P T Supertrend CustomPT Supertrend Custom Indicator Description
The PT Supertrend Custom indicator is a dual Supertrend-based tool designed to help traders identify market trends and potential reversals with enhanced accuracy. This custom indicator plots two Supertrend lines with different ATR (Average True Range) lengths and multipliers, providing a broader perspective on price movements across varying market conditions.
Key Features:
1. Dual Supertrend Lines:
- The indicator calculates two separate Supertrend values using customizable ATR lengths (default: 7 and 21) and factors (default: 3.0 for both).
- This dual-layered approach helps identify both short-term and long-term trends for better decision-making.
2. Customizable Parameters:
- ATR Length (ATR Length & ATR Length2): Determines the lookback period for volatility calculation.
- Factor (Factor & Factor2): Defines the multiplier for the ATR, controlling the sensitivity of the Supertrend lines.
3. Visual Trend Representation:
- Green and red line plots represent uptrends and downtrends, respectively.
- The indicator overlays on the price chart, offering a clear visual representation of trend direction.
- Trend fill areas provide additional clarity, with green shading for uptrends and red shading for downtrends.
4. Dynamic Trend Shifts:
- The indicator adapts dynamically based on price action, switching from an uptrend to a downtrend and vice versa when conditions change.
- Two independent trend signals allow traders to compare short-term and long-term trend confirmations.
5. Overlay on Price Chart:
- The indicator is plotted directly on the price chart for easy visualization without cluttering the workspace.
How to Use:
- Trend Identification:
- A green Supertrend line below price indicates an uptrend.
- A red Supertrend line above price signals a downtrend.
- When both Supertrends align, it indicates a strong trend; divergence may signal potential reversals.
- Entry & Exit Signals:
- Consider long positions when both Supertrend lines turn green.
- Consider short positions when both Supertrend lines turn red.
- Use the shorter ATR period for quicker entries and exits, while the longer ATR period provides confirmation.
- Risk Management:
- The Supertrend lines can serve as dynamic support/resistance levels for placing stop-loss orders.
Best Used In:
- Trend-following strategies
- Swing trading and day trading
- Volatile markets where ATR-based signals are effective
This indicator provides a comprehensive view of market trends by combining short- and long-term trend filters, making it a valuable tool for traders seeking precision and clarity in their trading decisions.
Created by Prince Thomas
Average True Range (ATR)
Uptrick: Zero Lag HMA Trend Suite1. Name and Purpose
Uptrick: Zero Lag HMA Trend Suite is a Pine Version 6 script that builds upon the Hull Moving Average (HMA) to offer an advanced trend analysis tool. Its purpose is to help traders identify trend direction, potential reversals, and overall market momentum with reduced lag compared to traditional moving averages. By combining the HMA with Average True Range (ATR) thresholds, slope-dependent coloring, Volume Weighted Average Price (VWAP) ribbons, and optional reversal signals, the script aims to give a detailed view of price activity in various market environments.
2. Overview
This script begins with the calculation of a Hull Moving Average, a method that blends Weighted Moving Averages in a way designed to cut down on lag while still smoothing out price fluctuations. Next, several enhancements are applied. The script compares current HMA values to previous ones for slope-based coloring, which highlights uptrends and downtrends at a glance. It also plots buy and sell signals when price moves beyond or below thresholds determined by the ATR and the user’s chosen signal multiplier. An optional VWAP ribbon can be shown to confirm bullish or bearish conditions relative to a volume-weighted benchmark. Additionally, the script can plot reversal signals (labeled with B) at points where price crosses back toward the HMA from above or below. Taken together, these elements allow traders to visualize both the short-term momentum and the broader context of how price interacts with volatility and overall market direction.
3. Why These Indicators Have Been Linked Together
The reason the Hull Moving Average, the Average True Range, and the VWAP have been integrated into one script is to tackle multiple facets of market analysis in a single tool. The Zero Lag Hull Moving Average provides a responsive trend line, the ATR offers a measure of volatility that helps distinguish significant price shifts from typical fluctuations, and the VWAP acts as a reference for fair value based on traded volume. By layering all three, the script helps traders avoid the need to juggle multiple separate indicators and offers a holistic perspective. The slope-based coloring focuses on trend direction, the ATR-based thresholds refine possible buy and sell zones, and the VWAP ribbons provide insight into how price stands relative to an important volume-weighted level. The inclusion of up and down signals and reversal B labels further refines entries and exits.
4. Why Use Uptrick: Zero Lag HMA Trend Suite
The Hull Moving Average is already known for reacting more quickly to price changes compared to other moving averages while retaining a degree of smoothness. This suite enhances the basic HMA by showing colored gradients that make it easy to spot trend direction changes, highlighting potential entry or exit points based on volatility-driven thresholds, and optionally layering a volume-based measure of bullish or bearish market sentiment. By relying on a zero lag approach and additional data points, the script caters to those wanting a more responsive method of identifying shifts in market dynamics. The added reversal signals and up or down alerts give traders extra confirmation for potential turning points.
5. How This Extension Improves on the Basic HMA
This extension not only plots the Hull Moving Average but also includes data-driven alerts and visual cues that traditional HMA lines do not provide. First, it offers multi-layered slope coloring, making up or down trends quickly apparent. Second, it uses ATR-based thresholds to pinpoint moments when price may be extending beyond normal volatility, thus generating buy or sell signals. Third, the script introduces an optional VWAP ribbon to indicate whether the market is trading above or below this pivotal volume-weighted benchmark, adding a further confirmation step for bullish or bearish conditions. Finally, it incorporates optional reversal signals labeled with B, indicating points where price might swing back toward the main HMA line.
6. Core Components
The script can be broken down into several primary functions and features.
a. Zero Lag HMA Calculation
Uses two Weighted Moving Averages (half-length and full-length) combined through a smoothing step based on the square root of the chosen length. This approach is designed to reduce lag significantly compared to other moving averages.
b. Slope Detection
Compares current and prior HMA values to determine if the trend is up or down. The slope-based coloring changes between turquoise shades for upward movement and magenta shades for downward movement, making trend direction immediately visible.
c. ATR-Based Thresholding for Up and Down Signals
The script calculates an Average True Range over a user-defined period, then multiplies it by a signal factor to form two bands around the HMA. When price crosses below the lower band, an up (buy) signal appears; when it crosses above the upper band, a down (sell) signal is shown.
d. Reversal Signals (B Labels)
Tracks when price transitions back toward the main HMA from an extreme zone. When enabled, these reversal points are labeled with a B and can help traders see potential turning points or mean-reversion setups.
e. VWAP Bands
An optional Volume Weighted Average Price ribbon that plots above or below the HMA, indicating bullish or bearish conditions relative to a volume-weighted price benchmark. This can also act as a kind of support/ resistance.
7. User Inputs
a. HMA Length
Controls how quickly the moving average responds to price changes. Shorter lengths react faster but can lead to more frequent signals, whereas longer lengths produce smoother lines.
b. Source
Specifies the price input, such as close or an alternative source, for the calculation. This can help align the HMA with specific trading strategies.
c. ATR Length and Signal Multiplier
Defines how the script calculates average volatility and sets thresholds for buy or sell alerts. Adjusting these values can help filter out noise or highlight more aggressive signals.
d. Slope Index
Determines how many bars to look back for detecting slope direction, influencing how sensitive the slope coloring is to small fluctuations.
e. Show Buy and Sell Signals, Reversal Signals, and VWAP
Lets users toggle the display of these features. Turning off certain elements can reduce chart clutter if traders prefer a simpler layout.
8. Calculation Process
The script’s calculation follows a step-by-step approach. It first computes two Weighted Moving Averages of the selected price source, one over half the specified length and one over the full length. It then combines these using 2*wma1 minus wma2 to reduce lag, followed by applying another weighted average using the square root of the length. Simultaneously, it computes the ATR for a user-defined period. By multiplying ATR by the signal multiplier, it establishes upper and lower bands around the HMA, where crossovers generate buy (up) or sell (down) signals. The script can also plot reversal signals (B labels) when price crosses back from these bands in the opposite direction. For the optional VWAP feature, Pine Script’s ta.vwap function is used, and differences between the HMA and VWAP levels determine the color and opacity of the ribbon.
9. Signal Generation and Filtering
The ATR-based thresholds reduce the influence of small, inconsequential price swings. When price falls below the lower band, the script issues an up (buy) signal. If price breaks above the upper band, a down (sell) signal appears. These signals are visible through labels placed near the bars. Reversal signals, labeled with B, can be turned on to help detect when price retraces from an extended area back toward the main HMA line. Traders can disable or enable these signals to match their preferred level of chart detail or risk tolerance.
