majikal78
Custom Volume Ratio Indicator
The Custom Volume Ratio Indicator is a unique tool designed for traders to analyze price movements in relation to trading volume. This indicator calculates the ratio of the price range (the difference between the highest and lowest prices of a candle) to the volume of that candle. By visualizing this ratio, traders can gain insights into market dynamics and potential price movements.
Key Features:
1. Price Range Calculation: The indicator computes the price range for each candle by subtracting the lowest price from the highest price. This gives traders an understanding of how much price fluctuated during that specific time frame.
2. Volume Measurement: It utilizes the trading volume of each candle, which reflects the number of shares or contracts traded during that period. Volume is a critical factor in confirming trends and reversals in the market.
3. Ratio Visualization: The primary output of the indicator is the ratio of price range to volume. A higher ratio may indicate increased volatility relative to volume, suggesting potential trading opportunities. Conversely, a lower ratio could imply a more stable market environment.
4. Color-Coded Bars: The bars representing the ratio are color-coded based on the candle's closing price relative to its opening price. Green bars indicate bullish candles (where the close is higher than the open), while red bars indicate bearish candles (where the close is lower than the open). This visual cue helps traders quickly assess market sentiment.
5. Background Highlighting: The indicator also features a subtle background color to enhance visibility, making it easier for traders to focus on key areas of interest on the chart.
Use Cases:
• Trend Confirmation: Traders can use the volume ratio to confirm existing trends. A rising ratio alongside increasing volume may suggest a strong bullish trend, while a declining ratio could indicate weakening momentum.
• Volatility Assessment: By analyzing the price range relative to volume, traders can identify periods of high volatility. This information can be crucial for setting stop-loss orders or determining entry points.
• Market Sentiment Analysis: The color-coded bars provide immediate insight into market sentiment, allowing traders to make informed decisions based on recent price action.
Overall, the Custom Volume Ratio Indicator serves as a valuable addition to any trader's toolkit, providing essential insights into market behavior and helping to inform trading strategies.
التقلب
CandelaCharts - OHLC Volatility Range Map 📝 Overview
Unlock the power of volatility analysis with the OHLC Volatility Range Map!
Volatility reveals the intensity and speed of price movements, often accompanied by manipulative wicks extending in the opposite direction of a candle’s close.
These sharp moves, common in volatile markets, are designed to mislead traders into taking positions against the prevailing trend. Such manipulation signals potential volatility spikes and offers key insights into market dynamics.
By analyzing these patterns, traders can anticipate the candle's distribution phase, where the price expands to new highs or lows during heightened volatility.
This phase provides crucial clues for spotting liquidity draws, retracement opportunities, and potential reversals, making the OHLC Volatility Range Map an indispensable tool for navigating fast-moving markets.
📦 Features
This tool offers a range of powerful features to enhance your trading analysis:
Real-time Data Feed : Stay updated with live candlestick stats, with each new candle updating OHLC data and performing ongoing historical calculations, even on sub-minute timeframes.
User-Friendly Interface : Designed for advanced traders, the intuitive interface allows easy navigation and customization of display settings, offering a personalized experience for data-driven analysis.
⚙️ Settings
Method: Sets the desired calculation algorithm.
Visualization: Controls the display modes.
Current volatility: Display the current-day volatility.
Use NY Midnight Open: Sets the day start
⚡️ Showcase
Here’s a visual showcase of the tool in action, highlighting its key features and capabilities:
Histogram
Barchart
📒 Usage
Here’s how you can use the OHLC Volatility Range Map to enhance your analysis:
Add OHLC Volatility Range Map to your Tradingview chart.
Watch at high-volatility zones that align with your analysis.
Combine this data with other models and insights to strengthen your trading strategy.
Example 1
By following these steps, you'll unlock powerful insights to refine and elevate your trading strategies.
🔹 Notes
Available calculation methods:
Mean
Median
🚨 Alerts
The indicator does not provide any alerts!
⚠️ Disclaimer
These tools are exclusively available on the TradingView platform.
Our charting tools are intended solely for informational and educational purposes and should not be regarded as financial, investment, or trading advice. They are not designed to predict market movements or offer specific recommendations. Users should be aware that past performance is not indicative of future results and should not rely on these tools for financial decisions. By using these charting tools, the purchaser agrees that the seller and creator hold no responsibility for any decisions made based on information provided by the tools. The purchaser assumes full responsibility and liability for any actions taken and their consequences, including potential financial losses or investment outcomes that may result from the use of these products.
By purchasing, the customer acknowledges and accepts that neither the seller nor the creator is liable for any undesired outcomes stemming from the development, sale, or use of these products. Additionally, the purchaser agrees to indemnify the seller from any liability. If invited through the Friends and Family Program, the purchaser understands that any provided discount code applies only to the initial purchase of Candela's subscription. The purchaser is responsible for canceling or requesting cancellation of their subscription if they choose not to continue at the full retail price. In the event the purchaser no longer wishes to use the products, they must unsubscribe from the membership service, if applicable.
We do not offer reimbursements, refunds, or chargebacks. Once these Terms are accepted at the time of purchase, no reimbursements, refunds, or chargebacks will be issued under any circumstances.
By continuing to use these charting tools, the user confirms their understanding and acceptance of these Terms as outlined in this disclaimer.
Systematic Risk Aggregation ModelThe “Systematic Risk Aggregation Model” is a quantitative trading strategy implemented in Pine Script™ designed to assess and visualize market risk by aggregating multiple financial risk factors. This model uses a multi-dimensional scoring approach to quantify systemic risk, incorporating volatility, drawdowns, put/call ratios, tail risk, volume spikes, and the Sharpe ratio. It derives a composite risk score, which is dynamically smoothed and plotted alongside adaptive Bollinger Bands to identify trading opportunities. The strategy’s theoretical framework aligns with modern portfolio theory and risk management literature (Markowitz, 1952; Taleb, 2007).
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Key Components of the Model
1. Volatility as a Risk Proxy
The model calculates the standard deviation of the closing price over a specified period (volatility_length) to quantify market uncertainty. Volatility is normalized to a score between 0 and 100, using its historical minimum and maximum values.
Reference: Volatility has long been regarded as a critical measure of financial risk and uncertainty in capital markets (Hull, 2008).
2. Drawdown Assessment
The drawdown metric captures the relative distance of the current price from the highest price over the specified period (drawdown_length). This is converted into a normalized score to reflect the magnitude of recent losses.
Reference: Drawdown is a key metric in risk management, often used to measure potential downside risk in portfolios (Maginn et al., 2007).
3. Put/Call Ratio as a Sentiment Indicator
The strategy integrates the put/call ratio, sourced from an external symbol, to assess market sentiment. High values often indicate bearish sentiment, while low values suggest bullish sentiment (Whaley, 2000). The score is normalized similarly to other metrics.
4. Tail Risk via Modified Z-Score
Tail risk is approximated using the modified Z-score, which measures the deviation of the closing price from its moving average relative to its standard deviation. This approach captures extreme price movements and potential “black swan” events.
Reference: Taleb (2007) discusses the importance of considering tail risks in financial systems.
5. Volume Spikes as a Proxy for Market Activity
A volume spike is defined as the ratio of current volume to its moving average. This ratio is normalized into a score, reflecting unusual trading activity, which may signal market turning points.
Reference: Volume analysis is a foundational tool in technical analysis and is often linked to price momentum (Murphy, 1999).
6. Sharpe Ratio for Risk-Adjusted Returns
The Sharpe ratio measures the risk-adjusted return of the asset, using the mean log return divided by its standard deviation over the same period. This ratio is transformed into a score, reflecting the attractiveness of returns relative to risk.
Reference: Sharpe (1966) introduced the Sharpe ratio as a standard measure of portfolio performance.
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Composite Risk Score
The composite risk score is calculated as a weighted average of the individual risk factors:
• Volatility: 30%
• Drawdown: 20%
• Put/Call Ratio: 20%
• Tail Risk (Z-Score): 15%
• Volume Spike: 10%
• Sharpe Ratio: 5%
This aggregation captures the multi-dimensional nature of systemic risk and provides a unified measure of market conditions.
