ADR % (Fixed Top Middle, Maroon Font)ADR % label . This shows the stock's ADR (Average Daily Range) in % as digits right above your chart without creating any clutter.
Средний истинный диапазон (ATR)
Average Daily Price Movement (14 Days)Computes the daily high-low range
Averages it over 14 candles
Displays a label on the most recent candle with the average range in text
Freedom LR Price Action PublicThis is a script using multiple types of linear regression with channels, LSMAs, signal lines based on LSMAs, and ATR based on linear regression.
RSI Divergence Strategy - AliferCryptoStrategy Overview
The RSI Divergence Strategy is designed to identify potential reversals by detecting regular bullish and bearish divergences between price action and the Relative Strength Index (RSI). It automatically enters positions when a divergence is confirmed and manages risk with configurable stop-loss and take-profit levels.
Key Features
Automatic Divergence Detection: Scans for RSI pivot lows/highs vs. price pivots using user-defined lookback windows and bar ranges.
Dual SL/TP Methods:
- Swing-based: Stops placed a configurable percentage beyond the most recent swing high/low.
- ATR-based: Stops placed at a multiple of Average True Range, with a separate risk/reward multiplier.
Long and Short Entries: Buys on bullish divergences; sells short on bearish divergences.
Fully Customizable: Input groups for RSI, divergence, swing, ATR, and general SL/TP settings.
Visual Plotting: Marks divergences on chart and plots stop-loss (red) and take-profit (green) lines for active trades.
Alerts: Built-in alert conditions for both bullish and bearish RSI divergences.
Detailed Logic
RSI Calculation: Computes RSI of chosen source over a specified period.
Pivot Detection:
- Identifies RSI pivot lows/highs by scanning a lookback window to the left and right.
- Uses ta.barssince to ensure pivots are separated by a minimum/maximum number of bars.
Divergence Confirmation:
- Bullish: Price makes a lower low while RSI makes a higher low.
- Bearish: Price makes a higher high while RSI makes a lower high.
Entry:
- Opens a Long position when bullish divergence is true.
- Opens a Short position when bearish divergence is true.
Stop-Loss & Take-Profit:
- Swing Method: Computes the recent swing high/low then adjusts by a percentage margin.
- ATR Method: Uses the current ATR × multiplier applied to the entry price.
- Take-Profit: Calculated as entry price ± (risk × R/R ratio).
Exit Orders: Uses strategy.exit to place bracket orders (stop + limit) for both long and short positions.
Inputs and Configuration
RSI Settings: Length & price source for the RSI.
Divergence Settings: Pivot lookback parameters and valid bar ranges.
SL/TP Settings: Choice between Swing or ATR method.
Swing Settings: Swing lookback length, margin (%), and risk/reward ratio.
ATR Settings: ATR length, stop multiplier, and risk/reward ratio.
Usage Notes
Adjust the Pivot Lookback and Range values to suit the volatility and timeframe of your market.
Use higher ATR multipliers for wider stops in choppy conditions, or tighten swing margins in trending markets.
Backtest different R/R ratios to find the balance between win rate and reward.
Disclaimer
This script is for educational purposes only and does not constitute financial advice. Trading carries significant risk and you may lose more than your initial investment. Always conduct your own research and consider consulting a professional before making any trading decisions.
Bullish and Bearish Breakout Alert for Gold Futures PullbackBelow is a Pine Script (version 6) for TradingView that includes both bullish and bearish breakout conditions for my intraday trading strategy on micro gold futures (MGC). The strategy focuses on scalping two-legged pullbacks to the 20 EMA or key levels with breakout confirmation, tailored for the Apex Trader Funding $300K challenge. The script accounts for the Daily Sentiment Index (DSI) at 87 (overbought, favoring pullbacks). It generates alerts for placing stop-limit orders for 175 MGC contracts, ensuring compliance with Apex’s rules ($7,500 trailing threshold, $20,000 profit target, 4:59 PM ET close).
Script Requirements
Version: Pine Script v6 (latest for TradingView, April 2025).
Purpose:
Bullish: Alert when price breaks above a rejection candle’s high after a two-legged pullback to the 20 EMA in a bullish trend (price above 20 EMA, VWAP, higher highs/lows).
Bearish: Alert when price breaks below a rejection candle’s low after a two-legged pullback to the 20 EMA in a bearish trend (price below 20 EMA, VWAP, lower highs/lows).
Context: 5-minute MGC chart, U.S. session (8:30 AM–12:00 PM ET), avoiding overbought breakouts above $3,450 (DSI 87).
Output: Alerts for stop-limit orders (e.g., “Buy: Stop=$3,377, Limit=$3,377.10” or “Sell: Stop=$3,447, Limit=$3,446.90”), quantity 175 MGC.
Apex Compliance: 175-contract limit, stop-losses, one-directional news trading, close by 4:59 PM ET.
How to Use the Script in TradingView
1. Add Script:
Open TradingView (tradingview.com).
Go to “Pine Editor” (bottom panel).
Copy the script from the content.
Click “Add to Chart” to apply to your MGC 5-minute chart .
2. Configure Chart:
Symbol: MGC (Micro Gold Futures, CME, via Tradovate/Apex data feed).
Timeframe: 5-minute (entries), 15-minute (trend confirmation, manually check).
Indicators: Script plots 20 EMA and VWAP; add RSI (14) and volume manually if needed .
3. Set Alerts:
Click the “Alert” icon (bell).
Add two alerts:
Bullish Breakout: Condition = “Bullish Breakout Alert for Gold Futures Pullback,” trigger = “Once Per Bar Close.”
Bearish Breakout: Condition = “Bearish Breakout Alert for Gold Futures Pullback,” trigger = “Once Per Bar Close.”
Customize messages (default provided) and set notifications (e.g., TradingView app, SMS).
Example: Bullish alert at $3,377 prompts “Stop=$3,377, Limit=$3,377.10, Quantity=175 MGC” .
4. Execute Orders:
Bullish:
Alert triggers (e.g., stop $3,377, limit $3,377.10).
In TradingView’s “Order Panel,” select “Stop-Limit,” set:
Stop Price: $3,377.
Limit Price: $3,377.10.
Quantity: 175 MGC.
Direction: Buy.
Confirm via Tradovate.
Add bracket order (OCO):
Stop-loss: Sell 175 at $3,376.20 (8 ticks, $1,400 risk).
Take-profit: Sell 87 at $3,378 (1:1), 88 at $3,379 (2:1) .
Bearish:
Alert triggers (e.g., stop $3,447, limit $3,446.90).
Select “Stop-Limit,” set:
Stop Price: $3,447.
Limit Price: $3,446.90.
Quantity: 175 MGC.
Direction: Sell.
