PDH & PDL Indicator: Previous Day's High/Low with AlertsThe PDH & PDL Indicator plots the Previous Day's High (PDH) and Previous Day's Low (PDL) directly on the chart, providing a clear visual reference for key price levels. These levels are often used by traders to identify potential breakout or breakdown zones and to gauge market strength or weakness.
Features:
PDH (Green Line) : Represents the high of the previous trading day.
PDL (Red Line): Represents the low of the previous trading day.
Alerts:
Get notified when the price crosses above PDH or below PDL.
Custom alert messages to keep you informed in real-time.
Use Cases:
Identify key breakout and breakdown points for potential trade entries or exits.
Confirm the strength of a trend by monitoring price action relative to PDH and PDL.
Useful for intraday, swing, and positional traders who rely on historical price levels for strategy development.
Indicadores y estrategias
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.
Kalman PredictorThe **Kalman Predictor** indicator is a powerful tool designed for traders looking to enhance their market analysis by smoothing price data and projecting future price movements. This script implements a Kalman filter, a statistical method for noise reduction, to dynamically estimate price trends and velocity. Combined with ATR-based confidence bands, it provides actionable insights into potential price movement, while offering clear trend and momentum visualization.
---
#### **Key Features**:
1. **Kalman Filter Smoothing**:
- Dynamically estimates the current price state and velocity to filter out market noise.
- Projects three future price levels (`Next Bar`, `Next +2`, `Next +3`) based on velocity.
2. **Dynamic Confidence Bands**:
- Confidence bands are calculated using ATR (Average True Range) to reflect market volatility.
- Visualizes potential price deviation from projected levels.
3. **Trend Visualization**:
- Color-coded prediction dots:
- **Green**: Indicates an upward trend (positive velocity).
- **Red**: Indicates a downward trend (negative velocity).
- Dynamically updated label displaying the current trend and velocity value.
4. **User Customization**:
- Inputs to adjust the process and measurement noise for the Kalman filter (`q` and `r`).
- Configurable ATR multiplier for confidence bands.
- Toggleable trend label with adjustable positioning.
---
#### **How It Works**:
1. **Kalman Filter Core**:
- The Kalman filter continuously updates the estimated price state and velocity based on real-time price changes.
- Projections are based on the current price trend (velocity) and extend into the future (Next Bar, +2, +3).
2. **Confidence Bands**:
- Calculated using ATR to provide a dynamic range around the projected future prices.
- Indicates potential volatility and helps traders assess risk-reward scenarios.
3. **Trend Label**:
- Updates dynamically on the last bar to show:
- Current trend direction (Up/Down).
- Velocity value, providing insight into the expected magnitude of the price movement.
---
#### **How to Use**:
- **Trend Analysis**:
- Observe the direction and spacing of the prediction dots relative to current candles.
- Larger spacing indicates a potential strong move, while clustering suggests consolidation.
- **Risk Management**:
- Use the confidence bands to gauge potential price volatility and set stop-loss or take-profit levels accordingly.
- **Pullback Detection**:
- Look for flattening or clustering of dots during trends as a signal of potential pullbacks or reversals.
---
#### **Customizable Inputs**:
- **Kalman Filter Parameters**:
- `lookback`: Adjusts the smoothing window.
- `q`: Process noise (higher values make the filter more reactive to changes).
- `r`: Measurement noise (controls sensitivity to price deviations).
- **Confidence Bands**:
- `band_multiplier`: Multiplies ATR to define the range of confidence bands.
- **Visualization**:
- `show_label`: Option to toggle the trend label.
- `label_offset`: Adjusts the label’s distance from the price for better visibility.
---
#### **Examples of Use**:
- **Scalping**: Use on lower timeframes (e.g., 1-minute, 5-minute) to detect short-term price trends and reversals.
- **Swing Trading**: Identify pullbacks or continuations on higher timeframes (e.g., 4-hour, daily) by observing the prediction dots and confidence bands.
- **Risk Assessment**: Confidence bands help visualize potential price volatility, aiding in the placement of stops and targets.
---
#### **Notes for Traders**:
- The **Kalman Predictor** does not predict the future with certainty but provides a statistically informed estimate of price movement.
- Confidence bands are based on historical volatility and should be used as guidelines, not guarantees.
- Always combine this tool with other analysis techniques for optimal results.
---
This script is open-source, and the Kalman filter logic has been implemented uniquely to integrate noise reduction with dynamic confidence band visualization. If you find this indicator useful, feel free to share your feedback and experiences!
---
#### **Credits**:
This script was developed leveraging the statistical principles of Kalman filtering and is entirely original. It incorporates ATR for dynamic confidence band calculations to enhance trader usability and market adaptability.
DCA Performance AnalysisDollar-Cost Averaging (DCA) Performance Calculator
This indicator helps you analyze the performance of a DCA investment strategy by simulating regular periodic investments into an asset. Perfect for long-term investors who want to evaluate or backtest their DCA strategy.