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Dynamic Bands with Bollinger Bands
The composite risk score is smoothed using a moving average and bounded by Bollinger Bands (basis ± 2 standard deviations). These bands provide dynamic thresholds for identifying overbought and oversold market conditions:
• Upper Band: Signals overbought conditions, where risk is elevated.
• Lower Band: Indicates oversold conditions, where risk subsides.
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Trading Strategy
The strategy operates on the following rules:
1. Entry Condition: Enter a long position when the risk score crosses above the upper Bollinger Band, indicating elevated market activity.
2. Exit Condition: Close the long position when the risk score drops below the lower Bollinger Band, signaling a reduction in risk.
These conditions are consistent with momentum-based strategies and adaptive risk control.
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Conclusion
This script exemplifies a systematic approach to risk aggregation, leveraging multiple dimensions of financial risk to create a robust trading strategy. By incorporating well-established risk metrics and sentiment indicators, the model offers a comprehensive view of market dynamics. Its adaptive framework makes it versatile for various market conditions, aligning with contemporary advancements in quantitative finance.
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References
1. Hull, J. C. (2008). Options, Futures, and Other Derivatives. Pearson Education.
2. Maginn, J. L., Tuttle, D. L., McLeavey, D. W., & Pinto, J. E. (2007). Managing Investment Portfolios: A Dynamic Process. Wiley.
3. Markowitz, H. (1952). Portfolio Selection. The Journal of Finance, 7(1), 77–91.
4. Murphy, J. J. (1999). Technical Analysis of the Financial Markets. New York Institute of Finance.
5. Sharpe, W. F. (1966). Mutual Fund Performance. The Journal of Business, 39(1), 119–138.
6. Taleb, N. N. (2007). The Black Swan: The Impact of the Highly Improbable. Random House.
7. Whaley, R. E. (2000). The Investor Fear Gauge. The Journal of Portfolio Management, 26(3), 12–17.
Improved Trend Shot | JeffreyTimmermansImproved Trend Shot
The "Improved Trend Shot" is an advanced trend-following tool that integrates cutting-edge features and the principles of John Ehlers’ SuperSmoother Filter to provide traders with more accurate trend detection and better decision-making. This enhanced version includes multiple smoothing types, customizable lengths, dynamic alerts, and a comprehensive dashboard to help traders quickly interpret market conditions.
This script is inspired by "TRW" . However, it is more advanced and includes additional features and options.
Key Features and Improvements
Smoothed Lines and Trend Detection
The core of the Improved Smooth Trend Shot relies on three key lines to capture market momentum:
Fast Line: Highly sensitive to short-term price changes, offering rapid responsiveness to market movements.
Middle Line: Provides a medium-term view of market trends, acting as a more stable reference.
Slow Line: Focuses on long-term trends, offering a broader perspective on market direction.
These three smoothed lines interact dynamically to create a visual color-coded cloud that helps traders easily interpret market conditions:
Green Cloud: Indicates an upward trend when the Fast line is above the Slow line.
Red Cloud: Signals a downward trend when the Fast line is below the Slow line.
The cloud color adjusts based on the relative positioning of the Fast, Middle, and Slow lines, helping traders to identify bullish or bearish trends with ease.
Dynamic Cloud Visualization and Alerts
The cloud and trend lines adapt to market conditions, updating in real-time to reflect changes in trend strength and momentum. Traders can also set up real-time alerts to notify them of important trend shifts, such as:
Fast and Slow Crossovers: Alerts when the Fast line crosses the Slow line.
Middle and Slow Crossovers: Alerts when the Middle line crosses the Slow line.
This makes it easier to capture trading opportunities and respond promptly to market changes.
Enhanced Smoothing Options
Traders can now choose from multiple smoothing types, including:
EMA (Exponential Moving Average)
SMA (Simple Moving Average)
DEMA (Double Exponential Moving Average)
WMA (Weighted Moving Average)
Each smoothing type has different properties, allowing traders to select the best fit for their trading style. The smoothing length can also be customized, offering flexibility in fine-tuning how sensitive or stable the trend lines should be.
Improved Signal Logic and Precision
The signal logic has been optimized for better precision. Now, the system provides more accurate buy and sell alerts based on:
Trend Detection: The color-coded cloud and the relative positions of the Fast, Middle, and Slow lines help visualize whether the trend is bullish or bearish.
Rising and Falling Indicators: The indicator also checks if each line is rising or falling over the last three bars, offering early signals of momentum shifts.
Dashboard Insights
The dashboard provides real-time updates on the positions and movements of the smoothed lines:
Line Positions: Displays the positions of the Fast, Middle, and Slow lines.
Trend Direction: Shows whether each line is rising or falling.
Price Levels: Displays the price levels for each of the smoothed lines, offering clear reference points for market evaluation.
These features help traders better understand the state of the market, offering valuable insights for both trend-following and reversal-based strategies.
Crossovers and Signal Triggers
The Improved Smooth Trend Shot focuses on crossovers between the different smoothed lines as primary trading signals. There are two types of crossovers:
Fast Shots: This occurs when the Fast line crosses the Slow line.
Slow Shots: This occurs when the Middle line crosses the Slow line.
These crossovers serve as key entry or exit points for traders, helping them spot potential trend reversals. The improved logic ensures that crossovers are accurately detected, reducing the chances of false signals.
Customization Options
The Improved Smooth Trend Shot offers a high degree of customization:
Smoothing Length: Adjust the smoothing period to balance between fast responses and stable trends.
Source Selection: Default to the average of high and low prices (hl2), or choose other price sources.
Smoothing Type: Select from EMA, SMA, DEMA, or WMA for personalized trend analysis.
Signal Type: Choose between Fast Shots or Slow Shots based on the type of crossover you want to focus on.
Long, Medium, and Short-Term Applications
Although the default settings are optimized for long-term trend analysis, the Improved Smooth Trend Shot is highly adaptable. By adjusting the smoothing length and selecting different smoothing types, traders can use the tool for:
Short-Term Trading: Focus on fast responses to market shifts using shorter smoothing periods.
Medium-Term Trading: Tailor the settings to capture intermediate trends.
Long-Term Trend Analysis: Use longer smoothing periods for a more stable and comprehensive view of market dynamics.
Advanced ATR Filtering and Alerts
The inclusion of ATR (Average True Range) filtering helps ensure that signals are triggered only when significant price movements occur. This helps reduce noise and false signals, ensuring traders only act on meaningful market shifts.
Conclusion
The Improved Smooth Trend Shot is a powerful and versatile tool that enhances the original SuperSmoother Filter with advanced features like customizable smoothing options, real-time alerts, and an intuitive dashboard. Whether you're a day trader, swing trader, or long-term investor, this enhanced indicator provides a comprehensive and actionable view of market trends.
The combination of enhanced signal accuracy, dynamic trend visualization, and in-depth customization ensures that the Improved Smooth Trend Shot is an indispensable tool for traders across all market conditions.
-Jeffrey
JJ Highlight Time Ranges with First 5 Minutes and LabelsTo effectively use this Pine Script as a day trader , here’s how the various elements can help you manage trades, track time sessions, and monitor price movements:
Key Components for a Day Trader:
1. First 5-Minute Highlight:
- Purpose: Day traders often rely on the first 5 minutes of the trading session to gauge market sentiment, watch for opening price gaps, or plan entries. This script draws a horizontal line at the high or low of the first 5 minutes, which can act as a key level for the rest of the day.
- How to Use: If the price breaks above or below the first 5-minute line, it can signal momentum. You might enter a long position if the price breaks above the first 5-minute high or a short if it breaks below the first 5-minute low.
2. Session Time Highlights:
- Morning Session (9:15–10:30 AM): The market often shows its strongest price action during the first hour of trading. This session is highlighted in yellow. You can use this highlight to focus on the most volatile period, as this is when large institutional moves tend to occur.
- Afternoon Session (12:30–2:55 PM): The blue highlight helps you track the mid-afternoon session, where liquidity may decrease, and price action can sometimes be choppier. Day traders should be more cautious during this period.
- How to Use: By highlighting these key times, you can:
- Focus on key breakouts during the morning session.