Confirm via Tradovate.
Add bracket order:
Stop-loss: Buy 175 at $3,447.80 (8 ticks, $1,400 risk).
Take-profit: Buy 87 at $3,446 (1:1), 88 at $3,445 (2:1) .
5. Monitor:
Green triangles (bullish) or red triangles (bearish) confirm signals.
Avoid bullish entries above $3,450 (DSI 87, overbought) or bearish entries below $3,296 (support) .
Close trades by 4:59 PM ET (set 4:50 PM alert) .
Adaptive ATR LimitsThis script plots adaptive ATR limits for intraday trading. It is intended for equities. It is not tested for other securities like futures, crypto, etc, though it may work for these too. It works for both regular trading hours and extended trading hours.
The limit lines (top and bottom) are always exactly 1 ATR/ADR apart. This is a key feature of the indicator.
The main mode is ATR, which includes overnight gaps and pre- and post-market movements. This also means the previous day close is considered to part of the current days range (which aligns with the definition of ATR). There is also an ADR mode, which uses the average range the price moves within regular hours only and is not affected by prices outside of these. Other than that, they work the same (including ATR/ADR length option and smoothing).
When in ADR mode, it treats premarket as a separate session from the regular/post-market and resets the session range at the regular market open. This is so it can plot the limits in the regular/post-market hours without being affected by the pre-market range. This is necessary since the daily ADR includes only regular market moves and due to the way the limits adapt.
It tries to plot the most sensible ATR limits based on the current daily ATR, in order to provide a visual target for how far a price could/should move intraday. In order to do this, it uses two methods to calculate limits, i) based on the mid-point of the current session range, and ii) based on the currently established range and current relative price position within that range.
The session starts using the first method. As more of the ATR is covered in the session, it transitions over of the second method. Once (if) the full ATR is covered within the session, it will have completely transitioned to the second method and will only use that for the rest of the session. In between these states, a weighted average of the two methods is used depending on the amount of the ATR the session has covered.
To explain the effect, as an example, imagine that the price is approaching the full ATR range on the high side. The indicator will have almost fully transitioned to the second (relative) method. The lower ATR limit will now be anchored to the daily low as the price hits the upper ATR limit. If the price goes beyond the upper ATR, the lower ATR limit will stay anchored to the daily low, and the upper limit will stay anchored to 1 ATR above the lower limit. This allows you to see how far the price is going beyond the upper ATR limit. If the price then returns and backs off the upper ATR limit, the lower ATR limit will un-anchor from the daily low (it will actually rise since the daily ATR range has been exceeded so the lower ATR limit needs to come up since the actual daily range can't fit into the ATR range anymore). The overall effect is to give you the best visual indication where the price is in relation to a possible upper ATR-based target. Reverse this example for when price low approaches the ATR range on the low side.
There is also a "basic mode" which simply plots 1 ATR/ADR above/below the session low/high. When using ADR, the session resets at the end of the pre-market.
The ATR length (averaging period) can be set (number of days), as well as a visual smoothing of the ATR limits using EMA.
Momentum + Keltner Stochastic Combo)The Momentum-Keltner-Stochastic Combination Strategy: A Technical Analysis and Empirical Validation
This study presents an advanced algorithmic trading strategy that implements a hybrid approach between momentum-based price dynamics and relative positioning within a volatility-adjusted Keltner Channel framework. The strategy utilizes an innovative "Keltner Stochastic" concept as its primary decision-making factor for market entries and exits, while implementing a dynamic capital allocation model with risk-based stop-loss mechanisms. Empirical testing demonstrates the strategy's potential for generating alpha in various market conditions through the combination of trend-following momentum principles and mean-reversion elements within defined volatility thresholds.
1. Introduction
Financial market trading increasingly relies on the integration of various technical indicators for identifying optimal trading opportunities (Lo et al., 2000). While individual indicators are often compromised by market noise, combinations of complementary approaches have shown superior performance in detecting significant market movements (Murphy, 1999; Kaufman, 2013). This research introduces a novel algorithmic strategy that synthesizes momentum principles with volatility-adjusted envelope analysis through Keltner Channels.
2. Theoretical Foundation
2.1 Momentum Component
The momentum component of the strategy builds upon the seminal work of Jegadeesh and Titman (1993), who demonstrated that stocks which performed well (poorly) over a 3 to 12-month period continue to perform well (poorly) over subsequent months. As Moskowitz et al. (2012) further established, this time-series momentum effect persists across various asset classes and time frames. The present strategy implements a short-term momentum lookback period (7 bars) to identify the prevailing price direction, consistent with findings by Chan et al. (2000) that shorter-term momentum signals can be effective in algorithmic trading systems.
2.2 Keltner Channels
Keltner Channels, as formalized by Chester Keltner (1960) and later modified by Linda Bradford Raschke, represent a volatility-based envelope system that plots bands at a specified distance from a central exponential moving average (Keltner, 1960; Raschke & Connors, 1996). Unlike traditional Bollinger Bands that use standard deviation, Keltner Channels typically employ Average True Range (ATR) to establish the bands' distance from the central line, providing a smoother volatility measure as established by Wilder (1978).
2.3 Stochastic Oscillator Principles
The strategy incorporates a modified stochastic oscillator approach, conceptually similar to Lane's Stochastic (Lane, 1984), but applied to a price's position within Keltner Channels rather than standard price ranges. This creates what we term "Keltner Stochastic," measuring the relative position of price within the volatility-adjusted channel as a percentage value.
3. Strategy Methodology
3.1 Entry and Exit Conditions
The strategy employs a contrarian approach within the channel framework:
Long Entry Condition:
Close price > Close price periods ago (momentum filter)
KeltnerStochastic < threshold (oversold within channel)
Short Entry Condition:
Close price < Close price periods ago (momentum filter)
KeltnerStochastic > threshold (overbought within channel)
Exit Conditions:
Exit long positions when KeltnerStochastic > threshold
Exit short positions when KeltnerStochastic < threshold
This methodology aligns with research by Brock et al. (1992) on the effectiveness of trading range breakouts with confirmation filters.
3.2 Risk Management
Stop-loss mechanisms are implemented using fixed price movements (1185 index points), providing definitive risk boundaries per trade. This approach is consistent with findings by Sweeney (1988) that fixed stop-loss systems can enhance risk-adjusted returns when properly calibrated.
3.3 Dynamic Position Sizing
The strategy implements an equity-based position sizing algorithm that increases or decreases contract size based on cumulative performance:
$ContractSize = \min(baseContracts + \lfloor\frac{\max(profitLoss, 0)}{equityStep}\rfloor - \lfloor\frac{|\min(profitLoss, 0)|}{equityStep}\rfloor, maxContracts)$
This adaptive approach follows modern portfolio theory principles (Markowitz, 1952) and Kelly criterion concepts (Kelly, 1956), scaling exposure proportionally to account equity.
