading volume and visually represent them on the chart. It calculates the 20-period simple moving average (SMA) of the trading volume and multiplies it by a user-defined threshold to determine the spike threshold. When the current volume exceeds this threshold, the script detects and highlights a volume spike.
Key Features:
Dynamic Spike Threshold:
The script calculates the spike threshold dynamically based on the average trading volume. Users can customize the threshold multiplier using an input setting.
Example: A threshold multiplier of 2.0 means the current volume must be twice the 20-period SMA to trigger a detection.
Visual Representation:
The current volume is plotted in blue bars.
The spike threshold is plotted as a red line, making it easy to visually identify when the volume crosses the threshold.
Alert Notification:
When a volume spike is detected, an alert is triggered to notify the user.
This feature is useful for real-time monitoring and spotting potential trading opportunities.
Use Case:
Traders can use this tool to identify sudden increases in trading activity, which may indicate a significant market move or event. It’s suitable for all markets, including cryptocurrencies, stocks, and forex.
Linear Regression Intensity [AlgoAlpha]Introducing the Linear Regression Intensity indicator by AlgoAlpha, a sophisticated tool designed to measure and visualize the strength of market trends using linear regression analysis. This indicator not only identifies bullish and bearish trends with precision but also quantifies their intensity, providing traders with deeper insights into market dynamics. Whether you’re a novice trader seeking clearer trend signals or an experienced analyst looking for nuanced trend strength indicators, Linear Regression Intensity offers the clarity and detail you need to make informed trading decisions.
Key Features:
📊 Comprehensive Trend Analysis: Utilizes linear regression over customizable periods to assess and quantify trend strength.
🎨 Customizable Appearance: Choose your preferred colors for bullish and bearish trends to align with your trading style.
🔧 Flexible Parameters: Adjust the lookback period, range tolerance, and regression length to tailor the indicator to your specific strategy.
📉 Dynamic Bar Coloring: Instantly visualize trend states with color-coded bars—green for bullish, red for bearish, and gray for neutral.
🏷️ Intensity Labels: Displays dynamic labels that represent the intensity of the current trend, helping you gauge market momentum at a glance.
🔔 Alert Conditions: Set up alerts for strong bullish or bearish trends and trend neutrality to stay ahead of market movements without constant monitoring.
Quick Guide to Using Linear Regression Intensity:
🛠 Add the Indicator: Simply add Linear Regression Intensity to your TradingView chart from your favorites. Customize the settings such as lookback period, range tolerance, and regression length to fit your trading approach.
📈 Market Analysis: Observe the color-coded bars to quickly identify the current trend state. Use the intensity labels to understand the strength behind each trend, allowing for more strategic entry and exit points.
🔔 Set Up Alerts: Enable alerts for when strong bullish or bearish trends are detected or when the trend reaches a neutral zone. This ensures you never miss critical market movements, even when you’re away from the chart.
How It Works:
The Linear Regression Intensity indicator leverages linear regression to calculate the underlying trend of a selected price source over a specified length. By analyzing the consistency of the regression values within a defined lookback period, it determines the trend’s intensity based on a percentage tolerance. The indicator aggregates pairwise comparisons of regression values to assess whether the trend is predominantly upward or downward, assigning a state of bullish, bearish, or neutral accordingly. This state is then visually represented through dynamic bar colors and intensity labels, offering a clear and immediate understanding of market conditions. Additionally, the inclusion of Average True Range (ATR) ensures that the intensity visualization accounts for market volatility, providing a more robust and reliable trend assessment. With customizable settings and alert conditions, Linear Regression Intensity empowers traders to fine-tune their strategies and respond swiftly to evolving market trends.