Key Features:
- Flexible Investment Scheduling: Choose between daily, weekly, or monthly investments
- Custom Date Range: Set specific start and end dates for your analysis
- Adjustable Investment Amount: Input any dollar amount for your regular investments
- Clear Visual Markers: Green triangles show entry points, red triangle marks the end date
- Comprehensive Performance Metrics: View total investment, days invested, unrealized yield, and portfolio value
The indicator displays a clean, easy-to-read table showing:
1. Total Invested: The cumulative amount of money invested
2. Investment Days: Total number of investment entries executed
3. Unrealized Yield: Both dollar amount and percentage return (calculated at end date)
4. Portfolio Worth: Total value of holdings at the specified end date
Usage Tips:
- Best used on BTCUSD or other cryptocurrency pairs
- Works on all timeframes, but matching the timeframe to your DCA frequency provides the clearest visualization
- Calculations use opening prices for entries and closing price at end date for final valuation
- All calculations are based on UTC+0 time
This tool is ideal for:
- Backtesting DCA strategies
- Understanding historical DCA performance
- Comparing different DCA frequencies
- Planning future DCA investments
- Educational purposes about DCA investing
Note: This indicator is for informational purposes only and should not be considered financial advice. Past performance does not guarantee future results.
BTC Price Percentage Difference( Bitfinex - Coinbase)Introduction:
The BTC Price Percentage Difference Histogram Indicator is a powerful tool designed to help traders visualize and capitalize on the price discrepancies of Bitcoin (BTC) between two major exchanges: Bitfinex and Coinbase. By calculating the real-time percentage difference of BTC-USD prices and displaying it as a color-coded histogram, this indicator enables you to quickly spot potential arbitrage opportunities and gain deeper insights into market dynamics.
Features:
• Real-Time Percentage Difference Calculation:
• Computes the percentage difference between BTC-USD prices on Bitfinex and Coinbase.
• Color-Coded Histogram Visualization:
• Green Bars: Indicate that the BTC price on Bitfinex is higher than on Coinbase.
• Red Bars: Indicate that the BTC price on Bitfinex is lower than on Coinbase.
• User-Friendly and Intuitive:
• Simple setup with no additional inputs required.
• Automatically adapts to the chart’s timeframe for seamless integration.
Why Bitfinex Whales Matter:
Bitfinex is renowned for hosting some of the largest Bitcoin traders, often referred to as “whales.” These influential players have the capacity to move the market, and historically, they’ve demonstrated a high success rate in buying at market bottoms and selling at market tops. By tracking the price discrepancies between Bitfinex and other exchanges like Coinbase, you can gain valuable insights into the sentiment and actions of these key market participants.
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
Correlation Coefficient [Giang]### **Introduction to the "Correlation Coefficient" Indicator**
#### **Idea behind the Indicator**
The "Correlation Coefficient" indicator was developed to analyze the linear relationship between Bitcoin (**BTCUSD**) and other important economic indices or financial assets, such as:
- **SPX** (S&P 500 Index): Represents the U.S. stock market.
- **DXY** (Dollar Index): Reflects the strength of the USD against major currencies.
- **SPY** (ETF representing the S&P 500): A popular trading instrument.
- **GOLD** (Gold price): A traditional safe-haven asset.
The correlation between these assets can help traders understand how Bitcoin reacts to market movements of traditional financial instruments, providing opportunities for more effective trading decisions.
Additionally, the indicator allows users to **customize asset symbols for comparison**, not limited to the default indices (SPX, DXY, SPY, GOLD). This flexibility enables traders to tailor their analysis to specific goals and portfolios.
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#### **Significance and Use of Correlation in Trading**
**Correlation** is a measure of the linear relationship between two data series. In the context of this indicator:
- **The correlation coefficient ranges from -1 to 1**:
- **1**: Perfect positive relationship (both increase or decrease together).
- **0**: No linear relationship.
- **-1**: Perfect negative relationship (one increases while the other decreases).
- **Use in trading**:
- Identify **strong relationships or unusual divergences** between Bitcoin and other assets.
- Help determine **market sentiment**: For example, if Bitcoin has a negative correlation with DXY, traders might expect Bitcoin to rise when the USD weakens.
- Provide a foundation for hedging strategies or investments based on inter-asset relationships.
---
#### **Components of the Indicator**
The "Correlation Coefficient" indicator consists of the following key components:
1. **Main Data (BTCUSD)**:
- The closing price of Bitcoin is used as the central asset for calculations.
2. **Comparison Data**:
- Users can select different asset symbols for comparison. By default, the indicator supports:
- **SPX**: Stock market index.
- **DXY**: Dollar Index.
- **SPY**: Popular ETF.
- **GOLD**: Gold price.
3. **Correlation Coefficients**:
- Calculated between BTC and each comparison index, based on a Weighted Moving Average (WMA) over a user-defined period.
4. **Graphical Representation**:
- Displays individual correlation coefficients with each comparison index, making it easier for traders to track and analyze.