4. Empirical Performance Analysis
Using historical data across multiple market regimes, the strategy demonstrates several key performance characteristics:
Enhanced performance during trending markets with moderate volatility
Reduced drawdowns during choppy market conditions through the dual-filter approach
Optimal performance when the threshold parameter is calibrated to market-specific characteristics (Pardo, 2008)
5. Strategy Limitations and Future Research
While effective in many market conditions, this strategy faces challenges during:
Rapid volatility expansion events where stop-loss mechanisms may be inadequate
Prolonged sideways markets with insufficient momentum
Markets with structural changes in volatility profiles
Future research should explore:
Adaptive threshold parameters based on regime detection
Integration with additional confirmatory indicators
Machine learning approaches to optimize parameter selection across different market environments (Cavalcante et al., 2016)
References
Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. The Journal of Finance, 47(5), 1731-1764.
Cavalcante, R. C., Brasileiro, R. C., Souza, V. L., Nobrega, J. P., & Oliveira, A. L. (2016). Computational intelligence and financial markets: A survey and future directions. Expert Systems with Applications, 55, 194-211.
Chan, L. K. C., Jegadeesh, N., & Lakonishok, J. (2000). Momentum strategies. The Journal of Finance, 51(5), 1681-1713.
Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. The Journal of Finance, 48(1), 65-91.
Kaufman, P. J. (2013). Trading systems and methods (5th ed.). John Wiley & Sons.
Kelly, J. L. (1956). A new interpretation of information rate. The Bell System Technical Journal, 35(4), 917-926.
Keltner, C. W. (1960). How to make money in commodities. The Keltner Statistical Service.
Lane, G. C. (1984). Lane's stochastics. Technical Analysis of Stocks & Commodities, 2(3), 87-90.
Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation. The Journal of Finance, 55(4), 1705-1765.
Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77-91.
Moskowitz, T. J., Ooi, Y. H., & Pedersen, L. H. (2012). Time series momentum. Journal of Financial Economics, 104(2), 228-250.
Murphy, J. J. (1999). Technical analysis of the financial markets: A comprehensive guide to trading methods and applications. New York Institute of Finance.
Pardo, R. (2008). The evaluation and optimization of trading strategies (2nd ed.). John Wiley & Sons.
Raschke, L. B., & Connors, L. A. (1996). Street smarts: High probability short-term trading strategies. M. Gordon Publishing Group.
Sweeney, R. J. (1988). Some new filter rule tests: Methods and results. Journal of Financial and Quantitative Analysis, 23(3), 285-300.
Wilder, J. W. (1978). New concepts in technical trading systems. Trend Research.
MG Thrust Indicator🚀 Explanation 🚀
The MG thrust indicator uses thrust momentum in price with some smoothing to detect uptrend and downtrend shifts.
✨ Key Features ✨
🗡smoothing_length (default: 37): length for smoothing price and thrust values (EMA or SMA).
🗡thrust_threshold (default: 1.5): multiples of ATR to identify significant thrusts.
🗡use_ema (default: true): toggle between EMA (faster response) and SMA (smoother) for smoothing.
🗡lookback_atr (default: 14): lookback period for ATR to normalize thrust.
📈 Thrust Calculation 📈
Thrust = (close - smoothed_price) / atr: measures how far the current price deviates from the smoothed price, normalized by ATR to account for volatility.
Background Highlights: colors the background faintly green/red for bullish/bearish thrusts.
❓ Seeing a bug or an issue ❓
Feel free to DM me if you see a component that seems badly calculated.
I will be happy to fix it.
❗❗ Disclaimer ❗❗
This is a single indicator, even though it's aggregating many, do not use it as a standalone.
Past performance is not indicative of future results.
Always backtest, check, and align parameters before live trading.
QQE SHARPE MAX BOT v2 - Reversals + Trailing + VolumenThe **“QQE SHARPE MAX BOT v2”** strategy is based on detecting momentum shifts using the QQE Mod indicator, combined with a trend filter based on EMA and Heikin Ashi, as well as a volume filter that requires volume to be above its moving average to validate entries. It operates in both directions (long and short) with automatic reversals and manages risk through dynamic trailing stops based on ATR, allowing it to maximize profits during strong trends and avoid trading in low-interest market zones.
Chandelier Exit with ZLSMA SwiftEdgeChandelier Exit with ZLSMA
Overview
The "Chandelier Exit with ZLSMA" indicator is a powerful trading tool designed to identify trend reversals and high-probability entry points in financial markets. By combining the volatility-based Chandelier Exit with the low-lag Zero Lag Least Squares Moving Average (ZLSMA), this indicator provides clear Buy and Sell signals, enhanced with a unique signal strength score to help traders prioritize high-quality opportunities. Visual enhancements, including dynamic color coding, background highlights, and trend arrows, make it intuitive and visually appealing for both novice and experienced traders.
What It Does
This indicator generates Buy and Sell signals when a trend reversal is detected by the Chandelier Exit, but only if the price crosses the ZLSMA for the first time in the direction of the trend. Each signal is accompanied by a percentage score (0-100%) that measures its strength based on price movement and momentum. The indicator overlays directly on the price chart, displaying:
Buy/Sell labels with signal strength (e.g., "Buy (85%)").
A ZLSMA line that changes color (green for bullish, red for bearish) to indicate trend direction.
Background highlights to mark signal candles.
Trend arrows to visually confirm signal points.
How It Works
The indicator combines two complementary components:
Chandelier Exit:
Uses the Average True Range (ATR) to create dynamic trailing stop levels (long_stop and short_stop) that adapt to market volatility.
Signals a Buy when the price crosses above the short stop (indicating a potential uptrend) and a Sell when it crosses below the long stop (indicating a potential downtrend).
Default settings use an ATR period of 1 and a multiplier of 2.0 for high sensitivity to short-term price movements.
Zero Lag LSMA (ZLSMA):
A low-lag moving average based on linear regression, designed to reduce delay compared to traditional moving averages.
Acts as a trend filter: Buy signals are only generated when the price closes above ZLSMA for the first time, and Sell signals when it closes below for the first time.
Default length of 50 balances smoothness with responsiveness.
Signal Strength Score:
Each signal is assigned a score (0-100%) based on:
Distance to ZLSMA (60% weight): How far the price is from ZLSMA, normalized by ATR. Larger distances indicate stronger breakouts.
Candlestick size (40% weight): The size of the signal candle, normalized by ATR. Larger candles suggest stronger momentum.
A high score (e.g., >80%) indicates a robust signal, while a low score (e.g., <50%) suggests caution.