Elevate your trading strategy with Linear Regression Intensity and gain unparalleled insights into market trends! 🌟📊
WhalenatorThis custom TradingView indicator combines multiple analytic techniques to help identify potential market trends, areas of support and resistance, and zones of heightened trading activity. It incorporates a SuperTrend-like line based on ATR, Keltner Channels for volatility-based price envelopes, and dynamic order blocks derived from significant volume and pivot points. Additionally, it highlights “whale” activities—periods of exceptionally large volume—along with an estimated volume profile level and approximate bid/ask volume distribution. Together, these features aim to offer traders a more comprehensive view of price structure, volatility, and institutional participation.
This custom TradingView indicator integrates multiple trading concepts into a single, visually descriptive tool. Its primary goal is to help traders identify directional bias, volatility levels, significant volume events, and potential support/resistance zones on a price chart. Below are the main components and their functionalities:
SuperTrend-Like Line (Trend Bias):
At the core of the indicator is a trend-following line inspired by the SuperTrend concept, which uses Average True Range (ATR) to adaptively set trailing stop levels. By comparing price to these levels, the line attempts to indicate when the market is in an uptrend (price above the line) or a downtrend (price below the line). The shifting levels can provide a dynamic sense of direction and help traders stay with the predominant trend until it shifts.
Keltner Channels (Volatility and Range):
Keltner Channels, based on an exponential moving average and Average True Range, form volatility-based envelopes around price. They help traders visualize whether price is extended (touching or moving outside the upper/lower band) or trading within a stable range. This can be useful in identifying low-volatility consolidations and high-volatility breakouts.
Dynamic Order Blocks (Approximations of Supply/Demand Zones):
By detecting pivot highs and lows under conditions of significant volume, the indicator approximates "order blocks." Order blocks are areas where institutional buying or selling may have occurred, potentially acting as future support or resistance zones. Although these approximations are not perfect, they offer a visual cue to areas on the chart where price might react strongly if revisited.
Volume Profile Proxy and Whale Detection:
The indicator highlights price levels associated with recent maximum volume activity, providing a rough "volume profile" reference. Such levels often become key points of price interaction.
"Whale" detection logic attempts to identify bars where exceptionally large volume occurs (beyond a defined threshold). By tracking these "whale bars," traders can infer where heavy participation—often from large traders or institutions—may influence market direction or create zones of interest.
Approximate Bid/Ask Volume and Dollar Volume Tracking:
The script estimates whether volume within each bar leans more towards the bid or the ask side, aiming to understand which participant (buyers or sellers) might have been more aggressive. Additionally, it calculates dollar volume (close price multiplied by volume) and provides an average to gauge the relative participation strength over time.
Labeling and Visual Aids:
Dynamic labels display Whale Frequency (the ratio of bars with exceptionally large volume), average dollar volume, and approximate ask/bid volume metrics. This gives traders at-a-glance insights into current market conditions, participation, and sentiment.
Strengths:
Multifaceted Analysis:
By combining trend, volatility, volume, and order block logic in one place, the indicator saves chart space and simplifies the analytical process. Traders gain a holistic view without flipping between multiple separate tools.
Adaptable to Market Conditions:
The use of ATR and Keltner Channels adapts to changing volatility conditions. The SuperTrend-like line helps keep traders aligned with the prevailing trend, avoiding constant whipsaws in choppy markets.
Volume-Based Insights:
Integrating whale detection and a crude volume profile proxy helps traders understand where large players might be interacting. This perspective can highlight critical levels that might not be evident from price action alone.
Convenient Visual Cues and Labels:
The indicator provides quick reference points and textual information about the underlying volume dynamics, making decision-making potentially faster and more informed.
Weaknesses:
Heuristic and Approximate Nature:
Many of the indicator’s features, like the "order blocks," "whale detection," and the approximate bid/ask volume, rely on heuristics and assumptions that may not always be accurate. Without actual Level II data or true volume profiles, the insights are best considered as supplementary, not definitive signals.
Lagging Components:
Indicators that rely on past data, like ATR-based trends or moving averages for Keltner Channels, inherently lag behind price. This can cause delayed signals, particularly in fast-moving markets, potentially missing some early opportunities or late in confirming market reversals.