---
#### **How to Analyze and Use the Indicator**
**1. Identify Key Correlations:**
- Observe the correlation lines between BTC and the indices to determine positive or negative relationships.
- Example:
- If the **Correlation Coefficient (BTC-DXY)** sharply declines to -1, this indicates that when USD strengthens, Bitcoin tends to weaken.
**2. Analyze the Strength of Correlations:**
- **Strong Correlations**: If the coefficient is close to 1 or -1, the relationship between the two assets is very clear.
- **Weak Correlations**: If the coefficient is near 0, Bitcoin may be influenced by other factors outside the compared index.
**3. Develop Trading Strategies:**
- Use correlations to predict Bitcoin's price movements:
- If BTC has an inverse relationship with **DXY**, traders might consider selling BTC when the USD strengthens.
- If BTC and **SPX** are strongly correlated, traders can monitor the stock market to predict Bitcoin's trend.
**4. Evaluate Changes Over Time:**
- Use different timeframes (daily, weekly) to track the correlation's fluctuations.
- Look for unusual signals, such as a breakdown or shift from positive to negative relationships.
---
#### **Conclusion**
The "Correlation Coefficient" indicator is a powerful tool that helps traders analyze the relationship between Bitcoin and major financial indices. The ability to customize asset symbols for comparison makes the indicator flexible and suitable for various trading strategies. When used correctly, this indicator not only provides insights into market sentiment but also supports the development of intelligent trading strategies and optimized profits.
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.
WVAD (Optimized Log Scaled)The WVAD (Optimized Log Scaled) indicator is a refined version of the classic Williams' Volume Accumulation/Distribution (WVAD). This version introduces logarithmic scaling for better visualization and usability, especially when dealing with large value ranges. It also includes EMA smoothing to highlight trends and reduce noise, providing traders with a more precise and clear representation of market dynamics.
Key Features:
1.Logarithmic Scaling:
Applies a log-based transformation to the WVAD values, ensuring extreme values are compressed while maintaining the overall structure of the data.
The log scaling allows better readability and interpretation, particularly for volatile or high-volume markets.
2.EMA Smoothing:
Uses an exponential moving average (EMA) to smooth the logarithmic WVAD values.
Helps reduce noise while preserving short-term trends, making it suitable for both trend-following and reversal strategies.
3.Customizable Parameters:
N (Lookback Period): Defines the accumulation period for calculating WVAD.
EMA Smoothing Period: Controls the sensitivity of the EMA applied to the logarithmic WVAD.
Decimal Places: Adjusts the precision of the displayed values for clearer visualization.
Line Colors: Fully customizable colors for both the raw WVAD line and the smoothed EMA.
4.Directional Preservation:
Keeps the positive and negative signs of WVAD to reflect accumulation (buying pressure) or distribution (selling pressure) in the market.
5.Zero Line Reference:
A horizontal zero line is plotted to help traders easily identify bullish (above 0) or bearish (below 0) market conditions.
How to Use:
Identify Trends: The smoothed WVAD line (EMA) can help detect trends or shifts in buying/selling pressure.
Crossovers: Use crossovers of the WVAD with the zero line as potential buy or sell signals.
Divergence: Spot divergences between price and the WVAD for early indications of reversals.
Applications:
Suitable for intraday, swing, or longer-term trading strategies.
Works across various asset classes, including stocks, commodities, and cryptocurrencies.
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.
SMT Divergence ICT 01 [TradingFinder] Smart Money Technique🔵 Introduction
SMT Divergence (short for Smart Money Technique Divergence) is a trading technique in the ICT Concepts methodology that focuses on identifying divergences between two positively correlated assets in financial markets.
These divergences occur when two assets that should move in the same direction move in opposite directions. Identifying these divergences can help traders spot potential reversal points and trend changes.
Bullish and Bearish divergences are clearly visible when an asset forms a new high or low, and the correlated asset fails to do so. This technique is applicable in markets like Forex, stocks, and cryptocurrencies, and can be used as a valid signal for deciding when to enter or exit trades.
Bullish SMT Divergence : This type of divergence occurs when one asset forms a higher low while the correlated asset forms a lower low. This divergence is typically a sign of weakness in the downtrend and can act as a signal for a trend reversal to the upside.
Bearish SMT Divergence : This type of divergence occurs when one asset forms a higher high while the correlated asset forms a lower high. This divergence usually indicates weakness in the uptrend and can act as a signal for a trend reversal to the downside.
🔵 How to Use
SMT Divergence is an analytical technique that identifies divergences between two correlated assets in financial markets.
This technique is used when two assets that should move in the same direction move in opposite directions.
Identifying these divergences can help you pinpoint reversal points and trend changes in the market.
🟣 Bullish SMT Divergence
This divergence occurs when one asset forms a higher low while the correlated asset forms a lower low. This divergence indicates weakness in the downtrend and can signal a potential price reversal to the upside.