10. Visualization on the Chart
The Zero HMA Lag Trend Suite aims for visual clarity. The HMA line is plotted multiple times with increasing transparency to create a gradient effect. Turquoise gradients indicate upward slopes, and magenta gradients signify downward slopes. Bar coloring can be configured to align with the slope direction, providing quick insight into current momentum. When enabled, buy or sell labels are placed under or above the bars as price crosses the ATR-defined boundaries. If the reversal option is active, B labels appear around areas where price changes direction. The optional VWAP ribbons form background bands, using distinct coloration to signal whether price is above or below the volume-weighted metric.
11. Market Adaptability
Because the script’s parameters (HMA length, ATR length, signal multiplier, and slope index) are user-configurable, it can adapt to a wide range of markets and timeframes. Intraday traders may prefer a shorter HMA length for quick signals, while swing or position traders might use a longer HMA length to filter out short-lived price changes. The source setting can also be adjusted, allowing for specialized data inputs beyond just close or open values.
12. Risk Management Considerations
The script’s signals and labels are based on past price data and volatility readings, and they do not guarantee profitable outcomes. Sharp market reversals or unforeseen fundamental events can produce false signals. Traders should combine this tool with broader risk management strategies, including stop-loss placement, position sizing, and independent market analyses. The Zero HMA Lag Trend Suite can help highlight potential opportunities, but it should not be relied upon as the sole basis for trade decisions.
13. Combining with Other Tools
Many traders choose to verify signals from the Zero HMA Lag Trend Suite using popular indicators like the Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), or even simple volume-based metrics to confirm whether a price movement has sufficient momentum. Conventional techniques such as support and resistance levels, chart patterns, or candlestick analysis can also supplement signals generated by the script’s up, down, or reversal B labels.
14. Parameter Customization and Examples
a. Short-Term Day Trading
Using a shorter HMA length (for instance, 9 or 14) and a slightly higher ATR multiplier might provide timely buy and sell signals, though it may also produce more whipsaws in choppy markets.
b. Swing or Position Trading
Selecting a longer HMA length (such as 50 or 100) with a moderate ATR multiplier can help users track more significant and sustained market moves, potentially reducing the effect of minor fluctuations.
c. Multiple Timeframe Blends
Some traders load two versions of the indicator on the same chart, one for short-term signals (with frequent B label reversals) and another for the broader trend direction, aligning entry and exit decisions with the bigger picture.
15. Realistic Expectations
Even though the Hull Moving Average helps minimize lag and the script incorporates volatility-based filters and optional VWAP overlays, it cannot predict future market behavior with complete accuracy. Periods of low liquidity or sudden market shocks can still lead to signals that do not reflect longer-term trends. Frequent parameter review and manual confirmation are advised before executing trades based solely on the script’s outputs.
16. Theoretical Background
The Hull Moving Average formula aims to balance smoothness with reactivity, accomplished by combining Weighted Moving Averages at varying lengths. By subtracting a slower average from a faster one and then applying another smoothing step with the square root of the original length, the HMA is designed to respond more promptly to price changes than typical exponential or simple moving averages. The ATR component, introduced by J. Welles Wilder, calculates the average range of price movement over a user-defined period, allowing the script to assess volatility and adapt signals accordingly. VWAP provides a volume-weighted benchmark that many institutional traders track to gauge fair intraday value.
17. Originality and Uniqueness
Although multiple HMA-based indicators can be found, Uptrick: Zero Lag HMA Trend Suite sets itself apart by merging slope-based coloring, ATR thresholds, VWAP ribbons, up or down labels, and optional reversal signals all in one cohesive platform. This synergy aims to reduce chart clutter while still giving traders a comprehensive look at trend direction, volatility, and volume-based sentiment.
18. Summary
Uptrick: Zero Lag HMA Trend Suite is a specialized trading script designed to highlight potential market trends and reversals with minimal delay. It leverages the Hull Moving Average for an adaptive yet smooth price line, pairs ATR-based thresholds for detecting possible breakouts or dips, and provides VWAP-based ribbons for added volume-weighted context. Traders can further refine their entries and exits by enabling up or down signals and reversal labels (B) where price may revert toward the HMA. Suitable for a wide range of timeframes and instrument types, the script encourages a disciplined approach to trade management and risk control.
19. Disclaimer
This script is provided for informational and educational purposes only. Trading and investing involve significant financial risk, and no indicator can guarantee success under all conditions. Users should practice robust risk management, including the placement of stop losses and position sizing, and should confirm signals with additional analysis tools. The developer of this script assumes no liability for any trading decisions or outcomes resulting from its use.
Composite Indicator (CCI + ATR)Composite Indicator (CCI + ATR)
The Composite Indicator (CCI + ATR) combines the Commodity Channel Index (CCI) with the Average True Range (ATR) , providing traders with a dynamic tool for identifying entry and exit points based on momentum and volatility. This indicator is particularly useful for markets like cryptocurrencies, which often exhibit sharp sell-offs and gradual upward trends.
Key Features
Momentum Analysis with CCI: The CCI calculates price momentum by comparing the current price level to its average over a specific period. The indicator generates signals when CCI crosses predefined thresholds.
- Buy Signal: Triggered when CCI crosses above the lower threshold (e.g., -100).
- Sell Signal: Triggered when CCI crosses below the upper threshold (e.g., +100).
Volatility Filtering with ATR: The ATR measures market volatility, ensuring signals occur only during significant price movements.
Separate multipliers for buy and sell signals allow tailored filtering based on market behavior.
Stop Loss Calculation: Dynamic stop loss levels are calculated using the ATR multiplier to adapt to market volatility, offering better risk management.
How It Works
CCI Calculation: The CCI is calculated using the typical price ((High + Low + Close) / 3) and a user-defined length. It detects momentum changes by measuring deviations from the average price.
ATR Calculation: The ATR determines the average price range over a specified period, identifying the market’s volatility. The ATR SMA acts as a baseline to filter signals.
Buy Signal: A buy signal is triggered when:
- CCI crosses above the lower threshold (e.g., -100).
- ATR exceeds its SMA multiplied by the buy multiplier (e.g., 1.0).
Sell Signal: A sell signal is triggered when:
- CCI crosses below the upper threshold (e.g., +100).
- ATR exceeds its SMA multiplied by the sell multiplier (e.g., 0.95).
Stop Loss Integration:
- Long positions: Stop loss = Low – (ATR * ATR Multiplier)
- Short positions: Stop loss = High + (ATR * ATR Multiplier)
Advantages
Combines momentum (CCI) and volatility (ATR) for precise signal generation.
Customizable thresholds and multipliers for different market conditions.
Dynamic stop loss ensures better risk management in volatile markets.
Suggested Parameter Settings
CCI Length: 20 (default). Adjust as follows:
- 10–15: Shorter timeframes (e.g., 5-15 minutes).
- 20: General use for 1-hour timeframes.
- 30–50: Longer timeframes (e.g., 4-hour or daily charts).
CCI Threshold: 100 (default). Adjust as follows:
- 50–75: For more frequent signals in ranging markets.
- 100: Balanced for most trading conditions.
- 150–200: For strong trends to reduce noise.
ATR Length: 14 (default). Adjust as follows:
- 10–14: For assets with moderate volatility.
- 20: For assets with lower volatility.
ATR Buy Multiplier: 1.0 (default). Adjust as follows:
- 0.9–1.0: For gradual uptrends in crypto markets.
- 1.1–1.2: For stronger trend filtering.
ATR Sell Multiplier: 0.95 (default). Adjust as follows:
- 0.8–0.95: For sharp sell-offs.
- 1.0–1.1: For stable downward trends.
ATR Multiplier (Stop Loss): 1.5 (default). Adjust as follows:
- 1.0–1.2: For shorter timeframes or less volatile markets.
- 2.0–2.5: For highly volatile markets like cryptocurrencies.
Example Use Cases
Scalping (5-15 minute charts): Use CCI Length = 10, CCI Threshold = 75, ATR Buy Multiplier = 0.9, ATR Sell Multiplier = 0.8.
Day Trading (1-hour charts): Use CCI Length = 20, CCI Threshold = 100, ATR Buy Multiplier = 1.0, ATR Sell Multiplier = 0.95.
Swing Trading (4-hour or daily charts): Use CCI Length = 30, CCI Threshold = 150, ATR Buy Multiplier = 1.2, ATR Sell Multiplier = 1.0.
Final Thoughts The Composite Indicator (CCI + ATR) is a versatile tool designed to enhance trading decisions by combining momentum analysis with volatility filtering. Whether scalping or swing trading, this indicator provides actionable insights and robust risk management to navigate complex markets effectively.
Volume profile [Signals] - By Leviathan [Mindyourbuisness]Market Sessions and Volume Profile with Sweep Signals - Based on Leviathan's Volume Profile
This indicator is an enhanced version of Leviathan's Volume Profile indicator, adding session-based value area analysis and sweep detection signals. It combines volume profile analysis with market structure concepts to identify potential reversal opportunities.