No Guaranteed Predictive Power:
As with any technical tool, it does not forecast the future with certainty. Strong volume at a certain level or a bullish SuperTrend reading does not guarantee price will continue in that direction. Market conditions can change unexpectedly, and false signals will occur.
Complexity and Overreliance Risk:
With multiple signals combined, there’s a risk of information overload. Traders might feel compelled to rely too heavily on this one tool. Without complementary analysis (fundamentals, news, or additional technical confirmation), overreliance on the indicator could lead to misguided trades.
Conclusion:
This integrated indicator offers a comprehensive visual guide to market structure, volatility, and activity. Its strength lies in providing a multi-dimensional viewpoint in a single tool. However, traders should remain aware of its approximations, inherent lags, and the potential for conflicting signals. Sound risk management, position sizing, and the use of complementary analysis methods remain essential for trading success.
Risks Associated with Trading:
No indicator can guarantee profitable trades or accurately predict future price movements. Market conditions are inherently unpredictable, and reliance on any single tool or combination of tools carries the risk of financial loss. Traders should practice sound risk management, including the use of stop losses and position sizing, and should not trade with funds they cannot afford to lose. Ultimately, decisions should be guided by a thorough trading plan and possibly supplemented with other forms of market analysis or professional advice.
Risks and Important Considerations:
• Not a Standalone Tool:
• This indicator should not be used in isolation. It is essential to incorporate additional technical analysis tools, fundamental analysis, and market context when making trading decisions.
• Relying solely on this indicator may lead to incomplete assessments of market conditions.
• Market Volatility and False Signals:
• Financial markets can be highly volatile, and indicators based on historical data may not accurately predict future movements.
• The indicator may produce false signals due to sudden market changes, low liquidity, or atypical trading activity.
• Risk Management:
• Always employ robust risk management strategies, including setting stop-loss orders, diversifying your portfolio, and not over-leveraging positions.
• Understand that no indicator guarantees success, and losses are a natural part of trading.
• Emotional Discipline:
• Avoid making impulsive decisions based on indicator signals alone.
• Emotional trading can lead to significant financial losses; maintain discipline and adhere to a well-thought-out trading plan.
• Continuous Learning and Adaptation:
• Stay informed about market news, economic indicators, and global events that may impact trading conditions.
• Continuously evaluate and adjust your trading strategies as market dynamics evolve.
• Consultation with Professionals:
• Consider seeking advice from financial advisors or professional traders to understand better how this indicator can fit into your overall trading strategy.
• Professional guidance can provide personalized insights based on your financial goals and risk tolerance.
Disclaimer:
Trading financial instruments involves substantial risk and may not be suitable for all investors. Past performance is not indicative of future results. This indicator is provided for informational and educational purposes only and should not be considered investment advice. Always conduct your own research and consult with a licensed financial professional before making any trading decisions.
Note: The effectiveness of any technical indicator can vary based on market conditions and individual trading styles. It's crucial to test indicators thoroughly using historical data and possibly paper trading before applying them in live trading scenarios.
Volume Rate of Change (VROC)Volume Rate of Change (VROC) is an indicator that calculates the percentage change in trading volume over a specific period, helping analyze market momentum and activity. It is calculated as:
VROC = ((Current Volume - Past Volume) ÷ Past Volume) × 100
This indicator shows changes in market interest. Positive values indicate increasing volume, while negative values signal a decrease. High VROC values often suggest potential trend reversals or breakouts.
Applications:
Breakout Validation: VROC > 200% confirms strong breakouts; below this may signal false moves.
Market Stagnation: VROC < 0% suggests shrinking volume and range-bound markets.
Trend End Alert: A drop below 0% during trends may indicate weakening momentum.
Adjusting for Timeframes: Tailor VROC to timeframes.
Examples:
Daily: VROC(5) compares with last week's same day; VROC(20) with 1 month ago.
Monthly: VROC(12) compares with the same month last year; VROC(1) with last month.