- Be more conservative in your trades during the afternoon, as market volatility may drop.
3. Dynamic Labels:
- Top/Bottom Positioning: The script places labels dynamically based on the selected position (Top or Bottom). This allows you to quickly glance at the session's start and identify where you are in terms of time.
- How to Use: Use these labels to remind yourself when major time segments (morning or afternoon) begin. You can adjust your trading strategy depending on the session, e.g., being more aggressive in the morning and more cautious in the afternoon.
Trading Strategy Suggestions:
1. Momentum Trades:
- After the first 5 minutes, use the high/low of that period to set up breakout trades.
- Long Entry: If the price breaks the high of the first 5 minutes (especially if there's a strong trend).
- Short Entry: If the price breaks the low of the first 5 minutes, signaling a potential downtrend.
2. Session-Based Strategy:
- Morning Session (9:15–10:30 AM):
- Look for strong breakout patterns such as support/resistance levels, moving average crossovers, or candlestick patterns (like engulfing candles or pin bars).
- This is a high liquidity period, making it ideal for executing quick trades.
- Afternoon Session (12:30–2:55 PM):
- The market tends to consolidate or show less volatility. Scalping and mean-reversion strategies work better here.
- Avoid chasing big moves unless you see a clear breakout in either direction.
3. Support and Resistance:
- The first 5-minute high/low often acts as a key support or resistance level for the rest of the day. If the price holds above or below this level, it’s an indication of trend continuation.
4. Breakout Confirmation:
- Look for breakouts from the highlighted session time ranges (e.g., 9:15 AM–10:30 AM or 12:30 PM–2:55 PM).
- If a breakout happens during a key time window, combine that with other technical indicators like volume spikes , RSI , or MACD for confirmation.
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Example Day Trader Usage:
1. First 5 Minutes Strategy: After the market opens at 9:15 AM, watch the price action for the first 5 minutes. The high and low of these 5 minutes are critical levels. If the price breaks above the high of the first 5 minutes, it might indicate a strong bullish trend for the day. Conversely, breaking below the low may suggest bearish movement.
2. Morning Session: After the first 5 minutes, focus on the **9:15 AM–10:30 AM** window. During this time, look for breakout setups at key support/resistance levels, especially when paired with high volume or momentum indicators. This is when many institutions make large trades, so price action tends to be more volatile and predictable.
3. Afternoon Session: From 12:30 PM–2:55 PM, the market might experience lower volatility, making it ideal for scalping or range-bound strategies. You could look for reversals or fading strategies if the market becomes too quiet.
Conclusion:
As a day trader, you can use this script to:
- Track and react to key price levels during the first 5 minutes.
- Focus on high volatility in the morning session (9:15–10:30 AM) and **be cautious** during the afternoon.
- Use session-based timing to adjust your strategies based on the time of day.
SV Volatility Indicator BasicThe SV Volatility Indicator Basic in TradingView calculates and visualizes daily and average volatility over specified periods using three lines. Here’s what it does:
1. Daily Volatility Calculation. The indicator computes daily volatility as the percentage difference between the high and low prices relative to the closing price:
2. 30-day Moving Average of Volatility. A simple moving average (SMA) is applied to the daily volatility values over the last 30 days to smooth short-term fluctuations.
3. 90-day Moving Average of Volatility. Similarly, an SMA is calculated over the last 90 days to provide a longer-term view of volatility trends.
4. Visualization:
Three lines are plotted:
Red line: Represents the daily volatility in percentage terms.
Blue line: Displays the 30-day moving average of volatility.
Green line: Shows the 90-day moving average of volatility.
This indicator helps traders analyze market volatility by providing both immediate (daily) and smoothed (30-day and 90-day) measures, aiding in trend identification and risk assessment.
Time-Based VWAP (TVWAP)(TVWAP) Indicator
The Time-Based Volume Weighted Average Price (TVWAP) indicator is a customized version of VWAP designed for intraday trading sessions with defined start and end times. Unlike the traditional VWAP, which calculates the volume-weighted average price over an entire trading day, this indicator allows you to focus on specific time periods, such as ICT kill zones (e.g., London Open, New York Open, Power Hour). It helps crypto scalpers and advanced traders identify price deviations relative to volume during key trading windows.
Key Features:
Custom Time Interval:
You can set the exact start and end times for the VWAP calculation using input settings for hours and minutes (24-hour format).
Ideal for analyzing short, high-liquidity periods.
Dynamic Accumulation of Price and Volume:
The indicator resets at the beginning of the specified session and accumulates price-volume data until the end of the session.
Ensures that the TVWAP reflects the weighted average price specific to the chosen session.
Visual Representation:
The indicator plots the TVWAP line only during the specified time window, providing a clear visual reference for price action during that period.
Outside the session, the TVWAP line is hidden (na).
Use Cases:
ICT Scalp Trading:
Monitor price rebalances or potential liquidity sweeps near TVWAP during important trading sessions.
Mean Reversion Strategies:
Detect pullbacks toward the session’s average price for potential entry points.
Breakout Confirmation:
Confirm price direction relative to TVWAP during kill zones or high-volume times to determine if a breakout is supported by volume.
Inputs:
Start Hour/Minute: The time when the TVWAP calculation starts.
End Hour/Minute: The time when the TVWAP calculation ends.
Technical Explanation:
The indicator uses the timestamp function to create time markers for the session start and end.
During the session, the price-volume (close * volume) is accumulated along with the total volume.
TVWAP is calculated as:
TVWAP = (Sum of (Price × Volume)) ÷ (Sum of Volume)
Once the session ends, the TVWAP resets for the next trading period.
Customization Ideas:
Alerts: Add notifications when the price touches or deviates significantly from TVWAP.
Different Colors: Use different line colors based on upward or downward trends.
Multiple Sessions: Add support for multiple TVWAP lines for different time periods (e.g., London + New York).
Best Range (Day Trading)The indicator is based on a formula very similar to that of the ATR. The average volatility of the last candles (a value adjustable via inputs) is calculated, and this value is then divided (a value adjustable via inputs), providing a specific value in terms of RANGE .
Its use is very straightforward. It was primarily designed for stock indices (Nasdaq & SPX). When used on the DAILY timeframe, it provides the recommended RANGE value for day trading with structural logic.
Its goal is to offer a guiding value for setting the chart to a range-based view that is optimal and as effective as possible in identifying breakouts of specific levels , helping traders avoid false breakouts or misleading structures.
We can also observe a division of levels into quartiles (25, 50, 75, 100, 125...). This helps provide reference ranges, allowing the range to be used with rounded numbers .
For example, on Nasdaq , if the indicator set on DAILY provides a value between 200 and 250, then it is advisable to visualize the chart at 200 RANGE for a more aggressive approach or at 250 RANGE for a more conservative approach.
On SPX , which is less volatile, we use increments of 25. If the indicator gives a value between 25 and 50 , then we use 25 for an aggressive approach and 50 for a conservative approach.
Obviously, this refers to FUTURES and the tick movements of MINI contracts.
Channel Breakout by NatXateThe Channel Breakout by NatXate is a multi-channel technical indicator designed to identify potential breakout opportunities based on a combination of Keltner Channels, Donchian Channels, and Bollinger Bands.
This indicator helps traders pinpoint buy and sell signals by analyzing price behavior around key channel boundaries, while filtering out false signals using volatility and momentum criteria such as the Average True Range (ATR) and Bollinger Bands Width (BBW).
Key Features:
Keltner Channel:
The Keltner Channel is calculated using an Exponential Moving Average (EMA) and ATR to define upper and lower boundaries.
The upper and lower Keltner boundaries serve as potential breakout levels.
Donchian Channel:
The Donchian Channel tracks the highest high and lowest low over a user-defined period.
Price breaking above or below these boundaries indicates a potential long or short opportunity.
Bollinger Bands:
Bollinger Bands use a Simple Moving Average (SMA) and standard deviation to define dynamic support and resistance levels.
The upper and lower Bollinger boundaries provide an additional layer of confirmation for breakouts.
Bollinger Bands Width (BBW) Filter:
Measures the width of the Bollinger Bands, which reflects market volatility.