Features
- Session-based volume profiles (Daily, Weekly, Monthly, Quarterly, Yearly)
- Forex sessions support (Tokyo, London, New York)
- Value Area analysis with POC, VAH, and VAL levels
- Extended level visualization for the last completed session
- Sweep detection signals for key value area levels
Sweep Signals Explanation
The indicator detects two types of sweeps at VAH, VAL, and POC levels:
Bearish Sweeps (Red Triangle Down)
Conditions:
- Price makes a high above the level (VAH/VAL/POC)
- Closes below the level
- Closes below the previous candle's low
- Previous candle must be bullish
Trading Implication: Suggests a failed breakout and potential reversal to the downside. These sweeps often indicate stop-loss hunting above key levels followed by institutional selling.
Bullish Sweeps (Green Triangle Up)
Conditions:
- Price makes a low below the level (VAH/VAL/POC)
- Closes above the level
- Closes above the previous candle's high
- Previous candle must be bearish
Trading Implication: Suggests a failed breakdown and potential reversal to the upside. These sweeps often indicate stop-loss hunting below key levels followed by institutional buying.
Trading Guidelines
1. Use sweep signals in conjunction with the overall trend
2. Look for additional confirmation like:
- Volume surge during the sweep
- Price action patterns
- Support/resistance levels
3. Consider the session's volatility and time of day
4. More reliable signals often occur at VAH and VAL levels
5. POC sweeps might indicate stronger reversals due to their significance as fair value levels
Notes
- The indicator works best on higher timeframes (1H and above)
- Sweep signals are more reliable during active market hours
- Consider using multiple timeframe analysis for better confirmation
- Past performance is not indicative of future results
Credits: Original Volume Profile indicator by Leviathan
Sunil BB Blast Heikin Ashi StrategySunil BB Blast Heikin Ashi Strategy
The Sunil BB Blast Heikin Ashi Strategy is a trend-following trading strategy that combines Bollinger Bands with Heikin-Ashi candles for precise market entries and exits. It aims to capitalize on price volatility while ensuring controlled risk through dynamic stop-loss and take-profit levels based on a user-defined Risk-to-Reward Ratio (RRR).
Key Features:
Trading Window:
The strategy operates within a user-defined time window (e.g., from 09:20 to 15:00) to align with market hours or other preferred trading sessions.
Trade Direction:
Users can select between Long Only, Short Only, or Long/Short trade directions, allowing flexibility depending on market conditions.
Bollinger Bands:
Bollinger Bands are used to identify potential breakout or breakdown zones. The strategy enters trades when price breaks through the upper or lower Bollinger Band, indicating a possible trend continuation.
Heikin-Ashi Candles:
Heikin-Ashi candles help smooth price action and filter out market noise. The strategy uses these candles to confirm trend direction and improve entry accuracy.
Risk Management (Risk-to-Reward Ratio):
The strategy automatically adjusts the take-profit (TP) level and stop-loss (SL) based on the selected Risk-to-Reward Ratio (RRR). This ensures that trades are risk-managed effectively.
Automated Alerts and Webhooks:
The strategy includes automated alerts for trade entries and exits. Users can set up JSON webhooks for external execution or trading automation.
Active Position Tracking:
The strategy tracks whether there is an active position (long or short) and only exits when price hits the pre-defined SL or TP levels.
Exit Conditions:
The strategy exits positions when either the take-profit (TP) or stop-loss (SL) levels are hit, ensuring risk management is adhered to.
Default Settings:
Trading Window:
09:20-15:00
This setting confines the strategy to the specified hours, ensuring trading only occurs during active market hours.
Strategy Direction:
Default: Long/Short
This allows for both long and short trades depending on market conditions. You can select "Long Only" or "Short Only" if you prefer to trade in one direction.
Bollinger Band Length (bbLength):
Default: 19
Length of the moving average used to calculate the Bollinger Bands.
Bollinger Band Multiplier (bbMultiplier):
Default: 2.0
Multiplier used to calculate the upper and lower bands. A higher multiplier increases the width of the bands, leading to fewer but more significant trades.
Take Profit Multiplier (tpMultiplier):
Default: 2.0
Multiplier used to determine the take-profit level based on the calculated stop-loss. This ensures that the profit target aligns with the selected Risk-to-Reward Ratio.
Risk-to-Reward Ratio (RRR):
Default: 1.0
The ratio used to calculate the take-profit relative to the stop-loss. A higher RRR means larger profit targets.
Trade Automation (JSON Webhooks):
Allows for integration with external systems for automated execution:
Long Entry JSON: Customizable entry condition for long positions.
Long Exit JSON: Customizable exit condition for long positions.
Short Entry JSON: Customizable entry condition for short positions.
Short Exit JSON: Customizable exit condition for short positions.
Entry Logic:
Long Entry:
The strategy enters a long position when:
The Heikin-Ashi candle shows a bullish trend (green close > open).
The price is above the upper Bollinger Band, signaling a breakout.
The previous candle also closed higher than it opened.
Short Entry:
The strategy enters a short position when:
The Heikin-Ashi candle shows a bearish trend (red close < open).
The price is below the lower Bollinger Band, signaling a breakdown.
The previous candle also closed lower than it opened.
Exit Logic:
Take-Profit (TP):
The take-profit level is calculated as a multiple of the distance between the entry price and the stop-loss level, determined by the selected Risk-to-Reward Ratio (RRR).
Stop-Loss (SL):
The stop-loss is placed at the opposite Bollinger Band level (lower for long positions, upper for short positions).
Exit Trigger:
The strategy exits a trade when either the take-profit or stop-loss level is hit.
Plotting and Visuals:
The Heikin-Ashi candles are displayed on the chart, with green candles for uptrends and red candles for downtrends.
Bollinger Bands (upper, lower, and basis) are plotted for visual reference.
Entry points for long and short trades are marked with green and red labels below and above bars, respectively.
Strategy Alerts:
Alerts are triggered when:
A long entry condition is met.
A short entry condition is met.
A trade exits (either via take-profit or stop-loss).
These alerts can be used to trigger notifications or webhook events for automated trading systems.
Notes:
The strategy is designed for use on intraday charts but can be applied to any timeframe.
It is highly customizable, allowing for tailored risk management and trading windows.
The Sunil BB Blast Heikin Ashi Strategy combines two powerful technical analysis tools (Bollinger Bands and Heikin-Ashi candles) with strong risk management, making it suitable for both beginners and experienced traders.
Feebacks are welcome from the users.
Multi-Timeframe Volatility ATR - [by Oberlunar]This script (for now in beta release) is specifically designed for scalping or traders operating on lower timeframes (if you are in a timeframe of one minute wait one minute to collect statistics). Its primary purpose is to provide detailed insights into market volatility by calculating the ATR (Average True Range) and its percentage changes, allowing traders to quickly identify shifts in market conditions.
The ATR is calculated across six user-defined timeframes, which can include very short intervals such as 5 or 15 seconds. This setup enables real-time monitoring of volatility, which is critical for scalping strategies. The script collects a rolling history of the last five ATR values for each timeframe. These historical values are used to calculate percentage changes by comparing the current ATR with the oldest value in the history, offering a clear view of how volatility is evolving over time.
Percentage changes are displayed dynamically in a table, with color-coded feedback to indicate the direction of the change: green for increases, red for decreases, and gray for stability or insufficient data. This visual representation makes it easy to spot whether market volatility is rising or falling at a glance.
By progressively collecting data, the script becomes increasingly effective as more ATR values are accumulated. This functionality is especially useful for traders on lower timeframes, where rapid changes in volatility can signal breakout opportunities or shifts in market dynamics.
Soon I will update personalized ATR parameters, and lookback strategies for statistics.
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.
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.
AI InfinityAI Infinity – Multidimensional Market Analysis
Overview
The AI Infinity indicator combines multiple analysis tools into a single solution. Alongside dynamic candle coloring based on MACD and Stochastic signals, it features Alligator lines, several RSI lines (including glow effects), and optionally enabled EMAs (20/50, 100, and 200). Every module is individually configurable, allowing traders to tailor the indicator to their personal style and strategy.
Important Note (Disclaimer)
This indicator is provided for educational and informational purposes only.
It does not constitute financial or investment advice and offers no guarantee of profit.
Each trader is responsible for their own trading decisions.
Past performance does not guarantee future results.
Please review the settings thoroughly and adjust them to your personal risk profile; consider supplementary analyses or professional guidance where appropriate.
Functionality & Components
1. Candle Coloring (MACD & Stochastic)
Objective: Provide an immediate visual snapshot of the market’s condition.
Details:
MACD Signal: Used to identify bullish and bearish momentum.
Stochastic: Detects overbought and oversold zones.
Color Modes: Offers both a simple (two-color) mode and a gradient mode.
2. Alligator Lines
Objective: Assist with trend analysis and determining the market’s current phase.
Details:
Dynamic SMMA Lines (Jaw, Teeth, Lips) that adjust based on volatility and market conditions.
Multiple Lengths: Each element uses a separate smoothing period (13, 8, 5).
Transparency: You can show or hide each line independently.