Visual Features:
The ZLSMA line changes color (green for bullish, red for bearish) to reflect the trend.
Signal candles are highlighted with a subtle green (Buy) or red (Sell) background.
Tiny triangular arrows appear below Buy signals and above Sell signals for clear visual confirmation.
Why Combine Chandelier Exit and ZLSMA?
The Chandelier Exit excels at identifying trend reversals through volatility-based stops, but it can generate false signals in choppy markets due to its sensitivity (especially with a short ATR period of 1). The ZLSMA addresses this by acting as a trend filter, ensuring signals are only triggered when the price confirms a trend by crossing the ZLSMA for the first time. This combination reduces noise and focuses on high-probability setups. The signal strength score further enhances decision-making by quantifying the conviction behind each signal, making the indicator feel intuitive and "smart."
How to Use
Setup:
Add the indicator to your chart in TradingView.
Adjust inputs in the settings panel:
ATR Period (default: 1): Controls the sensitivity of Chandelier Exit. Increase for smoother signals.
ATR Multiplier (default: 2.0): Sets the distance of stop levels from price extremes.
ZLSMA Length (default: 50): Adjusts the smoothness of the ZLSMA line. Shorter lengths (e.g., 20-30) are more responsive; longer lengths (e.g., 50-100) are smoother.
Use Close Price for Extremums (default: true): Determines whether Chandelier Exit uses closing prices or high/low prices for calculations.
Interpreting Signals:
Buy Signal: A green "Buy (X%)" label appears below a candle when the price crosses above the Chandelier Exit short stop and closes above ZLSMA for the first time. The percentage indicates signal strength (higher = stronger).
Sell Signal: A red "Sell (X%)" label appears above a candle when the price crosses below the Chandelier Exit long stop and closes below ZLSMA for the first time.
Use the ZLSMA line’s color (green for bullish, red for bearish) to confirm the overall trend.
Prioritize signals with high strength scores (e.g., >70%) for better reliability.
Trading Considerations:
Combine signals with other analysis (e.g., support/resistance, volume) for confirmation.
Test the indicator on a demo account or use TradingView’s Strategy Tester to evaluate performance.
Be cautious with the default ATR period of 1, as it is highly sensitive and may generate frequent signals in volatile markets.
What Makes It Unique
This indicator stands out due to its thoughtful integration of Chandelier Exit and ZLSMA, creating a synergy that balances sensitivity with reliability. The first-cross filter ensures signals are triggered only at the start of potential trends, reducing false positives. The signal strength score adds a layer of intelligence, helping traders assess the quality of each signal without needing external tools. Visual enhancements, such as dynamic ZLSMA coloring, background highlights, and trend arrows, make the indicator user-friendly and visually engaging, appealing to traders seeking a modern, intuitive tool.
Limitations and Notes
The short ATR period (1) makes the indicator highly sensitive, which suits short-term traders but may produce noise in sideways markets. Increase the ATR period for smoother signals.
The signal strength score is a heuristic based on price movement and momentum, not a predictive model. Use it as a guide, not a definitive predictor.
Always backtest the indicator on your preferred market and timeframe to ensure it aligns with your trading strategy.
SwiftEdge NW EnvelopeSwiftEdge NW Envelope
Overview
The SwiftEdge NW Envelope is a visually striking technical indicator designed for traders seeking to identify high-probability buy and sell opportunities in volatile markets. By combining the Relative Strength Index (RSI), Average True Range (ATR), and Nadaraya-Watson Envelope, this indicator provides a unique blend of momentum, volatility, and non-linear trend analysis. Its futuristic, AI-inspired aesthetic—featuring neon gradients and dynamic colors—enhances chart readability while delivering actionable trading signals.
What It Does
The SwiftEdge NW Envelope generates buy and sell signals based on price interactions with dynamically calculated support and resistance bands, confirmed by RSI conditions. The indicator:
Plots a Nadaraya-Watson Envelope to identify smooth, non-linear price trends and dynamic support/resistance zones.
Uses ATR to scale the envelope’s bands, adapting to market volatility.
Employs RSI to confirm overbought/oversold conditions, ensuring signals align with momentum.
Visualizes signals with neon-colored markers, background zones, and labels for intuitive decision-making.
How It Works
The indicator integrates three key components:
Nadaraya-Watson Envelope:
A kernel-based regression technique that smooths price data to create a central trend line (mean) and dynamic upper/lower bands.
Unlike traditional moving averages, it provides a non-linear, adaptive view of price trends, making it ideal for capturing complex market movements.
The band width is determined by ATR, ensuring responsiveness to volatility.
Average True Range (ATR):
Measures market volatility to scale the envelope’s bands.
A multiplier (default: 0.5) adjusts the sensitivity of the bands, allowing traders to fine-tune the indicator for different assets or market conditions.
Relative Strength Index (RSI):
A momentum oscillator with a shortened period (default: 5) for increased sensitivity.
Confirms buy signals when RSI is oversold (default: <30) and sell signals when RSI is overbought (default: >70).
Signal Logic
Buy Signal: Triggered when the price crosses above the lower band of the Nadaraya-Watson Envelope and RSI is below the oversold threshold. Marked by a green circle and a "BUY" label below the candle.
Sell Signal: Triggered when the price crosses below the upper band and RSI is above the overbought threshold. Marked by a magenta circle and a "SELL" label above the candle.
Background Zones: Green (buy) or red (sell) translucent zones highlight signal areas for quick recognition.
Visual Features
Dynamic Colors: The central trend line shifts between cyan (uptrend), purple (downtrend), or gray (neutral) based on price position relative to the mean.
Neon Gradient Fill: A translucent blue fill between the upper (green) and lower (red) bands creates a glowing, futuristic effect.
Modern Signal Markers: Small, vibrant circles (green for buy, magenta for sell) and clear labels enhance visual clarity.
Why This Combination?
The SwiftEdge NW Envelope combines RSI, ATR, and Nadaraya-Watson Envelope to create a robust trading tool:
RSI provides momentum confirmation, filtering out false signals in choppy markets.
ATR ensures the envelope adapts to changing volatility, making it suitable for both trending and ranging markets.
Nadaraya-Watson Envelope offers a sophisticated, non-linear alternative to traditional bands (e.g., Bollinger Bands), capturing subtle price dynamics. Together, these components deliver a balanced approach to trend-following and mean-reversion strategies, with RSI acting as a gatekeeper to improve signal reliability.
Customize Settings:
RSI Period (5): Adjust for more/less sensitivity to momentum.
RSI Overbought/Oversold (70/30): Modify thresholds to tighten or loosen signal conditions.
ATR Period (14) and Multiplier (0.5): Tune volatility sensitivity.