A minimum BBW threshold (minBBW) ensures signals are only generated during periods of sufficient volatility, helping to avoid false signals in consolidating markets.
ATR Filter:
The ATR is used to measure market volatility.
Only signals with ATR exceeding a user-defined percentage of the current price (atrThresholdPercent) are considered valid.
Buy and Sell Conditions:
Buy Signal:
Price breaks above the upper boundary of any of the three channels (Keltner, Donchian, or Bollinger Bands).
ATR is above its threshold, indicating sufficient volatility.
BBW is above the minBBW threshold.
Sell Signal:
Price breaks below the lower boundary of any of the three channels.
ATR is above its threshold.
BBW is above the minBBW threshold.
Non-Repainting Logic:
Signals are confirmed only after the bar closes (barstate.isconfirmed), preventing repainting and ensuring reliable signal generation.
Visual Signals:
Buy signals are marked with a green "B" label below the bar.
Sell signals are marked with a red "S" label above the bar.
The upper and lower boundaries of the Keltner Channel, Donchian Channel, and Bollinger Bands are plotted for visual clarity.
Alerts:
Separate alerts are available for Buy and Sell signals:
Buy Signal: "Channel Breakout Buy Signal by NatXate detected!"
Sell Signal: "Channel Breakout Sell Signal by NatXate detected!"
Alerts trigger once per bar close, making it suitable for real-time trading or monitoring.
How It Works:
Trend Identification:
The indicator identifies trends based on price breakouts above or below the channel boundaries.
Volatility Filtering:
Both ATR and BBW filters ensure that only high-probability breakout signals are shown, reducing noise in low-volatility environments.
Signal Confirmation:
Signals are confirmed after the bar closes to prevent false positives or premature triggers.
Parameters:
Keltner Channel Parameters:
lengthKC: Period for the Keltner Channel's EMA.
multKC: ATR multiplier for Keltner Channel boundaries.
Donchian Channel Parameters:
lengthDC: Period for calculating the highest high and lowest low.
Bollinger Bands Parameters:
lengthBB: Period for the Bollinger Bands' SMA.
multBB: Standard deviation multiplier for Bollinger Bands boundaries.
ATR Filter:
atrLength: Period for calculating ATR.
atrThresholdPercent: Minimum ATR as a percentage of the price for valid signals.
BBW Filter:
minBBW: Minimum Bollinger Bands Width required for signal generation.
Use Cases:
Breakout Trading:
Detect potential buy and sell opportunities when price breaks key channel boundaries during high volatility.
Trend Following:
Use the indicator to confirm trends and enter trades in the direction of the breakout.
Avoiding Low-Volatility Periods:
The BBW and ATR filters help avoid false signals in consolidating or choppy markets.
Recommended Usage:
Combine this indicator with additional tools such as volume analysis or momentum oscillators (e.g., MACD, RSI) for further confirmation.
Suitable for various timeframes, from intraday to swing trading.
Backtest thoroughly to adjust parameters for the specific market and timeframe you trade.
Dynamic Intensity Transition Oscillator (DITO)The Dynamic Intensity Transition Oscillator (DITO) is a comprehensive indicator designed to identify and visualize the slope of price action normalized by volatility, enabling consistent comparisons across different assets. This indicator calculates and categorizes the intensity of price movement into six states—three positive and three negative—while providing visual cues and alerts for state transitions.
Components and Functionality
1. Slope Calculation
- The slope represents the rate of change in price action over a specified period (Slope Calculation Period).
- It is calculated as the difference between the current price and the simple moving average (SMA) of the price, divided by the length of the period.
2. Normalization Using ATR
- To standardize the slope across assets with different price scales and volatilities, the slope is divided by the Average True Range (ATR).
- The ATR ensures that the slope is comparable across assets with varying price levels and volatility.
3. Intensity Levels
- The normalized slope is categorized into six distinct intensity levels:
High Positive: Strong upward momentum.
Medium Positive: Moderate upward momentum.
Low Positive: Weak upward movement or consolidation.
Low Negative: Weak downward movement or consolidation.
Medium Negative: Moderate downward momentum.
High Negative: Strong downward momentum.
4. Visual Representation
- The oscillator is displayed as a histogram, with each intensity level represented by a unique color:
High Positive: Lime green.
Medium Positive: Aqua.
Low Positive: Blue.
Low Negative: Yellow.
Medium Negative: Purple.
High Negative: Fuchsia.
Threshold levels (Low Intensity, Medium Intensity) are plotted as horizontal dotted lines for visual reference, with separate colors for positive and negative thresholds.
5. Intensity Table
- A dynamic table is displayed on the chart to show the current intensity level.
- The table's text color matches the intensity level color for easy interpretation, and its size and position are customizable.
6. Alerts for State Transitions
- The indicator includes a robust alerting system that triggers when the intensity level transitions from one state to another (e.g., from "Medium Positive" to "High Positive").
- The alert includes both the previous and current states for clarity.
Inputs and Customization
The DITO indicator offers a variety of customizable settings:
Indicator Parameters
Slope Calculation Period: Defines the period over which the slope is calculated.
ATR Calculation Period: Defines the period for the ATR used in normalization.
Low Intensity Threshold: Threshold for categorizing weak momentum.
Medium Intensity Threshold: Threshold for categorizing moderate momentum.
Intensity Table Settings
Table Position: Allows you to position the intensity table anywhere on the chart (e.g., "Bottom Right," "Top Left").
Table Size: Enables customization of table text size (e.g., "Small," "Large").
Use Cases
Trend Identification:
- Quickly assess the strength and direction of price movement with color-coded intensity levels.
Cross-Asset Comparisons:
- Use the normalized slope to compare momentum across different assets, regardless of price scale or volatility.
Dynamic Alerts:
- Receive timely alerts when the intensity transitions, helping you act on significant momentum changes.
Consolidation Detection:
- Identify periods of low intensity, signaling potential reversals or breakout opportunities.
How to Use
- Add the indicator to your chart.
- Configure the input parameters to align with your trading strategy.
Observe:
The Oscillator: Use the color-coded histogram to monitor price action intensity.
The Intensity Table: Track the current intensity level dynamically.
Alerts: Respond to state transitions as notified by the alerts.
Final Notes
The Dynamic Intensity Transition Oscillator (DITO) combines trend strength detection, cross-asset comparability, and real-time alerts to offer traders an insightful tool for analyzing market conditions. Its user-friendly visualization and comprehensive alerting make it suitable for both novice and advanced traders.
Disclaimer: This indicator is for educational purposes and is not financial advice. Always perform your own analysis before making trading decisions.
ADX (levels)This Pine Script indicator calculates and displays the Average Directional Index (ADX) along with the DI+ and DI- lines to help identify the strength and direction of a trend. The script is designed for Pine Script v6 and includes customizable settings for a more tailored analysis.
Features:
ADX Calculation:
The ADX measures the strength of a trend without indicating its direction.
It uses a smoothing method for more reliable trend strength detection.
DI+ and DI- Lines (Optional):
The DI+ (Directional Index Plus) and DI- (Directional Index Minus) help determine the direction of the trend:
DI+ indicates upward movement.
DI- indicates downward movement.
These lines are disabled by default but can be enabled via input settings.
Customizable Threshold:
A horizontal line (hline) is plotted at a user-defined threshold level (default: 20) to highlight significant ADX values that indicate a strong trend.
Slope Analysis:
The slope of the ADX is analyzed to classify the trend into:
Strong Trend: Slope is higher than a defined "medium" threshold.
Moderate Trend: Slope falls between "weak" and "medium" thresholds.
Weak Trend: Slope is positive but below the "weak" threshold.
A background color changes dynamically to reflect the strength of the trend:
Green (light or dark) indicates trend strength levels.
Custom Colors:
ADX color is customizable (default: pink #e91e63).
Background colors for trend strength can also be adjusted.
Independent Plot Window:
The indicator is displayed in a separate window below the price chart, making it easier to analyze trend strength without cluttering the main price chart.
Parameters:
ADX Period: Defines the lookback period for calculating the ADX (default: 14).
Threshold (hline): A horizontal line value to differentiate strong trends (default: 20).
Slope Thresholds: Adjustable thresholds for weak, moderate, and strong trend slopes.