3. RSI Lines & Glow Effects
Objective: Display the RSI values directly on the price chart so critical levels (e.g., 20, 50, 80) remain visible at a glance.
Details:
RSI Scaling: The RSI is plotted in the chart window, eliminating the need to switch panels.
Dynamic Transparency: A pulse effect indicates when the RSI is near critical thresholds.
Glow Mode: Choose between “Direct Glow” or “Dynamic Transparency” (based on ATR distance).
Custom RSI Length: Freely adjustable (default is 14).
4. Optional EMAs (20/50, 100, 200)
Objective: Utilize moving averages for trend assessment and identifying potential support/resistance areas.
Details:
20/50 EMA: Select which one to display via a dropdown menu.
100 EMA & 200 EMA: Independently enabled.
Color Logic: Automatically green (price > EMA) or red (price < EMA). Each EMA’s up/down color is customizable.
Configuration Options
Candle Coloring:
Choose between Gradient or Simple mode.
Adjust the color scheme for bullish/bearish candles.
Transparency is dynamically based on candle body size and Stochastic state.
Alligator Lines:
Toggle each line (Jaw/Teeth/Lips) on or off.
Select individual colors for each line.
RSI Section:
RSI Length can be set as desired.
RSI lines (0, 20, 50, 80, 100) with user-defined colors and transparency (pulse effect).
Additional lines (e.g., RSI 40/60) are also available.
Glow Effects:
Switch between “Dynamic Transparency” (ATR-based) and “Direct Glow”.
Independently applied to the RSI 100 and RSI 0 lines.
EMAs (20/50, 100, 200):
Activate each one as needed.
Each EMA’s up/down color can be customized.
Example Use Cases
Trend Identification:
Enable Alligator lines to gauge general trend direction through SMMA signals.
Timing:
Watch the Candle Colors to spot potential overbought or oversold conditions.
Fine-Tuning:
Utilize the RSI lines to closely monitor important thresholds (50 as a trend barometer, 80/20 as possible reversal zones).
Filtering:
Enable a 50 EMA to quickly see if the market is trading above (bullish) or below (bearish) it.
Uptrick: Volatility Reversion BandsUptrick: Volatility Reversion Bands is an indicator designed to help traders identify potential reversal points in the market by combining volatility and momentum analysis within one comprehensive framework. It calculates dynamic bands around a simple moving average and issues signals when price interacts with these bands. Below is a fully expanded description, structured in multiple sections, detailing originality, usefulness, uniqueness, and the purpose behind blending standard deviation-based and ATR-based concepts. All references to code have been removed to focus on the written explanation only.
Section 1: Overview
Uptrick: Volatility Reversion Bands centers on a moving average around which various bands are constructed. These bands respond to changes in price volatility and can help gauge potential overbought or oversold conditions. Signals occur when the price moves beyond certain thresholds, which may imply a reversal or significant momentum shift.
Section 2: Originality, Usefulness, Uniqness, Purpose
This indicator merges two distinct volatility measurements—Bollinger Bands and ATR—into one cohesive system. Bollinger Bands use standard deviation around a moving average, offering a baseline for what is statistically “normal” price movement relative to a recent mean. When price hovers near the upper band, it may indicate overbought conditions, whereas price near the lower band suggests oversold conditions. This straightforward construction often proves invaluable in moderate-volatility settings, as it pinpoints likely turning points and gauges a market’s typical trading range.
Yet Bollinger Bands alone can falter in conditions marked by abrupt volatility spikes or sudden gaps that deviate from recent norms. Intraday news, earnings releases, or macroeconomic data can alter market behavior so swiftly that standard-deviation bands do not keep pace. This is where ATR (Average True Range) adds an important layer. ATR tracks recent highs, lows, and potential gaps to produce a dynamic gauge of how much price is truly moving from bar to bar. In quieter times, ATR contracts, reflecting subdued market activity. In fast-moving markets, ATR expands, exposing heightened volatility on each new bar.
By overlaying Bollinger Bands and ATR-based calculations, the indicator achieves a broader situational awareness. Bollinger Bands excel at highlighting relative overbought or oversold areas tied to an established average. ATR simultaneously scales up or down based on real-time market swings, signaling whether conditions are calm or turbulent. When combined, this means a price that barely crosses the Bollinger Band but also triggers a high ATR-based threshold is likely experiencing a volatility surge that goes beyond typical market fluctuations. Conversely, a price breach of a Bollinger Band when ATR remains low may still warrant attention, but not necessarily the same urgency as in a high-volatility regime.
The resulting synergy offers balanced, context-rich signals. In a strong trend, the ATR layer helps confirm whether an apparent price breakout really has momentum or if it is just a temporary spike. In a range-bound market, standard deviation-based Bollinger Bands define normal price extremes, while ATR-based extensions highlight whether a breakout attempt has genuine force behind it. Traders gain clarity on when a move is both statistically unusual and accompanied by real volatility expansion, thus carrying a higher probability of a directional follow-through or eventual reversion.
Practical advantages emerge across timeframes. Scalpers in fast-paced markets appreciate how ATR-based thresholds update rapidly, revealing if a sudden price push is routine or exceptional. Swing traders can rely on both indicators to filter out false signals in stable conditions or identify truly notable moves. By calibrating to changes in volatility, the merged system adapts naturally whether the market is trending, ranging, or transitioning between these phases.
In summary, combining Bollinger Bands (for a static sense of standard-deviation-based overbought/oversold zones) with ATR (for a dynamic read on current volatility) yields an adaptive, intuitive indicator. Traders can better distinguish fleeting noise from meaningful expansions, enabling more informed entries, exits, and risk management. Instead of relying on a single yardstick for all market conditions, this fusion provides a layered perspective, encouraging traders to interpret price moves in the broader context of changing volatility.
Section 3: Why Bollinger Bands and ATR are combined
Bollinger Bands provide a static snapshot of volatility by computing a standard deviation range above and below a central average. ATR, on the other hand, adapts in real time to expansions or contractions in market volatility. When combined, these measures offset each other’s limitations: Bollinger Bands add structure (overbought and oversold references), and ATR ensures responsiveness to rapid price shifts. This synergy helps reduce noisy signals, particularly during sudden market turbulence or extended consolidations.
Section 4: User Inputs
Traders can adjust several parameters to suit their preferences and strategies. These typically include:
1. Lookback length for calculating the moving average and standard deviation.
2. Multipliers to control the width of Bollinger Bands.
3. An ATR multiplier to set the distance for additional reversal bands.
4. An option to display weaker signals when the price merely approaches but does not cross the outer bands.
Section 5: Main Calculations
At the core of this indicator are four important steps:
1. Calculate a basis using a simple moving average.
2. Derive Bollinger Bands by adding and subtracting a product of the standard deviation and a user-defined multiplier.
3. Compute ATR over the same lookback period and multiply it by the selected factor.
4. Combine ATR-based distance with the Bollinger Bands to set the outer reversal bands, which serve as stronger signal thresholds.
Section 6: Signal Generation
The script interprets meaningful reversal points when the price:
1. Crosses below the lower outer band, potentially highlighting oversold conditions where a bullish reversal may occur.
2. Crosses above the upper outer band, potentially indicating overbought conditions where a bearish reversal may develop.
Section 7: Visualization
The indicator provides visual clarity through labeled signals and color-coded references:
1. Distinct colors for upper and lower reversal bands.
2. Markers that appear above or below bars to denote possible buying or selling signals.
3. A gradient bar color scheme indicating a bar’s position between the lower and upper bands, helping traders quickly see if the price is near either extreme.
Section 8: Weak Signals (Optional)
For those preferring early cues, the script can highlight areas where the price nears the outer bands. When weak signals are enabled:
1. Bars closer to the upper reversal zone receive a subtle marker suggesting a less robust, yet still noteworthy, potential selling area.
2. Bars closer to the lower reversal zone receive a subtle marker suggesting a less robust, yet still noteworthy, potential buying area.
Section 9: Simplicity, Effectiveness, and Lower Timeframes
Although combining standard deviation and ATR involves sophisticated volatility concepts, this indicator is visually straightforward. Reversal bands and gradient-colored bars make it easy to see at a glance when price approaches or crosses a threshold. Day traders operating on lower timeframes benefit from such clarity because it helps filter out minor fluctuations and focus on more meaningful signals.
Section 10: Adaptability across Market Phases
Because both the standard deviation (for Bollinger Bands) and ATR adapt to changing volatility, the indicator naturally adjusts to various environments:
1. Trending: The additional ATR-based outer bands help distinguish between temporary pullbacks and deeper reversals.
2. Ranging: Bollinger Bands often remain narrower, identifying smaller reversals, while the outer ATR bands remain relatively close to the main bands.
Section 11: Reduced Noise in High-Volatility Scenarios
By factoring ATR into the band calculations, the script widens or narrows the thresholds during rapid market fluctuations. This reduces the amount of false triggers typically found in indicators that rely solely on fixed calculations, preventing overreactions to abrupt but short-lived price spikes.