NW Length (25), Bandwidth (8.0), Multiplier (3.0): Adjust the smoothness and width of the envelope.
Interpret Signals:
Buy: Look for green circles and "BUY" labels when price crosses above the lower band, confirmed by low RSI.
Sell: Look for magenta circles and "SELL" labels when price crosses below the upper band, confirmed by high RSI.
Use background zones to quickly spot active signal areas.
Combine with Other Tools:
Pair with support/resistance levels or volume analysis for additional confirmation.
Test signals on a demo account before live trading.
Originality
The SwiftEdge NW Envelope stands out due to:
Its innovative use of Nadaraya-Watson regression, a less common but powerful tool for non-linear trend analysis.
A unique visual design with neon gradients and dynamic colors, inspired by AI and futuristic interfaces, making it both functional and visually engaging.
A streamlined signal system that balances momentum (RSI), volatility (ATR), and trend (Nadaraya-Watson), reducing noise and enhancing trade precision.
Notes
Best suited for volatile markets (e.g., forex, crypto, stocks) where price swings create clear envelope breakouts.
Adjust input parameters to match your trading style (e.g., shorter RSI period for scalping, wider bands for swing trading).
Always backtest and validate signals in your specific market and timeframe before trading.
Multi Timeframe ATR, CCI & RSIMulti Timeframe ATR, CCI & RSI (MTF IND)
This indicator displays ATR, CCI, and RSI values from a custom selected timeframe in a clean table overlay.
It helps monitor volatility and momentum from higher/lower timeframes directly on your current chart.
Features:
• Select custom timeframe for all indicators (e.g., 1D, 1W, 65m, etc.)
• ATR with selectable smoothing type (RMA, SMA, EMA, WMA)
• CCI & RSI with trend arrows (▲ rising, ▼ falling, ▬ neutral)
• Compact summary table
DEMA Trend Oscillator Strategy📌 Overview
The DEMA Trend Oscillator Strategy is a dynamic trend-following approach based on the Normalized DEMA Oscillator SD.
It adapts in real-time to market volatility with the goal of improving entry accuracy and optimizing risk management.
⚠️ This strategy is provided for educational and research purposes only.
Past performance does not guarantee future results.
🎯 Strategy Objectives
The main goal of this strategy is to respond quickly to sudden price movements and trend reversals,
by combining momentum-based signals with volatility filters.
It is designed to be user-friendly for traders of all experience levels.
✨ Key Features
Normalized DEMA Oscillator: A momentum indicator that normalizes DEMA values on a 0–100 scale, allowing intuitive identification of trend strength
Two-Bar Confirmation Filter: Requires two consecutive bullish or bearish candles to reduce noise and enhance entry reliability
ATR x2 Trailing Stop: In addition to fixed stop-loss levels, a trailing stop based on 2× ATR is used to maximize profits during strong trends
📊 Trading Rules
Long Entry:
Normalized DEMA > 55 (strong upward momentum)
Candle low is above the upper SD band
Two consecutive bullish candles appear
Short Entry:
Normalized DEMA < 45 (downward momentum)
Candle high is below the lower SD band
Two consecutive bearish candles appear
Exit Conditions:
Take-profit at a risk-reward ratio of 1.5
Stop-loss triggered if price breaks below (long) or above (short) the SD band
Trailing stop activated based on 2× ATR to secure and extend profits
💰 Risk Management Parameters
Symbol & Timeframe: Any (AUDUSD 5M example)
Account size (virtual): $3000
Commission: 0.4PIPS(0.0004)
Slippage: 2 pips
Risk per trade: 5%
Number of trades (backtest):534
All parameters can be adjusted based on broker specifications and individual trading profiles.
⚙️ Trading Parameters & Considerations
Indicator: Normalized DEMA Oscillator SD
Parameter settings:
DEMA Period (len_dema): 40
Base Length: 20
Long Threshold: 55
Short Threshold: 45
Risk-Reward Ratio: 1.5
ATR Multiplier for Trailing Stop: 2.0
🖼 Visual Support
The chart displays the following visual elements:
Upper and lower SD bands (±2 standard deviations)
Entry signals shown as directional arrows
🔧 Strategy Improvements & Uniqueness
This strategy is inspired by “Normalized DEMA Oscillator SD” by QuantEdgeB,
but introduces enhancements such as a two-bar confirmation filter and an ATR-based trailing stop.
Compared to conventional trend-following strategies, it offers superior noise filtering and profit optimization.
✅ Summary
The DEMA Trend Oscillator Strategy is a responsive and practical trend-following method
that combines momentum detection with adaptive risk management.
Its visual clarity and logical structure make it a powerful and repeatable tool
for traders seeking consistent performance in trending markets.
⚠️ Always apply appropriate risk management. This strategy is based on historical data and does not guarantee future results.
Weighted Ichimoku StrategyLSE:HSBA
The Ichimoku Kinko Hyo indicator is a comprehensive tool that combines multiple signals to identify market trends and potential buying/selling opportunities. My weighted variant of this strategy attempts to assign specific weights to each signal, allowing for a more nuanced and customizable approach to trend identification. The intent is to try and make a more informed trading decision based on the cumulative strength of various signals.
I've tried not to make it a mishmash of this and that + MACD + RSI and on and on; most people have their preferred indicator that focuses on just that that they can use in conjunction.
The signals used can be grouped into two groups the 'Core Ichimoku Signals' & the 'Additional Signals' (at the end you will find the signals and their assigned weights followed by the thresholds where they align).
The Core Ichimoku Signals are the primary signals used in Ichimoku analysis, including Kumo Breakout, Chikou Cross, Kijun Cross, Tenkan Cross, and Kumo Twist.
While the Additional Signals provide further insights and confirmations, such as Kijun Confirmation, Tenkan-Kijun Above Cloud, Chikou Above Cloud, Price-Kijun Cross, Chikou Span Signal, and Price Positioning.
Entries are triggered when the cumulative weight of bullish signals exceeds a specified buy threshold, indicating a strong uptrend or potential trend reversal.
Exits are initiated when the cumulative weight of bearish signals surpasses a specified sell threshold, or when additional conditions such as consolidation patterns or ATR-based targets are met.
There are various exit types that you can choose between, which can be used separately or in conjunction with one another. As an example you might want to exit on a different condition during consolidation periods than during other periods or just use ATR with some other backstop.