Enable DI+ and DI-: Boolean options to display or hide the DI+ and DI- lines.
Colors: Customizable colors for ADX, background gradients, and other elements.
How to Use:
Identify Trend Strength:
Use the ADX value to determine the strength of a trend:
Below 20: Weak trend.
Above 20: Strong trend.
Analyze Trend Direction:
Enable DI+ and DI- to check whether the trend is upward (DI+ > DI-) or downward (DI- > DI+).
Dynamic Slope Detection:
Use the background color as a quick visual cue to assess trend strength changes.
This indicator is ideal for traders who want to measure trend strength and direction dynamically while maintaining a clean and organized chart layout.
Percentage Calculator by Akshay GaurThis indicator calculates and displays percentage levels above and below the current price. It allows you to easily identify any percentage levels which can be used in many things like creating strangles and straddles and make informed trading decisions. The indicator automatically adjusts and redraws the lines and labels on the latest bar to reflect real-time market conditions.
Key Features:
• Calculates percentage levels above and below the current price
• Displays percentage levels on big labels with the horizontal lines on the chart
• Allows you to adjust the percentage value and every details.
• Allows you to see Fluctuation line on the chart.
How to Use:
1. Set the percentage value to the desired level (e.g. 1%, 2%, etc.)
2. If you want to see Fluctuation lines also then turn on it from Input settings.
3. Use the displayed levels to identify desired percentage levels.
4. Make informed trading decisions based on the calculated levels
Implied and Historical VolatilityAbstract
This TradingView indicator visualizes implied volatility (IV) derived from the VIX index and historical volatility (HV) computed from past price data of the S&P 500 (or any selected asset). It enables users to compare market participants' forward-looking volatility expectations (via VIX) with realized past volatility (via historical returns). Such comparisons are pivotal in identifying risk sentiment, volatility regimes, and potential mispricing in derivatives.
Functionality
Implied Volatility (IV):
The implied volatility is extracted from the VIX index, often referred to as the "fear gauge." The VIX represents the market's expectation of 30-day forward volatility, derived from options pricing on the S&P 500. Higher values of VIX indicate increased uncertainty and risk aversion (Whaley, 2000).
Historical Volatility (HV):
The historical volatility is calculated using the standard deviation of logarithmic returns over a user-defined period (default: 20 trading days). The result is annualized using a scaling factor (default: 252 trading days). Historical volatility represents the asset's past price fluctuation intensity, often used as a benchmark for realized risk (Hull, 2018).
Dynamic Background Visualization:
A dynamic background is used to highlight the relationship between IV and HV:
Yellow background: Implied volatility exceeds historical volatility, signaling elevated market expectations relative to past realized risk.
Blue background: Historical volatility exceeds implied volatility, suggesting the market might be underestimating future uncertainty.
Use Cases
Options Pricing and Trading:
The disparity between IV and HV provides insights into whether options are over- or underpriced. For example, when IV is significantly higher than HV, options traders might consider selling volatility-based derivatives to capitalize on elevated premiums (Natenberg, 1994).
Market Sentiment Analysis:
Implied volatility is often used as a proxy for market sentiment. Comparing IV to HV can help identify whether the market is overly optimistic or pessimistic about future risks.
Risk Management:
Institutional and retail investors alike use volatility measures to adjust portfolio risk exposure. Periods of high implied or historical volatility might necessitate rebalancing strategies to mitigate potential drawdowns (Campbell et al., 2001).
Volatility Trading Strategies:
Traders employing volatility arbitrage can benefit from understanding the IV/HV relationship. Strategies such as "long gamma" positions (buying options when IV < HV) or "short gamma" (selling options when IV > HV) are directly informed by these metrics.
Scientific Basis
The indicator leverages established financial principles:
Implied Volatility: Derived from the Black-Scholes-Merton model, implied volatility reflects the market's aggregate expectation of future price fluctuations (Black & Scholes, 1973).
Historical Volatility: Computed as the realized standard deviation of asset returns, historical volatility measures the intensity of past price movements, forming the basis for risk quantification (Jorion, 2007).
Behavioral Implications: IV often deviates from HV due to behavioral biases such as risk aversion and herding, creating opportunities for arbitrage (Baker & Wurgler, 2007).
Practical Considerations
Input Flexibility: Users can modify the length of the HV calculation and the annualization factor to suit specific markets or instruments.
Market Selection: The default ticker for implied volatility is the VIX (CBOE:VIX), but other volatility indices can be substituted for assets outside the S&P 500.
Data Frequency: This indicator is most effective on daily charts, as VIX data typically updates at a daily frequency.
Limitations
Implied volatility reflects the market's consensus but does not guarantee future accuracy, as it is subject to rapid adjustments based on news or events.
Historical volatility assumes a stationary distribution of returns, which might not hold during structural breaks or crises (Engle, 1982).
References
Black, F., & Scholes, M. (1973). "The Pricing of Options and Corporate Liabilities." Journal of Political Economy, 81(3), 637-654.
Whaley, R. E. (2000). "The Investor Fear Gauge." The Journal of Portfolio Management, 26(3), 12-17.
Hull, J. C. (2018). Options, Futures, and Other Derivatives. Pearson Education.
Natenberg, S. (1994). Option Volatility and Pricing: Advanced Trading Strategies and Techniques. McGraw-Hill.
Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (2001). The Econometrics of Financial Markets. Princeton University Press.
Jorion, P. (2007). Value at Risk: The New Benchmark for Managing Financial Risk. McGraw-Hill.
Baker, M., & Wurgler, J. (2007). "Investor Sentiment in the Stock Market." Journal of Economic Perspectives, 21(2), 129-151.
Dynamic Volatility Differential Model (DVDM)The Dynamic Volatility Differential Model (DVDM) is a quantitative trading strategy designed to exploit the spread between implied volatility (IV) and historical (realized) volatility (HV). This strategy identifies trading opportunities by dynamically adjusting thresholds based on the standard deviation of the volatility spread. The DVDM is versatile and applicable across various markets, including equity indices, commodities, and derivatives such as the FDAX (DAX Futures).
Key Components of the DVDM:
1. Implied Volatility (IV):
The IV is derived from options markets and reflects the market’s expectation of future price volatility. For instance, the strategy uses volatility indices such as the VIX (S&P 500), VXN (Nasdaq 100), or RVX (Russell 2000), depending on the target market. These indices serve as proxies for market sentiment and risk perception (Whaley, 2000).
2. Historical Volatility (HV):
The HV is computed from the log returns of the underlying asset’s price. It represents the actual volatility observed in the market over a defined lookback period, adjusted to annualized levels using a multiplier of \sqrt{252} for daily data (Hull, 2012).
3. Volatility Spread:
The difference between IV and HV forms the volatility spread, which is a measure of divergence between market expectations and actual market behavior.
4. Dynamic Thresholds:
Unlike static thresholds, the DVDM employs dynamic thresholds derived from the standard deviation of the volatility spread. The thresholds are scaled by a user-defined multiplier, ensuring adaptability to market conditions and volatility regimes (Christoffersen & Jacobs, 2004).
Trading Logic:
1. Long Entry:
A long position is initiated when the volatility spread exceeds the upper dynamic threshold, signaling that implied volatility is significantly higher than realized volatility. This condition suggests potential mean reversion, as markets may correct inflated risk premiums.
2. Short Entry:
A short position is initiated when the volatility spread falls below the lower dynamic threshold, indicating that implied volatility is significantly undervalued relative to realized volatility. This signals the possibility of increased market uncertainty.
3. Exit Conditions:
Positions are closed when the volatility spread crosses the zero line, signifying a normalization of the divergence.
Advantages of the DVDM:
1. Adaptability:
Dynamic thresholds allow the strategy to adjust to changing market conditions, making it suitable for both low-volatility and high-volatility environments.
2. Quantitative Precision:
The use of standard deviation-based thresholds enhances statistical reliability and reduces subjectivity in decision-making.
3. Market Versatility:
The strategy’s reliance on volatility metrics makes it universally applicable across asset classes and markets, ensuring robust performance.