Section 12: Incorporation with Other Technical Tools
Many traders combine this indicator with oscillators such as RSI, MACD, or Stochastic, as well as volume metrics. Overbought or oversold signals in momentum oscillators can provide additional confirmation when price reaches the outer bands, while volume spikes may reinforce the significance of a breakout or potential reversal.
Section 13: Risk Management Considerations
All trading strategies carry risk. This indicator, like any tool, can and does produce losing trades if price unexpectedly reverses again or if broader market conditions shift rapidly. Prudent traders employ protective measures:
1. Stop-loss orders or trailing stops.
2. Position sizing that accounts for market volatility.
3. Diversification across different asset classes when possible.
Section 14: Overbought and Oversold Identification
Standard Bollinger Bands highlight regions where price might be overextended relative to its recent average. The extended ATR-based reversal bands serve as secondary lines of defense, identifying moments when price truly stretches beyond typical volatility bounds.
Section 15: Parameter Customization for Different Needs
Users can tailor the script to their unique preferences:
1. Shorter lookback settings yield faster signals but risk more noise.
2. Higher multipliers spread the bands further apart, filtering out small moves but generating fewer signals.
3. Longer lookback periods smooth out market noise, often leading to more stable but less frequent trading cues.
Section 16: Examples of Different Trading Styles
1. Day Traders: Often reduce the length to capture quick price swings.
2. Swing Traders: May use moderate lengths such as 20 to 50 bars.
3. Position Traders: Might opt for significantly longer settings to detect macro-level reversals.
Section 17: Performance Limitations and Reality Check
No technical indicator is free from false signals. Sudden fundamental news events, extreme sentiment changes, or low-liquidity conditions can render signals less reliable. Backtesting and forward-testing remain essential steps to gauge whether the indicator aligns well with a trader’s timeframe, risk tolerance, and instrument of choice.
Section 18: Merging Volatility and Momentum
A critical uniqueness of this indicator lies in how it merges Bollinger Bands (standard deviation-based) with ATR (pure volatility measure). Bollinger Bands provide a relative measure of price extremes, while ATR dynamically reacts to market expansions and contractions. Together, they offer an enhanced perspective on potential market turns, ideally reducing random noise and highlighting moments where price has traveled beyond typical bounds.
Section 19: Purpose of this Merger
The fundamental purpose behind blending standard deviation measures with real-time volatility data is to accommodate different market behaviors. Static standard deviation alone can underreact or overreact in abnormally volatile conditions. ATR alone lacks a baseline reference to normality. By merging them, the indicator aims to provide:
1. A versatile dynamic range for both typical and extreme moves.
2. A filter against frequent whipsaws, especially in choppy environments.
3. A visual framework that novices and experts can interpret rapidly.
Section 20: Summary and Practical Tips
Uptrick: Volatility Reversion Bands offers a powerful tool for traders looking to combine volatility-based signals with momentum-derived reversals. It emphasizes clarity through color-coded bars, defined reversal zones, and optional weak signal markers. While potentially useful across all major timeframes, it demands ongoing risk management, realistic expectations, and careful study of how signals behave under different market conditions. No indicator serves as a crystal ball, so integrating this script into an overall strategy—possibly alongside volume data, fundamentals, or momentum oscillators—often yields the best results.
Disclaimer and Educational Use
This script is intended for educational and informational purposes. It does not constitute financial advice, nor does it guarantee trading success. Sudden economic events, low-liquidity times, and unexpected market behaviors can all undermine technical signals. Traders should use proper testing procedures (backtesting and forward-testing) and maintain disciplined risk management measures.
Volatility Cycle IndicatorThe Volatility Cycle Indicator is a non-directional trading tool designed to measure market volatility and cycles based on the relationship between standard deviation and Average True Range (ATR). In the Chart GBPAUD 1H time frame you can clearly see when volatility is low, market is ranging and when volatility is high market is expanding.
This innovative approach normalizes the standard deviation of closing prices by ATR, providing a dynamic perspective on volatility. By analyzing the interaction between Bollinger Bands and Keltner Channels, it also detects "squeeze" conditions, highlighting periods of reduced volatility, often preceding explosive price movements.
The indicator further features visual aids, including colored zones, plotted volatility cycles, and highlighted horizontal levels to interpret market conditions effectively. Alerts for key events, such as volatility crossing significant thresholds or entering a squeeze, make it an ideal tool for proactive trading.
Key Features:
Volatility Measurement:
Tracks the Volatility Cycle, normalized using standard deviation and ATR.
Helps identify periods of high and low volatility in the market.
Volatility Zones:
Colored zones represent varying levels of market volatility:
Blue Zone: Low volatility (0.5–0.75).
Orange Zone: Transition phase (0.75–1.0).
Green Zone: Moderate volatility (1.0–1.5).
Fuchsia Zone: High volatility (1.5–2.0).
Red Zone: Extreme volatility (>2.0).
Squeeze Detection:
Identifies when Bollinger Bands contract within Keltner Channels, signaling a volatility squeeze.
Alerts are triggered for potential breakout opportunities.
Visual Enhancements:
Dynamic coloring of the Volatility Cycle for clarity on its momentum and direction.
Plots multiple horizontal levels for actionable insights into market conditions.
Alerts:
Sends alerts when the Volatility Cycle crosses significant levels (e.g., 0.75) or when a squeeze condition is detected.
Non-Directional Nature:
The indicator does not predict the market's direction but rather highlights periods of potential movement, making it suitable for both trend-following and mean-reversion strategies.
How to Trade with This Indicator:
Volatility Squeeze Breakout:
When the indicator identifies a squeeze (volatility compression), prepare for a breakout in either direction.
Use additional directional indicators or chart patterns to determine the likely breakout direction.
Crossing Volatility Levels:
Pay attention to when the Volatility Cycle crosses the 0.75 level:
Crossing above 0.75 indicates increasing volatility—ideal for trend-following strategies.
Crossing below 0.75 signals decreasing volatility—consider mean-reversion strategies.
Volatility Zones:
Enter positions as volatility transitions through key zones:
Low volatility (Blue Zone): Watch for breakout setups.
Extreme volatility (Red Zone): Be cautious of overextended moves or reversals.
Alerts for Proactive Trading:
Configure alerts for squeeze conditions and level crossings to stay updated without constant monitoring.
Best Practices:
Pair the Volatility Cycle Indicator with directional indicators such as moving averages, trendlines, or momentum oscillators to improve trade accuracy.
Use on multiple timeframes to align entries with broader market trends.
Combine with risk management techniques, such as ATR-based stop losses, to handle volatility spikes effectively.
ATR ReadoutDisplays a readout on the bottom right corner of the screen displaying ATR average (not of the individual candlestick, but of the current rolling period, including the candlestick in question).
Due to restrictions with Pine Script (or my knowledge thereof) only the current and previous candlestick data is shown, rather than the one currently hovered over.
The data is derived via the standard calculation for ATR.
Using this, one can quickly and easily get the proper data needed to calculate one's stop loss, rather than having to analyze the line graph of the basic ATR indicator.
Settings are implemented to change certain variables to your liking.
Kernel Regression Envelope with SMI OscillatorThis script combines the predictive capabilities of the **Nadaraya-Watson estimator**, implemented by the esteemed jdehorty (credit to him for his excellent work on the `KernelFunctions` library and the original Nadaraya-Watson Envelope indicator), with the confirmation strength of the **Stochastic Momentum Index (SMI)** to create a dynamic trend reversal strategy. The core idea is to identify potential overbought and oversold conditions using the Nadaraya-Watson Envelope and then confirm these signals with the SMI before entering a trade.
**Understanding the Nadaraya-Watson Envelope:**
The Nadaraya-Watson estimator is a non-parametric regression technique that essentially calculates a weighted average of past price data to estimate the current underlying trend. Unlike simple moving averages that give equal weight to all past data within a defined period, the Nadaraya-Watson estimator uses a **kernel function** (in this case, the Rational Quadratic Kernel) to assign weights. The key parameters influencing this estimation are:
* **Lookback Window (h):** This determines how many historical bars are considered for the estimation. A larger window results in a smoother estimation, while a smaller window makes it more reactive to recent price changes.
* **Relative Weighting (alpha):** This parameter controls the influence of different time frames in the estimation. Lower values emphasize longer-term price action, while higher values make the estimator more sensitive to shorter-term movements.
* **Start Regression at Bar (x\_0):** This allows you to exclude the potentially volatile initial bars of a chart from the calculation, leading to a more stable estimation.
The script calculates the Nadaraya-Watson estimation for the closing price (`yhat_close`), as well as the highs (`yhat_high`) and lows (`yhat_low`). The `yhat_close` is then used as the central trend line.