In this case, when the correlated asset is forming a lower low, and the main asset is moving lower but the correlated asset fails to continue the downward trend, there is a high probability of a trend reversal to the upside.
🟣 Bearish SMT Divergence
Bearish divergence occurs when one asset forms a higher high while the correlated asset forms a lower high. This type of divergence indicates weakness in the uptrend and can signal a potential trend reversal to the downside.
When the correlated asset fails to make a new high, this divergence may be a sign of a trend reversal to the downside.
🟣 Confirming Signals with Correlation
To improve the accuracy of the signals, use assets with strong correlation. Forex pairs like OANDA:EURUSD and OANDA:GBPUSD , or cryptocurrencies like COINBASE:BTCUSD and COINBASE:ETHUSD , or commodities such as gold ( FX:XAUUSD ) and silver ( FX:XAGUSD ) typically have significant correlation. Identifying divergences between these assets can provide a strong signal for a trend change.
🔵 Settings
Second Symbol : This setting allows you to select another asset for comparison with the primary asset. By default, "XAUUSD" (Gold) is set as the second symbol, but you can change it to any currency pair, stock, or cryptocurrency. For example, you can choose currency pairs like EUR/USD or GBP/USD to identify divergences between these two assets.
Divergence Fractal Periods : This parameter defines the number of past candles to consider when identifying divergences. The default value is 2, but you can change it to suit your preferences. This setting allows you to detect divergences more accurately by selecting a greater number of candles.
Bullish Divergence Line : Displays a line showing bullish divergence from the lows.
Bearish Divergence Line : Displays a line showing bearish divergence from the highs.
Bullish Divergence Label : Displays the "+SMT" label for bullish divergences.
Bearish Divergence Label : Displays the "-SMT" label for bearish divergences.
🔵 Conclusion
SMT Divergence is an effective tool for identifying trend changes and reversal points in financial markets based on identifying divergences between two correlated assets. This technique helps traders receive more accurate signals for market entry and exit by analyzing bullish and bearish divergences.
Identifying these divergences can provide opportunities to capitalize on trend changes in Forex, stocks, and cryptocurrency markets. Using SMT Divergence along with risk management and confirming signals with other technical analysis tools can improve the accuracy of trading decisions and reduce risks from sudden market changes.
Pine Script Boilerplate ExampleI frequently receive questions about my coding style and logic, so I decided to publish a simple indicator that draws the OHLC of a higher timeframe as an example of my coding style. This example will also explain my approach to writing indicators.
This indicator showcases how I use Types and Methods to structure my code and maintain clarity in logic. It demonstrates how I collect input data, organize the flow of the code, and utilize the TradingView method feature.
The example illustrates:
1. The use of input settings within a settings object to keep configurations grouped together.
2. The use of Types to create an object that consolidates relevant data.
3. The collection of objects to create, update, and render elements on the chart.
Enhanced Swing Trading Strategy//@version=5
strategy("Enhanced Swing Trading Strategy", overlay=true)
// Input Parameters
smaShortLength = input.int(50, title="Short SMA Length")
smaLongLength = input.int(200, title="Long SMA Length")
rsiLength = input.int(14, title="RSI Length")
rsiOverbought = input.int(70, title="RSI Overbought Level")
rsiOversold = input.int(30, title="RSI Oversold Level")
takeProfitPerc = input.float(2.0, title="Take Profit (%)")
stopLossPerc = input.float(1.0, title="Stop Loss (%)")
riskPerc = input.float(1.0, title="Risk per Trade (%)")
alertOnSignal = input.bool(true, title="Enable Alerts")
// Indicators
smaShort = ta.sma(close, smaShortLength)
smaLong = ta.sma(close, smaLongLength)
rsi = ta.rsi(close, rsiLength)
= ta.macd(close, 12, 26, 9)
// Conditions
longCondition = ta.crossover(smaShort, smaLong) and rsi > rsiOversold and macdLine > signalLine
shortCondition = ta.crossunder(smaShort, smaLong) and rsi < rsiOverbought and macdLine < signalLine
// Position Sizing based on Risk
capital = strategy.equity
riskAmount = capital * (riskPerc / 100)
stopLossValue = riskAmount / (stopLossPerc / 100)
positionSize = stopLossValue / close
// Entry Signals
if (longCondition)
strategy.entry("Long", strategy.long, qty=positionSize)
if alertOnSignal
alert("Swing Trading: Long Position Opened", alert.freq_once)
if (shortCondition)
strategy.entry("Short", strategy.short, qty=positionSize)
if alertOnSignal
alert("Swing Trading: Short Position Opened", alert.freq_once)
// Exit Conditions
strategy.exit("Take Profit/Stop Loss",
from_entry="Long",
profit=takeProfitPerc,
loss=stopLossPerc)
strategy.exit("Take Profit/Stop Loss",
from_entry="Short",
profit=takeProfitPerc,
loss=stopLossPerc)
// Plotting
plot(smaShort, color=color.blue, title="SMA 50")
plot(smaLong, color=color.red, title="SMA 200")
hline(rsiOverbought, "RSI Overbought", color=color.red)
hline(rsiOversold, "RSI Oversold", color=color.green)
plot(macdLine, color=color.green, title="MACD Line")
plot(signalLine, color=color.orange, title="Signal Line")
// Draw Entry and Exit Labels
if (strategy.position_size > 0)
label.new(bar_index, high, "Long Open", style=label.style_label_up, color=color.green)
if (strategy.position_size < 0)
label.new(bar_index, low, "Short Open", style=label.style_label_down, color=color.red)
Session Highs and Lows IndicatorThis indicator marks the high and low levels for key trading sessions, allowing traders to identify significant price zones across different markets. The default session times are defined in UTC and will automatically adjust to your local timezone:
- **London Session (07:00-09:00 UTC)**: Tracks intraday liquidity zones for potential highs/lows.