Intraday: VROC(24) (hourly) and VROC(288) (5 minutes) for the same time yesterday.
Adaptive ATR Trailing Stops█ Introduction
This script is based on the average true range (ATR) and has been improved with the HHV or LLV. The script supports the trader to have his stoploss trailed. In this case, the stoploss is dynamic and can be adjusted with each candleclose.
█ What Does This Indicator Do?
The ATR SL Trailing Indicator helps you dynamically adjust your stop-loss levels based on market movements. It uses market volatility to calculate trailing stop-loss levels, ensuring you can secure profits or minimize losses. The indicator creates two lines:
A green/red line for long positions (when you’re betting on prices going up).
A green/red line for short positions (when you’re betting on prices going down).
█ Key Concepts: How Does the Indicator Work?
The Average True Range (ATR) measures market volatility, showing how much the price moves over a specific period.
A high ATR indicates a volatile market (large price swings), while a low ATR indicates a quiet market (smaller price changes).
Why is ATR important? ATR helps dynamically adjust the distance between your stop-loss and the current price. In volatile markets, the stop-loss is placed further away to avoid being triggered by short-term fluctuations. In quieter markets, the stop-loss is set closer to the price.
The HHV is the highest price over a specific period. For long positions, the indicator uses the highest price minus an ATR-based value to determine the stop-loss level.
Why is HHV important? HHV ensures the stop-loss for long positions only moves up when the price reaches new highs. Once the price starts falling, the stop-loss remains unchanged to lock in profits or minimize losses.
The LLV is the lowest price over a specific period. For short positions, the indicator uses the lowest price plus an ATR-based value to determine the stop-loss level.
Why is LLV important? LLV ensures the stop-loss for short positions only moves down when the price reaches new lows. Once the price starts rising, the stop-loss remains unchanged to lock in profits or minimize losses.
█ How Does the Indicator Work?
For Long Positions:
The indicator sets the stop-loss below the current price, based on:
Market volatility (ATR).
The highest price over a specific period (HHV).
The line turns green when the current price is above the stop-loss.
The line turns red when the price drops below the stop-loss, signaling you may need to exit the trade.
For Short Positions:
The indicator sets the stop-loss above the current price, based on:
*Market volatility (ATR).
*The lowest price over a specific period (LLV).
*The line turns green when the current price is below the stop-loss.
*The line turns red when the price moves above the stop-loss, signaling you may need to exit the trade.
█ Advantages of the ATR SL Trailing Indicator
*Dynamic and adaptive: Automatically adjusts stop-loss levels based on market volatility.
*Visual clarity: Green and red lines clearly indicate whether your position is safe or at risk.
*Effective risk management: Helps you lock in profits and minimize losses without the need for constant manual adjustments.
█ When Should You Use This Indicator?
*If you practice trend-based trading and want your stop-losses to automatically adapt to market movements.
*In volatile markets, to avoid being stopped out by short-term fluctuations.
*When you want to implement efficient risk management without manually adjusting your positions.
█ Inputs
The user can set the indicator for both longs and shorts. This is particularly important because the calculation is different. The HHV is used for longs and the LLV for shorts. The user can therefore set the period/length for the ATR on the one hand and the HHV/LLV on the other. He also has a multiplier, which can also be customized. The multiplier multiplies the price change of each individual candle.
█ Color Change
If the SL is trailed and the price breaks a line, the color changes. In this case, it would have executed the SL on an open trade.
Combined VolumeThis indicator displays the combined volume for all the exchanges listed in the settings menu.
For example, with the default settings, on BTCUSD the indicator will display the current market's volume AND the volume of all other major exchanges listed on TradingView.
The gray indicator value is the current exchange's volume, the colored volume is the combined volume of all other exchanges, allowing you to compare the current exchange's volume to the broad market to give you a better idea of local exchange activity versus broad market activity.
If you want to add more exchange tickers, turn "debug" mode on and a small label will appear in the top right telling you which market type & exchange ticker you're currently on. All exchange tickers must be separated by a comma.