**Dynamic Envelope Bands with ATR:**
To identify potential entry and exit points around the Nadaraya-Watson estimation, the script uses **Average True Range (ATR)** to create dynamic envelope bands. ATR measures the volatility of the price. By multiplying the ATR by different factors (`nearFactor` and `farFactor`), we create multiple bands:
* **Near Bands:** These are closer to the Nadaraya-Watson estimation and are intended to identify potential immediate overbought or oversold zones.
* **Far Bands:** These are further away and can act as potential take-profit or stop-loss levels, representing more extreme price extensions.
The script calculates both near and far upper and lower bands, as well as an average between the near and far bands. This provides a nuanced view of potential support and resistance levels around the estimated trend.
**Confirming Reversals with the Stochastic Momentum Index (SMI):**
While the Nadaraya-Watson Envelope identifies potential overextended conditions, the **Stochastic Momentum Index (SMI)** is used to confirm a potential trend reversal. The SMI, unlike a traditional stochastic oscillator, oscillates around a zero line. It measures the location of the current closing price relative to the median of the high/low range over a specified period.
The script calculates the SMI on a **higher timeframe** (defined by the "Timeframe" input) to gain a broader perspective on the market momentum. This helps to filter out potential whipsaws and false signals that might occur on the current chart's timeframe. The SMI calculation involves:
* **%K Length:** The lookback period for calculating the highest high and lowest low.
* **%D Length:** The period for smoothing the relative range.
* **EMA Length:** The period for smoothing the SMI itself.
The script uses a double EMA for smoothing within the SMI calculation for added smoothness.
**How the Indicators Work Together in the Strategy:**
The strategy enters a long position when:
1. The closing price crosses below the **near lower band** of the Nadaraya-Watson Envelope, suggesting a potential oversold condition.
2. The SMI crosses above its EMA, indicating positive momentum.
3. The SMI value is below -50, further supporting the oversold idea on the higher timeframe.
Conversely, the strategy enters a short position when:
1. The closing price crosses above the **near upper band** of the Nadaraya-Watson Envelope, suggesting a potential overbought condition.
2. The SMI crosses below its EMA, indicating negative momentum.
3. The SMI value is above 50, further supporting the overbought idea on the higher timeframe.
Trades are closed when the price crosses the **far band** in the opposite direction of the trade. A stop-loss is also implemented based on a fixed value.
**In essence:** The Nadaraya-Watson Envelope identifies areas where the price might be deviating significantly from its estimated trend. The SMI, calculated on a higher timeframe, then acts as a confirmation signal, suggesting that the momentum is shifting in the direction of a potential reversal. The ATR-based bands provide dynamic entry and exit points based on the current volatility.
**How to Use the Script:**
1. **Apply the script to your chart.**
2. **Adjust the "Kernel Settings":**
* **Lookback Window (h):** Experiment with different values to find the smoothness that best suits the asset and timeframe you are trading. Lower values make the envelope more reactive, while higher values make it smoother.
* **Relative Weighting (alpha):** Adjust to control the influence of different timeframes on the Nadaraya-Watson estimation.
* **Start Regression at Bar (x\_0):** Increase this value if you want to exclude the initial, potentially volatile, bars from the calculation.
* **Stoploss:** Set your desired stop-loss value.
3. **Adjust the "SMI" settings:**
* **%K Length, %D Length, EMA Length:** These parameters control the sensitivity and smoothness of the SMI. Experiment to find settings that work well for your trading style.
* **Timeframe:** Select the higher timeframe you want to use for SMI confirmation.
4. **Adjust the "ATR Length" and "Near/Far ATR Factor":** These settings control the width and sensitivity of the envelope bands. Smaller ATR lengths make the bands more reactive to recent volatility.
5. **Customize the "Color Settings"** to your preference.
6. **Observe the plots:**
* The **Nadaraya-Watson Estimation (yhat)** line represents the estimated underlying trend.
* The **near and far upper and lower bands** visualize potential overbought and oversold zones based on the ATR.
* The **fill areas** highlight the regions between the near and far bands.
7. **Look for entry signals:** A long entry is considered when the price touches or crosses below the lower near band and the SMI confirms upward momentum. A short entry is considered when the price touches or crosses above the upper near band and the SMI confirms downward momentum.
8. **Manage your trades:** The script provides exit signals when the price crosses the far band. The fixed stop-loss will also close trades if the price moves against your position.
**Justification for Combining Nadaraya-Watson Envelope and SMI:**
The combination of the Nadaraya-Watson Envelope and the SMI provides a more robust approach to identifying potential trend reversals compared to using either indicator in isolation. The Nadaraya-Watson Envelope excels at identifying potential areas where the price is overextended relative to its recent history. However, relying solely on the envelope can lead to false signals, especially in choppy or volatile markets. By incorporating the SMI as a confirmation tool, we add a momentum filter that helps to validate the potential reversals signaled by the envelope. The higher timeframe SMI further helps to filter out noise and focus on more significant shifts in momentum. The ATR-based bands add a dynamic element to the entry and exit points, adapting to the current market volatility. This mashup aims to leverage the strengths of each indicator to create a more reliable trading strategy.
Breadth of Volatility The Breadth of Volatility (BoV) is an indicator designed to help traders understand the activity and volatility of the market. It focuses on analyzing how fast prices are moving and how much trading volume is driving those movements. By combining these two factors—price speed and volume strength—the BoV provides a single value that reflects the current level of market activity. This can help traders identify when the market is particularly active or calm, which is useful for planning trading strategies.
The speed component of the BoV measures how quickly prices are moving compared to their recent average. This is done by using a metric called the Average True Range (ATR), which calculates the typical size of price movements over a specific period. The BoV compares the current price change to this average, showing whether the market is moving faster or slower than usual. Faster price movements generally indicate higher volatility, which might signal opportunities for active traders.
The strength component focuses on the role of trading volume in price changes. It multiplies the trading volume by the size of the price movement to create a value called volume strength. This value is then compared to the highest volume strength seen over a recent period, which helps gauge whether the current price action is being strongly supported by trading activity. When the strength value is high, it suggests that market participants are actively trading and supporting the price movement.
These two components—speed and strength—are averaged to calculate the Breadth of Volatility value. While the formula also includes a placeholder for a third component (related to fundamental analysis), it is currently inactive and does not influence the final value. The BoV is displayed as a line on a chart, with a zero line for reference. Positive BoV values indicate heightened market activity and volatility, while values near zero suggest a quieter market. This indicator is particularly helpful for new traders to monitor market conditions and adjust their strategies accordingly, whether they’re focusing on trend-following or waiting for calmer periods for more conservative trades.
Important Notice:
Trading financial markets involves significant risk and may not be suitable for all investors. The use of technical indicators like this one does not guarantee profitable results. This indicator should not be used as a standalone analysis tool. It is essential to combine it with other forms of analysis, such as fundamental analysis, risk management strategies, and awareness of current market conditions. Always conduct thorough research or consult with a qualified financial advisor before making trading decisions. Past performance is not indicative of future results.
Disclaimer:
Trading financial instruments involves substantial risk and may not be suitable for all investors. Past performance is not indicative of future results. This indicator is provided for informational and educational purposes only and should not be considered investment advice. Always conduct your own research and consult with a licensed financial professional before making any trading decisions.
Note: The effectiveness of any technical indicator can vary based on market conditions and individual trading styles. It's crucial to test indicators thoroughly using historical data and possibly paper trading before applying them in live trading scenarios.
DAILY Supertrend + EMA Crossover with RSI FilterThis strategy is a technical trading approach that combines multiple indicators—Supertrend, Exponential Moving Averages (EMAs), and the Relative Strength Index (RSI)—to identify and manage trades.
Core Components:
1. Exponential Moving Averages (EMAs):
Two EMAs, one with a shorter period (fast) and one with a longer period (slow), are calculated. The idea is to spot when the faster EMA crosses above or below the slower EMA. A fast EMA crossing above the slow EMA often suggests upward momentum, while crossing below suggests downward momentum.
2. Supertrend Indicator:
The Supertrend uses Average True Range (ATR) to establish dynamic support and resistance lines. These lines shift above or below price depending on the prevailing trend. When price is above the Supertrend line, the trend is considered bullish; when below, it’s considered bearish. This helps ensure that the strategy trades only in the direction of the overall trend rather than against it.
3. RSI Filter:
The RSI measures momentum. It helps avoid buying into markets that are already overbought or selling into markets that are oversold. For example, when going long (buying), the strategy only proceeds if the RSI is not too high, and when going short (selling), it only proceeds if the RSI is not too low. This filter is meant to improve the quality of the trades by reducing the chance of entering right before a reversal.
4. Time Filters:
The strategy only triggers entries during user-specified date and time ranges. This is useful if one wants to limit trading activity to certain trading sessions or periods with higher market liquidity.
5. Risk Management via ATR-based Stops and Targets:
Both stop loss and take profit levels are set as multiples of the ATR. ATR measures volatility, so when volatility is higher, both stops and profit targets adjust to give the trade more breathing room. Conversely, when volatility is low, stops and targets tighten. This dynamic approach helps maintain consistent risk management regardless of market conditions.