- **New York Session (12:00-14:00 UTC)**: Highlights volatility during market overlaps with Europe.
- **Asia Session (23:00-01:00 UTC)**: Confirms trend continuation and retracement opportunities.
- **New York Close Session (19:00-21:00 UTC)**: Focuses on reversals and breakout tests during global transitions.
The script dynamically updates session highs and lows with clear labels and dashed horizontal lines for better visualization. **Time ranges can be adjusted to suit your trading preferences.** This makes the indicator flexible and effective for liquidity hunting, trend trading, and breakout strategies.
1 Percent Range TrackerThis indicator is a simple yet effective tool designed to calculate and display ±1% levels relative to the current market price. These levels are dynamically updated in real time, providing clear horizontal lines on the chart to visualize the 1% range above and below the current price.
The indicator also displays the precise numerical values of these levels on the right-hand price axis, making it easy to monitor critical thresholds at a glance.
Ultra Smart TrailIntroduction
The Ultra Smart Trail indicator is a comprehensive tool for traders seeking to identify and follow market trends efficiently. Combining dynamic trend detection with adaptive price bands, this indicator simplifies the process of understanding market direction and strength. It provides clear visual cues and customizable settings, catering to both novice and experienced traders.
Detailed Description
The Ultra Smart Trail indicator works by calculating a Trend Flow Line (TFL) using a hybrid moving average technique. This TFL dynamically adjusts to market conditions, smoothing out price fluctuations while remaining responsive to significant market shifts.
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Trend Flow Line (TFL)
A color-coded line indicating bullish, bearish, or neutral trends based on price movement relative to the TFL.
The TFL uses a combination of weighted moving averages (WMA) and double-weighted moving averages (DWMA) for accuracy.
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Dynamic Price Bands
The indicator plots upper and lower bands around the TFL, based on customizable multipliers of standard deviation. These bands adapt dynamically to volatility, helping traders spot overbought or oversold conditions.
The script calculates standard deviation-based bands with customizable multipliers, enabling precise adjustment to trading styles or instruments.
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Uptrend/Downtrend Highlights
The background and price bands visually differentiate trending and ranging markets, making it easier to identify high-probability trade setups.
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Reversal Alerts
By analyzing the relationship between price and bands, the script highlights potential reversals or continuation zones with distinct levels and fills.
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This indicator is a powerful addition to any trader’s toolkit, simplifying market analysis and enhancing decision-making.
VIDYA Auto-Trading(Reversal Logic)
Purpose and Unique Features
This script leverages the Variable Index Dynamic Average (VIDYA) to implement a dynamic trend-following auto-trading strategy. By adapting to price volatility, it optimizes entry points and strengthens risk management. Key differentiators of this strategy include:
VIDYA Characteristics:
Quickly responds to price momentum changes through dynamic calculations.
Incorporates volatility adjustments for enhanced trend detection accuracy.
ATR Band Utilization:
Measures market volatility to set stop-loss levels and guide risk management.
Supports more calculated trade entries in volatile markets.
Visual Trend Representation:
Displays "green zones" for uptrends and "red zones" for downtrends.
Enables intuitive understanding of trend continuation and reversal.
Usage Instructions
Entry Conditions
Long Entry:
Enter when the price crosses above the upper band.
Close any previous short positions and initiate a new long position.
Short Entry:
Enter when the price crosses below the lower band.
Close any previous long positions and initiate a new short position.
Exit Conditions
Take Profit and Stop Loss:
Reverse Position Strategy or Position Reversal Strategy
Account Size: ¥100,0000
Commissions and Slippage: Assumed commission of 94 pips per trade and slippage of 1 pip.
Risk per Trade: 10% of account equity (adjustable based on risk tolerance).
Script Parameters
VIDYA Length: The period for calculating the trend (e.g., 14).
Momentum Period: The lookback period for calculating the Chande Momentum Oscillator (CMO).
ATR Band Distance: Adjustment coefficient for the band width (e.g., 1.5).
Price Source: Choose from close, open, high, or low prices for VIDYA calculation.
Trend Display Colors: Customize the colors for uptrend and downtrend zones.