They are listed in evaluation order i.e. ATR trumps all, Consolidation exit trumps the regular Kumo sell and so on:
**ATR Sell**: Exits trades based on ATR-based profit targets and stop-losses.
**Consolidation Exit**: Exits trades during consolidation periods to reduce drawdown.
**Sell Below Kumo**: Exits trades when the price is below the Kumo, indicating a potential downtrend.
**Sell Threshold**: Exits trades when the cumulative weight of bearish signals surpasses a specified sell threshold.
There are various 'filters' which are really behavior modifiers:
**Kumo Breakout Filter**: Requires price to close above the Kumo for buy signals (essentially a entry delay).
**Whipsaw Filter**: Ensures trend strength over specified days to reduce false signals.
**Buy Cooldown**: Prevents new entries until half the Kijun period passes after an exit (prevents flapping).
**Chikou Filter**: Delays exits unless the previous close is below the Chikou Span.
**Consolidation Trend Filter**: Prevents consolidation exits if the trend is bullish (rare, but happens).
Then there are some debugging options. Ichimoku periods have some presets (personally I like 8/22/44/22) but are freely configurable, preset to the traditional values for purists.
The list of signals and most thresholds follow, play around with them. Thats all.
Cheers,
**Core Ichimoku Signals**
**Kumo Breakout**
- 30 (Bullish) / -30 (Bearish)
- Indicates a strong trend when the price breaks above (bullish) or below (bearish) the Kumo (cloud). This signal suggests a significant shift in market sentiment.
**Chikou Cross**
- 20 (Bullish) / -20 (Bearish)
- Shows the relationship between the Chikou Span (lagging span) and the current price. A bullish signal occurs when the Chikou Span is above the price, indicating a potential uptrend. Conversely, a bearish signal occurs when the Chikou Span is below the price, suggesting a downtrend.
**Kijun Cross**
- 15 (Bullish) / -15 (Bearish)
- Signals trend changes when the Tenkan-sen (conversion line) crosses above (bullish) or below (bearish) the Kijun-sen (base line). This crossover is often used to identify potential trend reversals.
**Tenkan Cross**
- 10 (Bullish) / -10 (Bearish)
- Indicates short-term trend changes when the price crosses above (bullish) or below (bearish) the Tenkan-sen. This signal helps identify minor trend shifts within the broader trend.
**Kumo Twist**
- 5 (Bullish) / -5 (Bearish)
- Shows changes in the Kumo's direction, indicating potential trend shifts. A bullish Kumo Twist occurs when Senkou Span A crosses above Senkou Span B, and a bearish twist occurs when Senkou Span A crosses below Senkou Span B.
**Additional Signals**
**Kijun Confirmation**
- 8 (Bullish) / -8 (Bearish)
- Confirms the trend based on the price's position relative to the Kijun-sen. A bullish signal occurs when the price is above the Kijun-sen, and a bearish signal occurs when the price is below it.
**Tenkan-Kijun Above Cloud**
- 5 (Bullish) / -5 (Bearish)
- Indicates a strong bullish trend when both the Tenkan-sen and Kijun-sen are above the Kumo. Conversely, a bearish signal occurs when both lines are below the Kumo.
**Chikou Above Cloud**
- 5 (Bullish) / -5 (Bearish)
- Shows the Chikou Span's position relative to the Kumo, indicating trend strength. A bullish signal occurs when the Chikou Span is above the Kumo, and a bearish signal occurs when it is below.
**Price-Kijun Cross**
- 2 (Bullish) / -2 (Bearish)
- Signals short-term trend changes when the price crosses above (bullish) or below (bearish) the Kijun-sen. This signal is similar to the Kijun Cross but focuses on the price's direct interaction with the Kijun-sen.
**Chikou Span Signal**
- 10 (Bullish) / -10 (Bearish)
- Indicates the trend based on the Chikou Span's position relative to past price highs and lows. A bullish signal occurs when the Chikou Span is above the highest high of the past period, and a bearish signal occurs when it is below the lowest low.
**Price Positioning**
- 10 (Bullish) / -10 (Bearish)
- Shows indecision when the price is between the Tenkan-sen and Kijun-sen, indicating a potential consolidation phase. A bullish signal occurs when the price is above both lines, and a bearish signal occurs when the price is below both lines.
**Confidence Level**: Highly Sensitive
- **Buy Threshold**: 50
- **Sell Threshold**: -50
- **Notes / Significance**: ~2–3 signals, very early trend detection. High sensitivity, may capture noise and false signals.
**Confidence Level**: Entry-Level
- **Buy Threshold**: 58
- **Sell Threshold**: -58
- **Notes / Significance**: ~3–4 signals, often Chikou Cross or Kumo Breakout. Very sensitive, risks noise (e.g., false buys in choppy markets).
**Confidence Level**: Entry-Level
- **Buy Threshold**: 60
- **Sell Threshold**: -60
- **Notes / Significance**: ~3–4 signals, Kumo Breakout or Chikou Cross anchors. Entry point for early trends.
**Confidence Level**: Moderate
- **Buy Threshold**: 65
- **Sell Threshold**: -65
- **Notes / Significance**: ~4–5 signals, balances sensitivity and reliability. Suitable for moderate risk tolerance.
**Confidence Level**: Conservative
- **Buy Threshold**: 70
- **Sell Threshold**: -70
- **Notes / Significance**: ~4–5 signals, emphasizes stronger confirmations. Reduces false signals but may miss some opportunities.
**Confidence Level**: Very Conservative
- **Buy Threshold**: 75
- **Sell Threshold**: -75
- **Notes / Significance**: ~5–6 signals, prioritizes high confidence. Minimizes risk but may enter trades late.
**Confidence Level**: High Confidence
- **Buy Threshold**: 80
- **Sell Threshold**: -80
- **Notes / Significance**: ~6–7 signals, very strong confirmations needed. Suitable for cautious traders.
**Confidence Level**: Very High Confidence
- **Buy Threshold**: 85
- **Sell Threshold**: -85
- **Notes / Significance**: ~7–8 signals, extremely high confidence required. Minimizes false signals significantly.
**Confidence Level**: Maximum Confidence
- **Buy Threshold**: 90
- **Sell Threshold**: -90
- **Notes / Significance**: ~8–9 signals, maximum confidence level. Ensures trades are highly reliable but may result in fewer trades.
**Confidence Level**: Ultra Conservative
- **Buy Threshold**: 100
- **Sell Threshold**: -100
- **Notes / Significance**: ~9–10 signals, ultra-high confidence. Trades are extremely reliable but opportunities are rare.
**Confidence Level**: Extreme Confidence
- **Buy Threshold**: 110
- **Sell Threshold**: -110
- **Notes / Significance**: All signals align, extreme confidence. Trades are almost certain but very few opportunities.
Dskyz (DAFE) Turning Point Indicator - Dskyz (DAFE) Turning Point Indicator — Smart Reversal Signals
Inspired by the intelligent logic of a pervious indicator I saw. This script represents a next-generation reversal detection system—completely re-engineered with cutting-edge filters, adaptive logic, and intelligent dashboards.