Overall Logic Flow:
- First, the market conditions are analyzed through EMAs, Supertrend, and RSI.
- When a buy (long) condition is met—meaning the fast EMA crosses above the slow EMA, the trend is bullish according to Supertrend, and RSI is below the specified “overbought” threshold—the strategy initiates or adds to a long position.
- Similarly, when a sell (short) condition is met—meaning the fast EMA crosses below the slow EMA, the trend is bearish, and RSI is above the specified “oversold” threshold—it initiates or adds to a short position.
- Each position is protected by an automatically calculated stop loss and a take profit level based on ATR multiples.
Intended Result:
By blending trend detection, momentum filtering, and volatility-adjusted risk management, the strategy aims to capture moves in the primary trend direction while avoiding entries at excessively stretched prices. Allowing multiple entries can potentially amplify gains in strong trends but also increases exposure, which traders should consider in their risk management approach.
In essence, this strategy tries to ride established trends as indicated by the Supertrend and EMAs, filter out poor-quality entries using RSI, and dynamically manage trade risk through ATR-based stops and targets.
ATR for Aggregated Bars (2 Bars)Range Bar ATR Indicator: Detailed Description and Usage Guide
This script is a custom indicator designed specifically for Range Bar charts , tailored to help traders understand and navigate market conditions by utilizing the Average True Range (ATR) concept. The indicator adapts the traditional ATR to work effectively with Range Bar charts, where bars have a fixed range rather than being time-based.
How It Works
1. ATR Calculation on Range Bars :
- Unlike time-based charts, Range Bar charts focus on price movement within a fixed range.
- The indicator calculates ATR by pairing consecutive bars, treating every two bars as a single unit . This pairing ensures that the ATR reflects price movement effectively on Range Bar charts.
2. Short and Long Period ATR Values :
- The script displays two ATR values :
- A short-period ATR , calculated over a smaller number of paired bars.
- A long-period ATR , calculated over a larger number of paired bars.
- These values provide a dynamic view of both recent and longer-term market volatility.
Why Use This Indicator?
The primary goal is to provide a meaningful adaptation of the ATR indicator for Range Bar charts, allowing traders to make informed decisions similar to using ATR on traditional time-based charts.
Key Applications
Determine a Better Custom Range :
- Analyze the ATR values to choose an optimal range size for Range Bar charts, ensuring better alignment with market conditions.
Assess Market Volatility :
- Rising volatility : When the short-period ATR value is higher than the long-period value, it signals increasing volatility.
- Decreasing volatility : When the short-period ATR value is lower, it indicates declining volatility.
Risk and Stop Loss Management :
- Use the higher ATR value (e.g., the long-period ATR) to calculate minimum stop loss levels. Multiply the ATR by 1.5 or 2 to set a safe buffer against market fluctuations.
How to Use It
1. Add the script to a Range Bar chart.
2. Configure the short and long ATR periods to suit your trading style and preferences.
3. Observe the displayed ATR values:
- Use these values to analyze market conditions and adapt your strategy accordingly.
4. Apply insights from the ATR values for:
- Determining custom Range Bar settings.
- Evaluating volatility trends.
- Setting effective risk parameters like stop loss levels.
Benefits
- Provides a tailored ATR tool for Range Bar charts, addressing the unique challenges of fixed-range trading.
- Offers both short-term and long-term perspectives on volatility.
- Enhances decision-making for range settings, volatility analysis, and risk management.
This indicator bridges the gap between traditional ATR indicators and the specific needs of Range Bar chart users, making it a versatile tool for traders.
Prediction Based on Linreg & Atr
We created this algorithm with the goal of predicting future prices 📊, specifically where the value of any asset will go in the next 20 periods ⏳. It uses linear regression based on past prices, calculating a slope and an intercept to forecast future behavior 🔮. This prediction is then adjusted according to market volatility, measured by the ATR 📉, and the direction of trend signals, which are based on the MACD and moving averages 📈.
How Does the Linreg & ATR Prediction Work?
1. Trend Calculation and Signals:
o Technical Indicators: We use short- and long-term exponential moving averages (EMA), RSI, MACD, and Bollinger Bands 📊 to assess market direction and sentiment (not visually presented in the script).
o Calculation Functions: These include functions to calculate slope, average, intercept, standard deviation, and Pearson's R, which are crucial for regression analysis 📉.
2. Predicting Future Prices:
o Linear Regression: The algorithm calculates the slope, average, and intercept of past prices to create a regression channel 📈, helping to predict the range of future prices 🔮.
o Standard Deviation and Pearson's R: These metrics determine the strength of the regression 🔍.
3. Adjusting the Prediction:
o The predicted value is adjusted by considering market volatility (ATR 📉) and the direction of trend signals 🔮, ensuring that the prediction is aligned with the current market environment 🌍.
4. Visualization:
o Prediction Lines and Bands: The algorithm plots lines that display the predicted future price along with a prediction range (upper and lower bounds) 📉📈.
5. EMA Cross Signals:
o EMA Conditions and Total Score: A bullish crossover signal is generated when the total score is positive and the short EMA crosses above the long EMA 📈. A bearish crossover signal is generated when the total score is negative and the short EMA crosses below the long EMA 📉.
6. Additional Considerations:
o Multi-Timeframe Regression Channel: The script calculates regression channels for different timeframes (5m, 15m, 30m, 4h) ⏳, helping determine the overall market direction 📊 (not visually presented).
Confidence Interpretation:
• High Confidence (close to 100%): Indicates strong alignment between timeframes with a clear trend (bullish or bearish) 🔥.
• Low Confidence (close to 0%): Shows disagreement or weak signals between timeframes ⚠️.
Confidence complements the interpretation of the prediction range and expected direction 🔮, aiding in decision-making for market entry or exit 🚀.
Español
Creamos este algoritmo con el objetivo de predecir los precios futuros 📊, específicamente hacia dónde irá el valor de cualquier activo en los próximos 20 períodos ⏳. Utiliza regresión lineal basada en los precios pasados, calculando una pendiente y una intersección para prever el comportamiento futuro 🔮. Esta predicción se ajusta según la volatilidad del mercado, medida por el ATR 📉, y la dirección de las señales de tendencia, que se basan en el MACD y las medias móviles 📈.
¿Cómo Funciona la Predicción con Linreg & ATR?
Cálculo de Tendencias y Señales:
Indicadores Técnicos: Usamos medias móviles exponenciales (EMA) a corto y largo plazo, RSI, MACD y Bandas de Bollinger 📊 para evaluar la dirección y el sentimiento del mercado (no presentados visualmente en el script).
Funciones de Cálculo: Incluye funciones para calcular pendiente, media, intersección, desviación estándar y el coeficiente de correlación de Pearson, esenciales para el análisis de regresión 📉.
Predicción de Precios Futuros:
Regresión Lineal: El algoritmo calcula la pendiente, la media y la intersección de los precios pasados para crear un canal de regresión 📈, ayudando a predecir el rango de precios futuros 🔮.
Desviación Estándar y Pearson's R: Estas métricas determinan la fuerza de la regresión 🔍.
Ajuste de la Predicción:
El valor predicho se ajusta considerando la volatilidad del mercado (ATR 📉) y la dirección de las señales de tendencia 🔮, asegurando que la predicción esté alineada con el entorno actual del mercado 🌍.
Visualización:
Líneas y Bandas de Predicción: El algoritmo traza líneas que muestran el precio futuro predicho, junto con un rango de predicción (límites superior e inferior) 📉📈.
Señales de Cruce de EMAs:
Condiciones de EMAs y Puntaje Total: Se genera una señal de cruce alcista cuando el puntaje total es positivo y la EMA corta cruza por encima de la EMA larga 📈. Se genera una señal de cruce bajista cuando el puntaje total es negativo y la EMA corta cruza por debajo de la EMA larga 📉.
Consideraciones Adicionales:
Canal de Regresión Multi-Timeframe: El script calcula canales de regresión para diferentes marcos de tiempo (5m, 15m, 30m, 4h) ⏳, ayudando a determinar la dirección general del mercado 📊 (no presentado visualmente).
Interpretación de la Confianza:
Alta Confianza (cerca del 100%): Indica una fuerte alineación entre los marcos temporales con una tendencia clara (alcista o bajista) 🔥.
Baja Confianza (cerca del 0%): Muestra desacuerdo o señales débiles entre los marcos temporales ⚠️.
La confianza complementa la interpretación del rango de predicción y la dirección esperada 🔮, ayudando en las decisiones de entrada o salida en el mercado 🚀.
ATR SL Band (No-Repaint, Multi-Timeframe) + Risk per ContractThis indicator draws a non-repainting band for ATR-based Stoploss placement.
If used on Futures, it shows the distance + risk from the previous candle close, as well as from the current price.