The "Other Exchanges" input setting overrides all other lists allowing you to specify your own exchange list for assets not provided by the default settings (the indicator supports crypto, forex and stocks by default).
EMA Volatility Channel [QuantAlgo]EMA Volatility Channel 🌊📈
The EMA Volatility Channel by QuantAlgo is an advanced technical indicator designed to capture price volatility and trend dynamics through adaptive channels based on exponential moving averages. This sophisticated system combines EMA-based trend analysis with dynamic volatility-adjusted bands to help traders and investors identify trend direction, potential reversals, and market volatility conditions. By evaluating both price momentum and volatility together, this tool enables users to make informed trading decisions while adapting to changing market conditions.
💫 Dynamic Channel Architecture
The EMA Volatility Channel provides a unique framework for assessing market trends through a blend of exponential moving averages and volatility-based channel calculations. Unlike traditional channel indicators that use fixed-width bands, this system incorporates dynamic volatility measurements to adjust channel width automatically, helping users determine whether price movements are significant relative to current market conditions. By combining smooth EMA trends with adaptive volatility bands, it evaluates both directional movement and market volatility, while the smoothing parameters ensure stable yet responsive channel adjustments. This adaptive approach allows users to identify trending conditions while remaining aware of volatility expansions and contractions, enhancing both trend-following and reversal strategies.
📊 Indicator Components & Mechanics
The EMA Volatility Channel is composed of several technical components that create a dynamic channel system:
EMA Midline: Calculates a smoothed exponential moving average that serves as the channel's centerline, providing a clear reference for trend direction.
Volatility Measurement: Computes average price movement to determine dynamic channel width, adapting to changing market conditions automatically.
Smooth Band Calculation: Applies additional smoothing to the channel bands, reducing noise while maintaining responsiveness to significant price movements.
📈 Key Indicators and Features
The EMA Volatility Channel combines various technical tools to deliver a comprehensive analysis of market conditions.
The indicator utilizes exponential moving averages with customizable length and smoothing parameters to adapt to different trading styles. Volatility calculations are applied to determine channel width, providing context-aware boundaries for price movement. The trend detection component evaluates price action relative to the channel bands, helping validate trends and identify potential reversals.
The indicator incorporates multi-layered visualization with color-coded channels and bars to signal both trend direction and market position. These adaptive visual cues, combined with programmable alerts for channel breakouts, help traders and investors track both trend changes and volatility conditions, supporting both trend-following and mean-reversion strategies.
⚡️ Practical Applications and Examples
✅ Add the Indicator: Add the indicator to your TradingView chart by clicking on the star icon to add it to your favorites ⭐️
👀 Monitor Channel Position: Watch the price position relative to the channel bands to identify trend direction and potential reversals. When price moves outside the channel, consider potential trend changes or extreme conditions.
🔔 Set Alerts: Configure alerts for channel breakouts and trend changes, ensuring you can act on significant technical developments promptly.
🌟 Summary and Tips
The EMA Volatility Channel by QuantAlgo is a versatile technical tool, designed to support both trend following and volatility analysis across different market environments. By combining smooth EMA trends with dynamic volatility-based channels, it helps traders and investors identify significant price movements while measuring market volatility, providing reliable technical signals. The tool's adaptability across timeframes makes it suitable for both trend-following and reversal strategies, allowing users to capture opportunities while maintaining awareness of changing market conditions.
Adaptive Supertrend with Dynamic Optimization [EdgeTerminal]The Enhanced Adaptive Supertrend represents a significant evolution of the traditional Supertrend indicator, incorporating advanced mathematical optimization, dynamic volatility adjustment, intelligent signal filtering, reduced noise and false positives.
Key Features
Dynamic volatility-adjusted bands
Self-optimizing multiplier
Intelligent signal filtering system
Cooldown period to prevent signal clustering
Clear buy/sell signals with optimal positioning
Smooth trend visualization
RSI and MACD integration for confirmation
Performance-based optimization
Dynamic Band Calculation
Dynamic Band Calculation automatically adapts to market volatility, generates wider bands in volatile periods, reducing false signals. It also generates tighter bands in stable periods, capturing smaller moves and smooth transitions between different volatility regimes.