The Dskyz (DAFE) Turning Point Indicator
🧠 What Is It?
is designed to identify key market reversal zones with extraordinary accuracy by combining trend direction, volatility confirmation, price action patterns, and smart filtering layers—all visualized in a highly interactive and informative chart overlay.
This isn’t just a signal generator—it’s a decision-making assistant.
⚙️ Inputs & How to Use Them
All input fields are grouped for ease-of-use and explanation:
🔸 Reversal Logic Settings
Source: The price source used for signal generation (default: hlcc4). Can be changed to any standard price formula (open, close, hl2, etc.).
ATR Period: Used for determining volatility and dynamic trailing stop logic.
Supertrend Factor / Period: Calculates directional movement to detect trending vs choppy zones.
Reversal Sensitivity Thresholds: Internal logic filters minor pullbacks from true reversals.
🔸 Filters
Trend Filter: Enables trend-only signals (optional).
Volume Spike Filter: Confirms reversals with significant volume activity.
Volatility Zone Coloring: Visually highlights high-volatility areas to avoid late entries or fakeouts.
Custom High/Low Detection: Smart local top/bottom scanning to reinforce accuracy.
🔸 Visual & Dashboard Options
Signal Labels: Toggle signal labels on the chart.
Color Theme: Choose your visual theme for easier visibility.
Dashboard Toggle: Activate a compact dashboard summarizing strategy health (win rate, drawdown, trend state, volatility).
🧩 Functions Used
ta.supertrend(): Determines trend direction for signal confirmation and filtering.
ta.atr(): Calculates real-time volatility to determine trailing stop exits and visual zones.
ta.rsi() (internally optimized): Helps filter overbought/oversold conditions.
Local High/Low Scanner: Tracks recent pivots using a custom dynamic lookback.
Signal Engine: Consolidates multiple confirmation layers before plotting.
🚀 What Makes It Unique?
Unlike traditional reversal indicators, this one combines:
Multi-factor signal validation: No single indicator makes the call—volume, trend, price action, and volatility all contribute.
Adaptive filtering: The indicator evolves with the market—less noise, smarter signals.
Visual volatility heatmap zones: Avoid entering during uncertainty or manipulation spikes.
Interactive trend dashboard: Immediate insight into the strength and condition of the current market phase.
Highly customizable: Turn features on/off to match your trading style—scalping, swing, or trend-following.
Precision timing: Uses optimized versions of RSI and ATR that adjust automatically with price context.
🧬 Recommended for:
Commodity: Futures, Forex, Crypto
Timeframes: 1m to 1h for active traders. 4h+ for swing trades.
Pair With: Support/resistance zones, Fibonacci levels, and smart money concepts for additional confluence.
🎯 Why It Works
- Traditional reversal signals suffer from lag and noise. This system filters both by:
- Using multi-source confirmation, not just price movement.
-Tracking volatility directly, not assuming static markets.
-Detecting exhaustion, not just divergence.
-Keeping your screen clean, with only the most relevant data shown.
🧾 Credit & Acknowledgement
🧠 Original Concept Inspiration: This project was deeply inspired by the work of Enes_Yetkin_ and their approach to reversal detection. This version expands on the concept with additional technical layers, updated visuals, and real-time adaptability.
📌 Final Thoughts
This is more than a reversal tool. It's a market condition interpreter, entry/exit planner, and risk assistant all in one. Every aspect is engineered to give you an edge—especially when timing means everything.
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
-Dskyz
Rogue ORB PRORogue ORB Pro is a precision-engineered Opening Range Breakout (ORB) indicator built for active intraday traders who need real signals, not noise.
This tool identifies high-probability breakout entries from the opening range, enhanced with optional ATR-based stop loss levels, deviation targets, cooldown filters, and a relative volume gate to filter weak setups.
🔍 Key Features:
Opening Range High/Low: Drawn from a user-defined time window and locked for the day
Deviations: Automatically plots target zones above and below the OR range (e.g. 1, 2 deviations)
Pre-Market Levels: Automatically draws pre market high and low lines at the end of pre market session
Buy/Sell Signals: Triggered on breakout of the OR High/Low with configurable breakout logic (touch or close)
ATR Stop Loss Line: Dynamically drawn at a fixed ATR distance from breakout candle, with optional SL label
Cooldown Period: Prevents back-to-back signals by enforcing a user-defined bar delay between entries, can help with overtrading
Volume Filter: Optional relative volume filter that requires breakout candles to exceed a custom volume threshold
VWAP Overlay: Visual VWAP for directional bias and confluence
ATR Stop-Loss & TargetsATR and Supertrend-based SL/TP & Trailing System
This indicator combines Average True Range (ATR) and Supertrend logic to help traders define precise stop-loss, first target, and trailing stop-loss (TSL) levels.
⚙️ Key Features:
📏 ATR-based Stop-Loss & Target Lines:
Uses ATR (default period: 5) based on the previous day's candle for more stable risk management.
Traders can choose the price source: Close, Open, or enter a manual price.
SL and first target are calculated using multipliers:
Multiplier 1 = Stop Loss
Multiplier 2 = First Target
📉 Supertrend for Trailing Stop:
Built-in Supertrend logic for trailing stop-loss management.
Uses ATR(10) with a multiplier of 2.1, based on HL2.
Supertrend can be toggled ON/OFF from the settings.
ATR % Oscillator - DolphinTradeBot1️⃣ Overview
🔸 This is a simplified version of ATR and TR that shows volatility as percentage changes , making it easier to compare two symbols.
🔸 The indicator compares the volatility of two different assets by calculating the percentage-based price ranges and their moving averages .
📌 This is especially useful for pair traders, as it helps identify which symbol is more volatile, allowing for strategic decisions based on relative movement rather than overall market direction.
2️⃣ How Is It Work?
🔸 For each symbol, it calculates the absolute percentage difference between either:
• Close and Open (net price change), or
• High and Low (daily price range).
🔸 The results are visualized as column bars — the taller the bar, the higher the volatility.
🔸 It also plots a moving average line (SMA) based on the selected range length.
📌 These calculations are independent of the chart you're on — they work purely based on the two selected symbols.
If no symbols are selected, it defaults to using the current chart's symbol.
3️⃣ How to Use It?
With this indicator, you can:
🔸 Compare the volatility between two assets.
🔸 Detect sudden volatility spikes that may signal upcoming momentum.
🔸 Support spread, arbitrage, or correlation-based strategies .
🔸 See which symbol is gaining market attention (a larger difference = more activity).
Example: Compare BTC vs ETH to see which one is dominating in terms of price action or volatility.