The risk value is automatically calculated for the following symbols:
(Micro) ES (S&P 500)
(Micro) NQ (NASDAQ 100)
(Micro) YM (Dow Jones Industrial Average / US30)
The timeframe can be set individually. It is not recommended to use a lower timeframe than the chart timeframe as values differ from the actual timeframe's ATR SL in this case.
Visual ATR StopThis indicator uses the Average True Range (ATR) to display a visual range for stop placement. Two multiplier values (example, 1 and 3) can be set to create a filled area below the price. This area represents the range between the two ATR levels, adjusted by subtracting the current price, providing a simple way to visualize stop-loss placement based on volatility.
The indicator is customizable; for example, negative values can place the area above the price for short positions. The filled color can also be removed, which allows precise levels to be marked above and below.
Precision Trading Strategy: Golden EdgeThe PTS: Golden Edge strategy is designed for scalping Gold (XAU/USD) on lower timeframes, such as the 1-minute chart. It captures high-probability trade setups by aligning with strong trends and momentum, while filtering out low-quality trades during consolidation or low-volatility periods.
The strategy uses a combination of technical indicators to identify optimal entry points:
1. Exponential Moving Averages (EMAs): A fast EMA (3-period) and a slow EMA (33-period) are used to detect short-term trend reversals via crossover signals.
2. Hull Moving Average (HMA): A 66-period HMA acts as a higher-timeframe trend filter to ensure trades align with the overall market direction.
3. Relative Strength Index (RSI): A 12-period RSI identifies momentum. The strategy requires RSI > 55 for long trades and RSI < 45 for short trades, ensuring entries are backed by strong buying or selling pressure.
4. Average True Range (ATR): A 14-period ATR ensures trades occur only during volatile conditions, avoiding choppy or low-movement markets.
By combining these tools, the PTS: Golden Edge strategy creates a precise framework for scalping and offers a systematic approach to capitalize on Gold’s price movements efficiently.
WhalenatorThis custom TradingView indicator combines multiple analytic techniques to help identify potential market trends, areas of support and resistance, and zones of heightened trading activity. It incorporates a SuperTrend-like line based on ATR, Keltner Channels for volatility-based price envelopes, and dynamic order blocks derived from significant volume and pivot points. Additionally, it highlights “whale” activities—periods of exceptionally large volume—along with an estimated volume profile level and approximate bid/ask volume distribution. Together, these features aim to offer traders a more comprehensive view of price structure, volatility, and institutional participation.
This custom TradingView indicator integrates multiple trading concepts into a single, visually descriptive tool. Its primary goal is to help traders identify directional bias, volatility levels, significant volume events, and potential support/resistance zones on a price chart. Below are the main components and their functionalities:
SuperTrend-Like Line (Trend Bias):
At the core of the indicator is a trend-following line inspired by the SuperTrend concept, which uses Average True Range (ATR) to adaptively set trailing stop levels. By comparing price to these levels, the line attempts to indicate when the market is in an uptrend (price above the line) or a downtrend (price below the line). The shifting levels can provide a dynamic sense of direction and help traders stay with the predominant trend until it shifts.
Keltner Channels (Volatility and Range):
Keltner Channels, based on an exponential moving average and Average True Range, form volatility-based envelopes around price. They help traders visualize whether price is extended (touching or moving outside the upper/lower band) or trading within a stable range. This can be useful in identifying low-volatility consolidations and high-volatility breakouts.
Dynamic Order Blocks (Approximations of Supply/Demand Zones):
By detecting pivot highs and lows under conditions of significant volume, the indicator approximates "order blocks." Order blocks are areas where institutional buying or selling may have occurred, potentially acting as future support or resistance zones. Although these approximations are not perfect, they offer a visual cue to areas on the chart where price might react strongly if revisited.
Volume Profile Proxy and Whale Detection:
The indicator highlights price levels associated with recent maximum volume activity, providing a rough "volume profile" reference. Such levels often become key points of price interaction.
"Whale" detection logic attempts to identify bars where exceptionally large volume occurs (beyond a defined threshold). By tracking these "whale bars," traders can infer where heavy participation—often from large traders or institutions—may influence market direction or create zones of interest.
Approximate Bid/Ask Volume and Dollar Volume Tracking:
The script estimates whether volume within each bar leans more towards the bid or the ask side, aiming to understand which participant (buyers or sellers) might have been more aggressive. Additionally, it calculates dollar volume (close price multiplied by volume) and provides an average to gauge the relative participation strength over time.
Labeling and Visual Aids:
Dynamic labels display Whale Frequency (the ratio of bars with exceptionally large volume), average dollar volume, and approximate ask/bid volume metrics. This gives traders at-a-glance insights into current market conditions, participation, and sentiment.
Strengths:
Multifaceted Analysis:
By combining trend, volatility, volume, and order block logic in one place, the indicator saves chart space and simplifies the analytical process. Traders gain a holistic view without flipping between multiple separate tools.
Adaptable to Market Conditions:
The use of ATR and Keltner Channels adapts to changing volatility conditions. The SuperTrend-like line helps keep traders aligned with the prevailing trend, avoiding constant whipsaws in choppy markets.
Volume-Based Insights:
Integrating whale detection and a crude volume profile proxy helps traders understand where large players might be interacting. This perspective can highlight critical levels that might not be evident from price action alone.
Convenient Visual Cues and Labels:
The indicator provides quick reference points and textual information about the underlying volume dynamics, making decision-making potentially faster and more informed.
Weaknesses:
Heuristic and Approximate Nature:
Many of the indicator’s features, like the "order blocks," "whale detection," and the approximate bid/ask volume, rely on heuristics and assumptions that may not always be accurate. Without actual Level II data or true volume profiles, the insights are best considered as supplementary, not definitive signals.
Lagging Components:
Indicators that rely on past data, like ATR-based trends or moving averages for Keltner Channels, inherently lag behind price. This can cause delayed signals, particularly in fast-moving markets, potentially missing some early opportunities or late in confirming market reversals.
No Guaranteed Predictive Power:
As with any technical tool, it does not forecast the future with certainty. Strong volume at a certain level or a bullish SuperTrend reading does not guarantee price will continue in that direction. Market conditions can change unexpectedly, and false signals will occur.
Complexity and Overreliance Risk:
With multiple signals combined, there’s a risk of information overload. Traders might feel compelled to rely too heavily on this one tool. Without complementary analysis (fundamentals, news, or additional technical confirmation), overreliance on the indicator could lead to misguided trades.
Conclusion:
This integrated indicator offers a comprehensive visual guide to market structure, volatility, and activity. Its strength lies in providing a multi-dimensional viewpoint in a single tool. However, traders should remain aware of its approximations, inherent lags, and the potential for conflicting signals. Sound risk management, position sizing, and the use of complementary analysis methods remain essential for trading success.
Risks Associated with Trading:
No indicator can guarantee profitable trades or accurately predict future price movements. Market conditions are inherently unpredictable, and reliance on any single tool or combination of tools carries the risk of financial loss. Traders should practice sound risk management, including the use of stop losses and position sizing, and should not trade with funds they cannot afford to lose. Ultimately, decisions should be guided by a thorough trading plan and possibly supplemented with other forms of market analysis or professional advice.
Risks and Important Considerations:
• Not a Standalone Tool:
• This indicator should not be used in isolation. It is essential to incorporate additional technical analysis tools, fundamental analysis, and market context when making trading decisions.
• Relying solely on this indicator may lead to incomplete assessments of market conditions.
• Market Volatility and False Signals:
• Financial markets can be highly volatile, and indicators based on historical data may not accurately predict future movements.
• The indicator may produce false signals due to sudden market changes, low liquidity, or atypical trading activity.
• Risk Management:
• Always employ robust risk management strategies, including setting stop-loss orders, diversifying your portfolio, and not over-leveraging positions.
• Understand that no indicator guarantees success, and losses are a natural part of trading.
• Emotional Discipline:
• Avoid making impulsive decisions based on indicator signals alone.
• Emotional trading can lead to significant financial losses; maintain discipline and adhere to a well-thought-out trading plan.
• Continuous Learning and Adaptation:
• Stay informed about market news, economic indicators, and global events that may impact trading conditions.
• Continuously evaluate and adjust your trading strategies as market dynamics evolve.
• Consultation with Professionals:
• Consider seeking advice from financial advisors or professional traders to understand better how this indicator can fit into your overall trading strategy.
• Professional guidance can provide personalized insights based on your financial goals and risk tolerance.
Disclaimer:
Trading financial instruments involves substantial risk and may not be suitable for all investors. Past performance is not indicative of future results. This indicator is provided for informational and educational purposes only and should not be considered investment advice. Always conduct your own research and consult with a licensed financial professional before making any trading decisions.
Note: The effectiveness of any technical indicator can vary based on market conditions and individual trading styles. It's crucial to test indicators thoroughly using historical data and possibly paper trading before applying them in live trading scenarios.
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
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!