Scientific Relevance:
The strategy builds on empirical research into the predictive power of implied volatility over realized volatility (Poon & Granger, 2003). By leveraging the divergence between these measures, the DVDM aligns with findings that IV often overestimates future volatility, creating opportunities for mean-reversion trades. Furthermore, the inclusion of dynamic thresholds aligns with risk management best practices by adapting to volatility clustering, a well-documented phenomenon in financial markets (Engle, 1982).
References:
1. Christoffersen, P., & Jacobs, K. (2004). The importance of the volatility risk premium for volatility forecasting. Journal of Financial and Quantitative Analysis, 39(2), 375-397.
2. Engle, R. F. (1982). Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987-1007.
3. Hull, J. C. (2012). Options, Futures, and Other Derivatives. Pearson Education.
4. Poon, S. H., & Granger, C. W. J. (2003). Forecasting volatility in financial markets: A review. Journal of Economic Literature, 41(2), 478-539.
5. Whaley, R. E. (2000). The investor fear gauge. Journal of Portfolio Management, 26(3), 12-17.
This strategy leverages quantitative techniques and statistical rigor to provide a systematic approach to volatility trading, making it a valuable tool for professional traders and quantitative analysts.
Triple Power Stop [CHE]Triple Power Stop
This indicator provides a comprehensive multi-timeframe approach for stop level and trend analysis, tailored for traders who want enhanced precision and adaptability in their trading strategies. Here's what makes the Triple Power Stop (CHE) stand out:
Key Features:
1. ATR-Based Stop Levels:
- Uses the Average True Range (ATR) to dynamically calculate stop levels, ensuring sensitivity to market volatility.
- Adjustable ATR multiplier for fine-tuning the stop levels to fit different trading styles.
2. Multi-Timeframe Analysis:
- Evaluates trends across three different timeframes with user-defined multipliers.
- Enables deeper insight into the market's broader context while keeping the focus on precision.
3. Dynamic Volatility Adjustment:
- Introduces a unique volatility factor to enhance stop-level calculations.
- Adapts to market conditions, offering reliable support for both trending and ranging markets.
4. Clear Trend Visualization:
- Stop levels and trends are visually represented with color-coded lines (green for uptrend, red for downtrend).
- Seamlessly integrates trend changes and helps identify potential reversals.
5. Signal Alerts:
- Long and short entry signals are plotted directly on the chart for actionable insights.
- Eliminates guesswork and provides clarity in decision-making.
6. Customizability:
- Adjustable parameters such as ATR length, multipliers, and label counts, allowing traders to tailor the indicator to their strategies.
Practical Use:
The Triple Power Stop (CHE) is ideal for traders who want to:
- Manage risk effectively: With dynamically calculated stop levels, traders can protect their positions while allowing room for natural market fluctuations.
- Follow the trend: Multi-timeframe trend detection ensures alignment with broader market movements.
- Simplify decisions: Clear visual indicators and signals make trading decisions more intuitive and less stressful.
How to Use:
1. Set the ATR length and multiplier values based on your risk tolerance and trading strategy.
2. Choose multipliers for different timeframes to adapt the indicator to your preferred resolutions.
3. Use the color-coded trend lines and entry signals to time your trades and manage positions efficiently.
Disclaimer:
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Enhance your trading precision and confidence with Triple Power Stop (CHE)! 🚀
Happy trading
Chervolino
DAILY ATR LEVELS AND EXPECTED MOVE LEVELSThis Pine Script code is designed to visualize ATR (Average True Range) levels and expected move levels on a chart. It provides useful inputs for customizing how these levels are displayed, such as line width, style, and color. The script is divided into several sections, each focused on a different feature:
1. User Inputs for Customization:
- Line Width and Style: Users can customize the line width, style (solid, dotted, or dashed), and color for various levels.
- Offset for Line Placement: The rightOffset input controls how far in the future the lines extend (measured in minutes).
- Show Labels: Labels can be toggled on/off for ATR levels and expected move lines, with customizable text colors.
2. ATR Levels and ATR Settings:
- The ATR length (atrLength) and the multiplier (atrMultiplier) control the calculation of ATR levels.
- The script plots ATR levels based on the daily open price, including key levels like ATR +25%, ATR +50%, etc., for both positive and negative movements.
- Line Drawing: The script dynamically creates lines for each ATR level, and the lines are customized according to the user's inputs. For each level, the line.new function is used to plot a line from the start of the day (daily open) to a point offset in the future.
- Labels: Labels are added near each ATR level to make them more identifiable, such as "ATR +25%" or "Daily Open."
3. Expected Move Calculation and Logic:
- The script calculates the expected move for the next trading session based on the previous close price and the volatility derived from the VIX (Volatility Index).
- The expected move is calculated as a percentage of the previous close and is added and subtracted from the previous close price to generate upper and lower levels.
- Volatility Adjustment: The VIX value is adjusted by the square root of 252 (the number of average trading days in a year) to calculate the daily volatility.
- Upper and Lower Lines: Lines are drawn for the expected move's upper and lower bounds, showing the potential price movement based on volatility.
4. Customizable Expected Move Lines:
- Line Style and Color: The upper and lower expected move lines can be customized in terms of width, style, and color, as specified by the user.
- Labels for Expected Move Levels: Labels are added for the upper and lower expected move lines, such as "Expected Move Upper" and "Expected Move Lower."
5. Logic for Drawing Lines:
- The script continuously evaluates whether the levels should be displayed based on the user's preferences.
- If showATRLevels or showLineEM is enabled, the script will draw the respective lines and labels on the chart.
- It uses line.new to draw the lines and label.new to position the labels at the correct levels on the chart.
6. Handling Time and Line Deletion:
- The script handles the dynamic nature of the chart by deleting previous lines (using line.delete) to avoid cluttering the chart with outdated lines.
- The time for the lines is set dynamically using the startTime and endTime variables, ensuring that lines are drawn within the correct timeframe.
Summary of Key Features:
- ATR Levels: Plots key levels of ATR, such as daily open, ATR +25%, ATR -25%, etc., with customizable colors and line styles.
- Expected Move Levels: Calculates and plots the upper and lower bounds of the expected move based on the VIX and previous close price.
- Customization Options: Users can control the appearance (line width, style, color) and whether to show labels for the ATR and expected move levels.
- Dynamic Updates: The lines and labels update dynamically throughout the trading day, adjusting based on market conditions.
Overall, this script is designed to help traders visualize volatility and potential price movement on a daily chart by providing ATR-based levels and expected move projections. It offers a high degree of customization to suit different charting preferences.
ADR Table BY @ICT_YEROADR Table BY @ICT_YERO
Created by: @ICT_YERO
This custom indicator is designed to provide the Average Daily Range (ADR) for multiple timeframes, including Daily, 4-Hour, and 1-Hour. The indicator is tailored to assist traders in understanding price volatility and making informed trading decisions.
Key Features
Multi-Timeframe ADR Calculation:
Automatically calculates and displays the ADR for Daily, 4-Hour, and 1-Hour timeframes.
Helps traders identify potential price movement ranges for different trading sessions.
Dynamic Range Visualization:
Clear visual representation of the ADR on the chart, making it easy to spot price extremes.
Real-time updates to reflect changes in price movement.
Custom Alerts:
Option to set alerts when the price approaches the ADR high or low.
Useful for identifying potential reversal zones or breakout opportunities.
User-Friendly Interface:
Simple and intuitive settings to customize colors, levels, and display preferences.
Seamlessly integrates with your existing TradingView setup.
ICT-Inspired Methodology:
Designed for traders who follow ICT concepts, focusing on precision and high-probability setups.
Applications
Range Trading: Helps determine the high and low boundaries for scalping or intraday setups.
Volatility Analysis: Understand market behavior during different times of the day or week.
Reversal Zones: Identify areas where price is likely to reverse, based on ADR extremes.
Whether you're a scalper, day trader, or swing trader, this indicator provides a comprehensive overview of price volatility across multiple timeframes, making it an essential tool for your trading arsenal.
DAILY ATR LEVELSThis script is a custom technical indicator for use in TradingView, designed to display daily Average True Range (ATR) levels on the chart, along with the daily opening price. It provides a customizable way to track price levels relative to the daily ATR, which can be useful for traders looking for volatility-based price targets or ranges.