RSI Integration
The RSI and MACD play multiple crucial roles in the Adaptive Supertrend.
It first helps with momentum factor calculation. This dynamically adjusts band width based on momentum conditions. When the RSI is oversold, bands widen by 20% to prevent false signals during strong downtrends and provide more room for price movements in extreme conditions.
When the RSI is overbought, brands tighten by 20% and they become more sensitive to potential reversals to help catch trend changes earlier.
This reduces false signals in strong trends, helps detect potential reversals earlier than the usual, create adaptive band width based on market conditions and finally, better protection against whipsaws.
MACD Integration
The MACD in this supertrend indicator serves as a trend confirmation tool. The idea is to use MACD crossovers to confirm trend changes to reduce false trend change signals and enhance the signal quality.
For this to become a signal, MACD crossovers must align with price movement to help filter out weak or false signals, which acts as an additional layer of trend confirmation.
Additionally, MACD line position relative to signal line indicates trend strength, helps maintain positions in strong trends and assists in early detection of trend weakening.
Momentum Integration
Momentum Integration prevents false signals in extreme conditions, It adjusts dynamic bands based on market momentum, improves trend confirmation in strong moves and reduces whipsaws during consolidations.
Improved signals
There are a few systems to generate better signals, allowing for generally faster signals compared to original supertrend, such as:
Enforced cooldown period between signals
Prevents signal clustering
Clearer entry/exit points
Reduced false signals during choppy markets
Performance Optimization
This script implements a Sharpe ratio-inspired optimization algorithm to balance returns against risk, penalize large drawdowns, adapt parameters in real-time and improve risk-adjusted performance
Parameter Settings
ATR Period: 10 (default) - adjust based on timeframe
Initial Multiplier: 3.0 (default) - will self-optimize
Optimization Period: 50 (default) - longer periods for more stability
Smoothing Period: 3 (default) - adjust for signal smoothness
Best Practices
Use on multiple timeframes for confirmation
Allow the optimization process to run for at least 50 bars
Monitor the adaptive multiplier for trend strength indication
Consider RSI and MACD alignment for stronger signals
Did it move?That is the eternal question in trading.: Is the price moving? This indicators aims to answer that question. It is based on concepts from 2 Bars from "The Strat". This indicator measures the distance the current price is above the previous high or below the previous low and on two timeframes. The assumption is that the price is moving as long as the price is above or below the previous bar.
The distance the price moved is normalized by the standard deviation. This serves the trader in two ways: 1) you can quickly determine if a price movement is significant (score > 1), and 2) you can plan exits when the score falls below 1 (e.g., movement become insignificant). Movement upwards are colored green and down movements are red. When the price is also above the higher timeframe high (below the HTF low), the color are more intense. When the price is not moving, the background is highlighted.
Finally, there are two alert setting. One is for then the price stops moving (movement score falls below a threshold. The other is a exit/reversal warning. For example if there is a strong move in the opposite it will trigger that alert.
Chande Volatility-Based Trailing Stops This indicator is developed from a description outlined in the Chande - Kroll book, "The New Technical Trader". It is designed to help control risk by plotting two lines that function as long and short trailing stops.
How does it work?
"These stops are derived from recent highest high or lowest low. They adjust based on volatility. However, to avoid giving up a sizable chunk of profit before the stop is hit, it is modified in such a way that the stop can only advance with price, not retreat. This will lock in a greater portion of potential profits..."
Settings:
The default settings are those described in the book. They are described as being best for intermediate term trades. Use the multiplier to tighten or loosen the stop. A smaller multiplier will result in tighter stops. It is recommended to adjust this value for your preferred timeframe. You can toggle the trailing stop lines on or off as well as cross over marker.