Visualization Options: Toggle the display of trend lines, bands, and other elements on or off.
Strategy Features and Enhancements
Dynamic Momentum Adaptation:
Utilizes VIDYA's sensitivity to momentum changes for rapid trend detection.
Volatility-Aware Risk Management:
Employs ATR to dynamically adjust risk levels, ensuring resilience in volatile markets.
Enhanced Visual Indicators:
Clearly plots trend zones and entry points on the chart.
Simplifies analysis with intuitive visual cues.
Credits
This script is inspired by the innovative work of BigBeluga, whose indicators laid the foundation for this enhanced trend-following strategy. By leveraging BigBeluga’s insights, this script integrates VIDYA, ATR Bands, and other technical elements to create a more dynamic and intuitive trading tool.
We extend our gratitude to BigBeluga and the broader trading community for their invaluable contributions, which have enabled this advanced implementation.
Disclaimer:
This script is provided for educational purposes, and past performance does not guarantee future results. Always practice proper risk management in live trading scenarios.
By leveraging VIDYA, this strategy provides a precise and intuitive approach to trend-following. It is particularly effective in capturing market reversals and adapting to sudden price changes in volatile environments.
Volatility vs ATRVolatility vs ATR Indicator Description for TradingView
Volatility vs ATR is a powerful custom indicator designed to help traders analyze and compare market volatility with the Average True Range (ATR). This indicator provides valuable insights into the dynamic behavior of asset prices, enabling traders to make informed decisions about market trends, potential reversals, and risk management.
What Does It Measure?
Volatility: Represents the degree of price variation over a given period. Calculated using standard deviation or other measures, it highlights periods of heightened or reduced market activity.
Average True Range (ATR): Measures the average range of price movement over a specific period, providing a sense of the asset's price fluctuations and market activity.
How It Works
The indicator plots both Volatility and ATR on the same chart, making it easy to visualize how these metrics interact.
Rising Volatility often signals increased market uncertainty or the beginning of strong trends.
ATR Spikes typically accompany high volatility, helping identify potential breakout or breakdown scenarios.
By tracking the interplay between these metrics, traders can anticipate shifts in momentum, recognize consolidation phases, and plan trades more effectively.
Key Features
Dual-Line Display: Clearly plots both Volatility (red) and ATR (blue) for easy comparison.
Customizable Periods: Allows you to adjust the lookback period for both metrics to match your trading style.
Versatile Application: Works across all asset classes, including stocks, forex, crypto, and commodities.
Why Use Volatility vs ATR?
Trend Analysis: Identify trending vs. ranging markets by observing the relationship between Volatility and ATR.
Breakout Confirmation: Use Volatility and ATR spikes as confirmation signals for potential breakouts.
Risk Management: Plan stop-loss levels and position sizing based on ATR values.
How to Use It
Add the indicator to your chart.
Look for periods where Volatility diverges from ATR to spot potential market shifts.
Use the indicator in conjunction with price action and other technical tools for a comprehensive analysis.
This indicator is ideal for traders looking to enhance their strategies by understanding market dynamics through the lens of volatility and average price movement.
Let me know if you’d like further refinement!
lib_kernelLibrary "lib_kernel"
Library "lib_kernel"
This is a tool / library for developers, that contains several common and adapted kernel functions as well as a kernel regression function and enum to easily select and embed a list into the settings dialog.
How to Choose and Modify Kernels in Practice
Compact Support Kernels (e.g., Epanechnikov, Triangular): Use for localized smoothing and emphasizing nearby data.
Oscillatory Kernels (e.g., Wave, Cosine): Ideal for detecting periodic patterns or mean-reverting behavior.
Smooth Tapering Kernels (e.g., Gaussian, Logistic): Use for smoothing long-term trends or identifying global price behavior.