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Customization Options:
- Line Width: Determines the thickness of the plotted lines for the ATR levels and daily open line, ranging from 1 to 10.
- Right Offset (minutes): A time offset (in minutes) that shifts the end of the daily opening price line to the right for visual clarity.
- Line Style: The user can choose between solid, dashed, or dotted lines for all the plotted levels.
- Display Options: Users can toggle the visibility of the daily opening price line (showDayLevel), labels (showLabels), and ATR levels (showATRLevels).
- Colors: Customizable colors for the daily opening price line (dayLevelColor), labels (labelTextColor), and the ATR levels for both positive and negative values (atrLevelPlusColor and atrLevelMinusColor).
ATR Settings:
- ATR Length: Defines the number of periods (bars) to use when calculating the ATR. The default is 180, which corresponds to the ATR calculated on the daily chart using the last 180 bars.
- ATR Multiplier: Allows the user to scale the ATR levels by a multiplier (from 0.1 to 5.0), adjusting the sensitivity of the levels.
- ATR Levels: Users can toggle visibility for several predefined ATR levels, such as +25%, +50%, +75%, +100%, -25%, -50%, -75%, and -100%. These levels represent price points above or below the daily open based on the ATR.
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ATR Levels Calculation:
- The ATR is calculated based on the daily chart using the ta.atr() function with the specified ATR length, default is set at 180.
- The script computes multiple ATR levels above and below the daily open price, adjusting each level by 25%, 50%, 75%, and 100% of the ATR value (scaled by the ATR multiplier).
ATR Level Plotting:
- For each ATR level (positive and negative), a line is drawn across the chart at the corresponding price level.
- The color, line style, and width of these lines can be customized.
- Each ATR level also has an optional label showing the percentage level (e.g., "ATR +25%") at the specified price, which is positioned at the end of the line.
- The labels are removed from the previous bars to avoid clutter.
Workflow:
- The script first calculates the daily opening price using the request.security() function to pull the open price from the daily chart.
- It then calculates the ATR based on the selected length and multiplier.
- The start time for the daily open line is determined by the bar's timestamp at the start of the day, and the end time is adjusted using the user-defined right offset.
- After determining the relevant price levels (for the opening price and ATR levels), the script plots these levels on the chart as lines. It handles the drawing and deletion of lines to ensure that the chart remains updated in real time.
- If labels are enabled, text labels are displayed next to the ATR levels and the daily open line, providing clear markers for the user.
Practical Use:
- Volatility Analysis: This indicator is useful for identifying key price levels based on daily volatility (ATR). Traders can use it to set potential targets or support/resistance levels that are adjusted for volatility.
- Day Trading or Swing Trading: The daily opening price line helps traders quickly see where the price opened for the day, and the ATR levels give a dynamic range for the day's potential price movement.
Overall, this script is designed to provide a clear, customizable view of daily price levels in relation to the ATR, helping traders make informed decisions based on volatility and price action.
goose's session + killzone indicatorA powerful, multi-functional TradingView script designed for forex traders. It visually delineates major market sessions—Asia, London, and New York—on the chart, provides customizable session ranges, pip range counters, and configurable “killzone” markers. The indicator allows users to switch between a traditional line-and-fill style and a historical box style for session visualization, offering both real-time and historical context of market ranges.
Key Features:
1. Session Visualization Options:
• Lines & Fill Style:
• Highlights active sessions using dynamic lines and filled areas that update in real-time.
• Displays session high, low, and mid-range boundaries with customizable colors, border widths, and line styles.
• Historical Boxes Style:
• Creates and retains boxes for each past session, enabling users to review historical session ranges over extended periods.
• Each session box is drawn with user-defined fill and border colors, opacity, and line styles, anchored to the session’s high, low, and timeframe.
• Supports viewing multiple historical sessions at once, up to a configurable limit.
2. Pip Range Counters:
• Displays the range of pips for each active session, anchored to a fixed position near the bottom-right corner of the session.
• Uses arrow-style labels (label.style_label_up/down) to maintain a stable visual offset relative to the session, minimizing movement during vertical zoom.
• Customizable text size, color, and vertical offset, ensuring the pip counter remains legible and unobtrusive.
3. Killzone Lines:
• Allows users to define up to 15 custom “killzone” times with specific line colors, styles, and optional labels.
• Each killzone is drawn precisely when the price crosses the user-specified time, marking important market events or transitions.
4. User Configurations:
• Session Times: Fully adjustable start and end times for Asian, London, and New York sessions.
• Color & Style Settings:
• Customizable fill and border colors (with adjustable opacity) for each session style.
• User-friendly dropdowns and checkboxes for setting line styles, widths, and text sizes.
• Display Mode Selector:
• A dropdown (sessionStyle) lets users toggle between “Lines & Fill” and “Historical Boxes” for session visualization.
• Pip Counter and Killzone Settings:
• Options to show or hide pip counters, match label colors to session fills, and configure killzone appearance individually.
5. Robust Utility Functions:
• Functions to parse user-input times, determine if the current time falls within a session, and calculate session ranges.
• Historical session logic that detects session transitions and creates/upgrades boxes accordingly.
How It Works:
• Session Style Selection:
• Users choose their preferred visualization style via the sessionStyle dropdown.
• If “Lines & Fill” is selected, the indicator plots dynamic lines and fills during active sessions.
• If “Boxes” is selected, the indicator creates historical boxes that outline the range of each past session, persisting on the chart until session boundaries change.
• Pip Counter Labeling:
• During an active session, the pip counter calculates the range between the session’s high and low and displays it as text positioned just below the bottom-right corner of the session.
• The use of arrow-style labels ensures the text remains at a stable visual distance from the session’s outline, even when zooming vertically.
• Killzones:
• Users can define specific times (“killzones”) where important market events occur.
• When the price crosses these times, the script draws lines and optional labels with user-defined appearance settings.
Ideal Use Cases:
• Real-Time Trading: Quickly identify current session ranges, pip sizes, and crucial killzone markers during live trading.
• Historical Analysis: Switch to Historical Boxes to review past session ranges over days, weeks, or months, aiding in pattern recognition and strategy refinement.
• Customization: Tailor the appearance to match personal preferences or chart themes, including colors, styles, line widths, and label sizes.
This comprehensive indicator combines real-time session tracking with historical range visualization and customizable killzones. Its dual display modes, extensive settings, and stable pip counter labels make it a versatile tool for forex traders seeking to analyze market sessions both in the moment and retrospectively.
Adaptive Momentum Reversion StrategyThe Adaptive Momentum Reversion Strategy: An Empirical Approach to Market Behavior
The Adaptive Momentum Reversion Strategy seeks to capitalize on market price dynamics by combining concepts from momentum and mean reversion theories. This hybrid approach leverages a Rate of Change (ROC) indicator along with Bollinger Bands to identify overbought and oversold conditions, triggering trades based on the crossing of specific thresholds. The strategy aims to detect momentum shifts and exploit price reversions to their mean.
Theoretical Framework
Momentum and Mean Reversion: Momentum trading assumes that assets with a recent history of strong performance will continue in that direction, while mean reversion suggests that assets tend to return to their historical average over time (Fama & French, 1988; Poterba & Summers, 1988). This strategy incorporates elements of both, looking for periods when momentum is either overextended (and likely to revert) or when the asset’s price is temporarily underpriced relative to its historical trend.
Rate of Change (ROC): The ROC is a straightforward momentum indicator that measures the percentage change in price over a specified period (Wilder, 1978). The strategy calculates the ROC over a 2-period window, making it responsive to short-term price changes. By using ROC, the strategy aims to detect price acceleration and deceleration.
Bollinger Bands: Bollinger Bands are used to identify volatility and potential price extremes, often signaling overbought or oversold conditions. The bands consist of a moving average and two standard deviation bounds that adjust dynamically with price volatility (Bollinger, 2002).
The strategy employs two sets of Bollinger Bands: one for short-term volatility (lower band) and another for longer-term trends (upper band), with different lengths and standard deviation multipliers.