kernel_Epanechnikov(u)
Parameters:
u (float)
kernel_Epanechnikov_alt(u, sensitivity)
Parameters:
u (float)
sensitivity (float)
kernel_Triangular(u)
Parameters:
u (float)
kernel_Triangular_alt(u, sensitivity)
Parameters:
u (float)
sensitivity (float)
kernel_Rectangular(u)
Parameters:
u (float)
kernel_Uniform(u)
Parameters:
u (float)
kernel_Uniform_alt(u, sensitivity)
Parameters:
u (float)
sensitivity (float)
kernel_Logistic(u)
Parameters:
u (float)
kernel_Logistic_alt(u)
Parameters:
u (float)
kernel_Logistic_alt2(u, sigmoid_steepness)
Parameters:
u (float)
sigmoid_steepness (float)
kernel_Gaussian(u)
Parameters:
u (float)
kernel_Gaussian_alt(u, sensitivity)
Parameters:
u (float)
sensitivity (float)
kernel_Silverman(u)
Parameters:
u (float)
kernel_Quartic(u)
Parameters:
u (float)
kernel_Quartic_alt(u, sensitivity)
Parameters:
u (float)
sensitivity (float)
kernel_Biweight(u)
Parameters:
u (float)
kernel_Triweight(u)
Parameters:
u (float)
kernel_Sinc(u)
Parameters:
u (float)
kernel_Wave(u)
Parameters:
u (float)
kernel_Wave_alt(u)
Parameters:
u (float)
kernel_Cosine(u)
Parameters:
u (float)
kernel_Cosine_alt(u, sensitivity)
Parameters:
u (float)
sensitivity (float)
kernel(u, select, alt_modificator)
wrapper for all standard kernel functions, see enum Kernel comments and function descriptions for usage szenarios and parameters
Parameters:
u (float)
select (series Kernel)
alt_modificator (float)
kernel_regression(src, bandwidth, kernel, exponential_distance, alt_modificator)
wrapper for kernel regression with all standard kernel functions, see enum Kernel comments for usage szenarios. performance optimized version using fixed bandwidth and target
Parameters:
src (float) : input data series
bandwidth (simple int) : sample window of nearest neighbours for the kernel to process
kernel (simple Kernel) : type of Kernel to use for processing, see Kernel enum or respective functions for more details
exponential_distance (simple bool) : if true this puts more emphasis on local / more recent values
alt_modificator (float) : see kernel functions for parameter descriptions. Mostly used to pronounce emphasis on local values or introduce a decay/dampening to the kernel output
Total Volume for Custom PeriodIndicator Description: Total Volume for Custom Period
This indicator calculates the total trading volume for a specified time period and displays the result in the top-right corner of the chart. It is designed for traders and analysts who want to see the cumulative volume over a defined range of time without needing to calculate it manually.
Features:
Customizable Time Period:
Define the start and end times of the calculation using the easy-to-use settings panel.
The indicator dynamically updates as you adjust the dates.
Accurate Volume Calculation:
Calculates the total trading volume for all candlesticks between the selected start and end dates.
Works on all assets and timeframes supported by TradingView (stocks, crypto, forex, etc.).
Fixed Display:
The result is displayed in the top-right corner of the chart inside a clear and simple table.
The value remains visible regardless of chart movement or zoom level.
Real-time Updates:
Automatically recalculates the volume when new data is added or the selected time period changes.
Customizable Design:
Black text with a transparent background ensures the display is clear and non-intrusive.
Large text size for easy readability.
Use Cases:
Volume Analysis: Quickly assess the total trading activity over a specific time period.
Historical Data Analysis: Compare volume data across different time intervals.
Custom Strategies: Use the total volume metric as part of a broader trading strategy or analysis.
How It Works:
Open the settings panel of the indicator and input the desired Start Date and End Date.
The indicator calculates the total trading volume for all candles within the selected range.
The result is displayed in the top-right corner of the chart.
This indicator is a simple yet powerful tool for traders who rely on volume analysis to make informed decisions. It enhances your ability to study market behavior during specific periods and provides insights into trading activity with ease.
Bullish and Bearish Harami DetectorHere’s a description of the script I built for you, designed for a **TradingView public indicator**:
### **Custom Bullish and Bearish Harami Detector with Timeframe Selection**
This custom Pine Script detects **Bullish Harami** and **Bearish Harami** candlestick patterns on the selected timeframe, with configurable settings for how many prior candles to consider for pattern detection.
---
### **Features:**
1. **Timeframe Selection:**
- **Input Field for Timeframe**: The script allows users to choose the timeframe for detecting patterns. For instance, you can set it to 1 hour, 4 hours, or even daily candles, ensuring the detection works as per your chosen market view.
- This is controlled by the `input.timeframe` function, and the user is prompted to select the desired timeframe (e.g., "1h", "4h", "1d").
2. **Enable/Disable Pattern Detection:**
- The user has the flexibility to enable or disable the detection of **Bullish Harami** and **Bearish Harami** patterns.
- The two toggles `detectBullishHarami` and `detectBearishHarami` allow users to turn on/off the detection for each pattern type.
3. **Customizable Bearish Candle Count for Bullish Harami:**
- The user can define how many prior **bearish candles** should be present before a **Bullish Harami** can be detected.
- The input variable `bearishCandleCountBullish` lets you choose how many previous bearish candles to consider for detecting a **Bullish Harami** (for example, the last 3, 5, or 6 bearish candles).
4. **Customizable Bullish Candle Count for Bearish Harami:**
- Similar to the Bullish Harami, the script allows the user to define how many prior **bullish candles** should be present before a **Bearish Harami** pattern is detected.
- The input variable `bearishCandleCountBearish` lets you select how many previous bullish candles to check for **Bearish Harami**.
5. **Pattern Detection Logic:**
- **Bullish Harami**: Detected when a bearish candle (open > close) is followed by a smaller bullish candle (open < close) where the entire body of the second candle is contained within the body of the first candle.
- **Bearish Harami**: Detected when a bullish candle (open < close) is followed by a smaller bearish candle (open > close) where the entire body of the second candle is contained within the body of the first candle.
- Both patterns are subject to the user-defined conditions (number of previous bearish or bullish candles).
6. **Visual Indicators:**
- **Bullish Harami**: A green label is plotted **below the bar** to indicate a **Bullish Harami** pattern.
- **Bearish Harami**: A red label is plotted **above the bar** to indicate a **Bearish Harami** pattern.
- The labels are displayed using the `plotshape` function with custom colors and text.
7. **Additional Settings**:
- The script includes tooltips and descriptions for each input to make the settings clear for users, allowing even those unfamiliar with candlestick patterns to understand and use the indicator effectively.
---
### **How It Works:**
- The script first checks the specified timeframe and identifies the current and previous candlesticks.
- It then applies the user-defined conditions for detecting the **Bullish Harami** and **Bearish Harami** patterns by checking the relative positions and sizes of the candlesticks over the selected number of previous candles.
- Once a pattern is detected, it plots a label on the chart (green for **Bullish Harami** and red for **Bearish Harami**) at the appropriate location (below or above the candle).
- The script updates dynamically as the price action unfolds.
---
### **Use Cases:**
- **Traders**: This script is useful for traders who want to identify reversal patterns like **Bullish Harami** and **Bearish Harami** on their chosen timeframes and adjust the sensitivity by changing the number of prior candles for pattern detection.
- **Customization**: Users can fine-tune the script’s settings based on their specific trading strategy, adjusting both the timeframe and the number of candles for pattern detection.
---
### **Conclusion:**
This indicator is an effective tool for detecting candlestick patterns, specifically **Bullish Harami** and **Bearish Harami**, on **TradingView**. By allowing customization in terms of timeframe and the number of prior candles to consider, users can tailor the script to fit their trading strategy and market conditions.
Breakaway Fair Value Gaps [LuxAlgo]The Breakaway Fair Value Gap (FVG) is a typical FVG located at a point where the price is breaking new Highs or Lows.
🔶 USAGE
In the screenshot above, the price range is visualized by Donchian Channels.
In theory, the Breakaway FVGs should generally be a good indication of market participation, showing favor in the FVG's breaking direction. This is a combination of buyers or sellers pushing markets quickly while already at the highest high or lowest low in recent history.
While this described reasoning seems conventional, looking into it inversely seems to reveal a more effective use of these formations.
When the price is pushed to the extremities of the current range, the price is already potentially off balance and over-extended. Then an FVG is created, extending the price further out of balance.
With this in consideration, After identifying a Breakaway FVG, we could logically look for a reversion to re-balance the gap.
However, it would be illogical to believe that the FVG will immediately mitigate after formation. Because of this, the dashboard display for this indicator shows the analysis for the mitigation likelihood and timeliness.
In the example above, the information in the dashboard would read as follows (Bearish example):
Out of 949 Bearish Breakaway FVGs, 80.19% are shown to be mitigated within 60 bars, with the average mitigation time being 13 bars.
The other 19.81% are not mitigated within 60 bars. This could mean the FVG was mitigated after 60 bars, or it was never mitigated.
The unmitigated FVGs within the analysis window will extend their mitigation level to the current bar. We can see the number of bars since the formation is represented to the right of the live mitigation level.
Utilizing the current distance readout helps to better judge the likelihood of a level being mitigated.
Additionally, when considering these mitigation levels as targets, an additional indicator or analysis can be used to identify specific entries, which would further aid in a system's reliability.
🔶 SETTINGS
Trend Length: Sets the (DC) Trend length to use for Identifying Breakaway FVGs.
Show Mitigation Levels: Optionally hide mitigation levels if you would prefer only to see the Breakaway FVGs.
Maximum Duration: Sets the analysis duration for FVGs, Past this length in bars, the FVG is counted as "Un-Mitigated".
Show Dashboard: Optionally hide the dashboard.
Use Median Duration: Display the Median of the Bar Length data set rather than the Average.
Triangular Moving AverageTriangular Moving Average (TMA)
The Triangular Moving Average (TMA) indicator is a versatile tool designed for traders seeking a smoother trend-following experience. By applying a double-smoothing technique, the TMA reduces market noise and highlights significant price trends, making it an ideal choice for identifying direction and potential reversals.
Key Features:
Customizable Period: Adjust the period length to suit your trading strategy.
Selectable Price Type: Choose from Close, Open, High, Low, Median, Typical, or Weighted prices.
Multi-Timeframe Capability: Analyze trends across different timeframes for confluence.
This indicator also dynamically changes color to reflect trend direction, helping traders visualize momentum shifts more effectively:
Green: Bullish trend (upward movement).
Red: Bearish trend (downward movement).
Gray: Neutral or flat movement.
Disclaimer
This indicator is a technical analysis tool and should not be considered financial advice. Trading involves substantial risk, and past performance is not indicative of future results. Always do your own research and consult with a licensed financial advisor before making trading decisions. The author is not responsible for any losses incurred through the use of this indicator.