Strategy Construction
Indicator Inputs:
ROC Period: The rate of change is computed over a 2-period window, which provides sensitivity to short-term price fluctuations.
Bollinger Bands:
Lower Band: Calculated with a 18-period length and a standard deviation of 1.7.
Upper Band: Calculated with a 21-period length and a standard deviation of 2.1.
Calculations:
ROC Calculation: The ROC is computed by comparing the current close price to the close price from rocPeriod days ago, expressing it as a percentage.
Bollinger Bands: The strategy calculates both upper and lower Bollinger Bands around the ROC, using a simple moving average as the central basis. The lower Bollinger Band is used as a reference for identifying potential long entry points when the ROC crosses above it, while the upper Bollinger Band serves as a reference for exits, when the ROC crosses below it.
Trading Conditions:
Long Entry: A long position is initiated when the ROC crosses above the lower Bollinger Band, signaling a potential shift from a period of low momentum to an increase in price movement.
Exit Condition: A position is closed when the ROC crosses under the upper Bollinger Band, or when the ROC drops below the lower band again, indicating a reversal or weakening of momentum.
Visual Indicators:
ROC Plot: The ROC is plotted as a line to visualize the momentum direction.
Bollinger Bands: The upper and lower bands, along with their basis (simple moving averages), are plotted to delineate the expected range for the ROC.
Background Color: To enhance decision-making, the strategy colors the background when extreme conditions are detected—green for oversold (ROC below the lower band) and red for overbought (ROC above the upper band), indicating potential reversal zones.
Strategy Performance Considerations
The use of Bollinger Bands in this strategy provides an adaptive framework that adjusts to changing market volatility. When volatility increases, the bands widen, allowing for larger price movements, while during quieter periods, the bands contract, reducing trade signals. This adaptiveness is critical in maintaining strategy effectiveness across different market conditions.
The strategy’s pyramiding setting is disabled (pyramiding=0), ensuring that only one position is taken at a time, which is a conservative risk management approach. Additionally, the strategy includes transaction costs and slippage parameters to account for real-world trading conditions.
Empirical Evidence and Relevance
The combination of momentum and mean reversion has been widely studied and shown to provide profitable opportunities under certain market conditions. Studies such as Jegadeesh and Titman (1993) confirm that momentum strategies tend to work well in trending markets, while mean reversion strategies have been effective during periods of high volatility or after sharp price movements (De Bondt & Thaler, 1985). By integrating both strategies into one system, the Adaptive Momentum Reversion Strategy may be able to capitalize on both trending and reverting market behavior.
Furthermore, research by Chan (1996) on momentum-based trading systems demonstrates that adaptive strategies, which adjust to changes in market volatility, often outperform static strategies, providing a compelling rationale for the use of Bollinger Bands in this context.
Conclusion
The Adaptive Momentum Reversion Strategy provides a robust framework for trading based on the dual concepts of momentum and mean reversion. By using ROC in combination with Bollinger Bands, the strategy is capable of identifying overbought and oversold conditions while adapting to changing market conditions. The use of adaptive indicators ensures that the strategy remains flexible and can perform across different market environments, potentially offering a competitive edge for traders who seek to balance risk and reward in their trading approaches.
References
Bollinger, J. (2002). Bollinger on Bollinger Bands. McGraw-Hill Professional.
Chan, L. K. C. (1996). Momentum, Mean Reversion, and the Cross-Section of Stock Returns. Journal of Finance, 51(5), 1681-1713.
De Bondt, W. F., & Thaler, R. H. (1985). Does the Stock Market Overreact? Journal of Finance, 40(3), 793-805.
Fama, E. F., & French, K. R. (1988). Permanent and Temporary Components of Stock Prices. Journal of Political Economy, 96(2), 246-273.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Trend Research.
Enhanced HMA 5D standard Deviation - RickSimple hull moving average enhanced with standard deviation bands calculated over a 5 day period to account for volatility in ranging periods.
Possibility to choose the source of the hull calculation, as well as the source to use as threshold for long and short signal.
Two different types of visualization: candle coloring or moving average.
Prime Bands [ChartPrime]The Prime Standard Deviation Bands indicator uses custom-calculated bands based on highest and lowest price values over specific period to analyze price volatility and trend direction. Traders can set the bands to 1, 2, or 3 standard deviations from a central base, providing a dynamic view of price behavior in relation to volatility. The indicator also includes color-coded trend signals, standard deviation labels, and mean reversion signals, offering insights into trend strength and potential reversal points.
⯁ KEY FEATURES AND HOW TO USE
⯌ Standard Deviation Bands :
The indicator plots upper and lower bands based on standard deviation settings (1, 2, or 3 SDs) from a central base, allowing traders to visualize volatility and price extremes. These bands can be used to identify overbought and oversold conditions, as well as potential trend reversals.
Example of 3-standard-deviation bands around price:
⯌ Dynamic Trend Indicator :
The midline of the bands changes color based on trend direction. If the midline is rising, it turns green, indicating an uptrend. When the midline is falling, it turns orange, suggesting a downtrend. This color coding provides a quick visual reference to the current trend.
Trend color examples for rising and falling midlines:
⯌ Standard Deviation Labels :
At the end of the bands, the indicator displays labels with price levels for each standard deviation level (+3, 0, -3, etc.), helping traders quickly reference where price is relative to its statistical boundaries.
Price labels at each standard deviation level on the chart:
⯌ Mean Reversion Signals :
When price moves beyond the upper or lower bands and then reverts back inside, the indicator plots mean reversion signals with diamond icons. These signals indicate potential reversal points where the price may return to the mean after extreme moves.
Example of mean reversion signals near bands:
⯌ Standard Deviation Scale on Chart :
A visual scale on the right side of the chart shows the current price position in relation to the bands, expressed in standard deviations. This scale provides an at-a-glance view of how far price has deviated from the mean, helping traders assess risk and volatility.
⯁ USER INPUTS
Length : Sets the number of bars used in the calculation of the bands.
Standard Deviation Level : Allows selection of 1, 2, or 3 standard deviations for upper and lower bands.
Colors : Customize colors for the uptrend and downtrend midline indicators.
⯁ CONCLUSION
The Prime Standard Deviation Bands indicator provides a comprehensive view of price volatility and trend direction. Its customizable bands, trend coloring, and mean reversion signals allow traders to effectively gauge price behavior, identify extreme conditions, and make informed trading decisions based on statistical boundaries.
Aura Vibes EMA Ribbon + VStop + SAR + Bollinger BandsThe combination of Exponential Moving Averages (EMA), Volatility Stop (VStop), Parabolic SAR (PSAR), and Bollinger Bands (BB) offers a comprehensive approach to technical analysis, each serving a distinct purpose:
Exponential Moving Averages (EMA): EMAs are used to identify the direction of the trend by smoothing price data. Shorter-period EMAs react more quickly to price changes, while longer-period EMAs provide a broader view of the trend.
Volatility Stop (VStop): VStop is a dynamic stop-loss mechanism that adjusts based on market volatility, typically using the Average True Range (ATR). This allows traders to set stop-loss levels that accommodate market fluctuations, potentially reducing the likelihood of premature stop-outs.
Parabolic SAR (PSAR): PSAR is a trend-following indicator that provides potential entry and exit points by plotting dots above or below the price chart. When the dots are below the price, it suggests an uptrend; when above, a downtrend.
Bollinger Bands (BB): BB consists of a middle band (typically a 20-period simple moving average) and two outer bands set at standard deviations above and below the middle band. These bands expand and contract based on market volatility, helping traders identify overbought or oversold conditions.
Integrating these indicators can enhance trading strategies:
Trend Identification: Use EMAs to determine the prevailing market trend. For instance, a short-term EMA crossing above a long-term EMA may signal an uptrend.
Entry and Exit Points: Combine PSAR and BB to pinpoint potential entry and exit points. For example, a PSAR dot appearing below the price during an uptrend, coinciding with the price touching the lower Bollinger Band, might indicate a buying opportunity.
Risk Management: Implement VStop to set adaptive stop-loss levels that adjust with market volatility, providing a buffer against market noise.
By thoughtfully combining these indicators, traders can develop a robust trading system that adapts to various market conditions.