4️⃣⚙️ Settings
🔸 Symbol Settings
• Symbol-1 / Symbol-2: Choose the two assets to compare.
• Checkboxes: Enable/disable visibility for each symbol's data.
🔸 Calculation Settings
• Range Average: The number of bars used for the moving average.
• Calculation Source:
- Close-Open: Measures net price movement.
- High-Low: Measures total price range.
VoluTility🌊 VoluTility forecasts trend exhaustion, breakout pressure, and structural inflection by measuring volatility within the effort stream. Built on the concept of ATR applied to volume, it doesn’t read raw volume — it reveals whether that volume is stable, chaotic, or compressing ahead of a move. The goal is to detect structural setups before they resolve. The lower the timeframe, the greater the alpha.
🧠 Core Logic
A zero-centered histogram shows the deviation of smoothed volume from its own volatility baseline. Positive bars indicate expansion; negative bars signal compression. Color reflects rate-of-change in volume volatility. Opacity tracks effort/result strength — showing when moves are real or hollow.
The overlaid ribbon (EMA vs HMA) highlights rhythm shifts. Orange fill signals real expansion; yellow shows decay or absorption. Together, they expose pre-breakout compression and exhaustion tails before price reacts.
🏗️ Structural Read
On the 1H BTC chart shown, price coils into a shallow pullback, compressing within a narrow range marked by shrinking candle bodies and muted wick aggression. A sudden expansion candle breaks the coil cleanly, with no immediate rejection or wick reversion. Price holds above the breakout pivot, establishing a baseline for structural acceptance and shifting bias toward continuation.
🔰 Zone Descriptions
🔴 Volatile blowout
🟠 Clean expansion
🟡 Passive or absorbed effort
🟢 Steady-state rhythm
🔵 Compression coil
🧐 Suggested Use
VoluTility is expressly designed as an overlay for sub-pane indicators, where it acts as a second-order rhythm map — exposing hidden structural pressure within volume or volatility streams. When paired with volume (like ZVOL or OBVX), it highlights when flow is expanding with intent versus fading into noise. When layered over volatility signals (like ATR Turbulence or WIRE), it reveals whether expansion has real effort behind it — or is just structural slack.
It pairs especially well with the Relative Directional Index (RDI), where its histogram and ribbon offer early exhaustion signals before traditional trend or momentum fades appear. On raw momentum tools, it acts as a filter: softening false breaks and confirming pressure-backed continuation.
Run on 15m or lower charts for early entry cues or breakout anticipation. On 1H charts, use it to validate compression resolution or detect fatigue before structure turns. It doesn’t react to price — it forecasts readiness.
FSH ATR MTF MonitorThe FSH ATR MTF Monitor tracks the Average True Range (ATR) and current range across six customizable timeframes, displaying the results in a table. When a timeframe’s range exceeds its ATR, the range value turns yellow, signaling heightened volatility. This multi-timeframe tool helps traders assess market conditions and plan entries or exits.
Key Features:
- Monitors ATR and range for up to six timeframes simultaneously.
- Customizable ATR length and timeframe inputs.
- Highlights ranges exceeding ATR in yellow for quick identification.
- Table display with toggle option for flexibility.
How to Use:
1. Add the indicator to your chart.
2. Adjust the ATR length and timeframes in the inputs as needed.
3. Watch for yellow range values to spot volatility spikes across timeframes.
4. Toggle the table off if not needed.
Ideal for scalpers, swing traders, or anyone analyzing volatility across multiple timeframes.
ATR Stop BufferThe ATR Stop Buffer indicator calculates the Daily Average True Range (ATR) and converts it into ticks based on the symbol's minimum price movement. It then displays the full ATR, 2% of ATR, and 10% of ATR in a clean table format, rounded up for simplicity. This tool is ideal for traders who want to set volatility-based stop-loss levels or buffers for their trades.
Key Features:
- Uses a 14-period Daily ATR for robust volatility measurement.
- Converts ATR into ticks for precise application across different instruments.
- Table display with toggle option for flexibility.
- Perfect for risk management and trade planning.
How to Use:
1. Add the indicator to your chart.
2. Use the table values to adjust your stop-loss distances (e.g., 2% ATR for tight stops, 10% ATR for wider buffers).
3. Toggle the table off if you only need the values occasionally.
Note: Works best on instruments with defined tick sizes (e.g., futures, forex, stocks).
Daily Bollinger Band StrategyOverview of the Daily Bollinger Band Strategy
1. Strategy Overview and Features
This strategy is a tool for backtesting a trading method that uses Bollinger Bands. It is *not* a tool for automated trading.
1-1. Main Display Items
The main chart displays the Bollinger Bands and the 200-day moving average.
It also shows the entry and exit points along with the position size (in units of 100 shares).
1-2. Summary of Trading Rules
For long (buy) strategies, the trade enters when the price crosses above the +1σ line of the Bollinger Bands, aiming to ride an upward trend. The position is exited when the price crosses below the middle band.
For short (sell) strategies, the trade enters when the price crosses below the -1σ line of the Bollinger Bands, aiming to ride a downward trend. The position is exited when the price crosses above the middle band.
1-3. Strategic Enhancements
The strategy uses the slope of the 200-day moving average to determine the trend direction and enter trades accordingly. This improves the win rate and payoff ratio.
Additionally, to reduce the probability of ruin, the risk per trade is limited to 1.0% of capital, and position sizing is adjusted using ATR (a volatility indicator).
2. Trading Rules
2-1. Chart Type
Only daily charts are used.
2-2. Indicators Used
(1) Bollinger Bands** (used for entry and exit signals)
- Period: Fixed at 80 days
- Upper and lower bands: Fixed at ±1σ
(2) Moving Average** (used to determine trend direction)
- Period: Fixed at 200 days
- Trend direction is judged based on whether the difference from the previous day is positive (upward) or negative (downward)
2-3. Buy Rules
Setup:
- Price crosses above the +1σ line from below
- Both the middle band and 200-day moving average are upward sloping
Entry:
- Buy at the next day’s market open using a market order
Exit:
- If the price crosses below the middle band, sell at the next day’s open using a market order
2-4. Sell Rules
Setup:
- Price crosses below the -1σ line from above
- Both the middle band and 200-day moving average are downward sloping
Entry:
- Sell at the next day’s market open using a market order
Exit:
- If the price crosses above the middle band, buy back at the next day’s open using a market order
2-5. Risk Management Rules
- Risk per trade: 1.0% of total capital (acceptable loss = capital × 1.0%)
- Position size: Acceptable loss ÷ 2ATR (rounded down to the nearest unit of 100 shares)
2-6. Other Notes
- No brokerage fees
- No pyramiding
- No partial exits
- No reverse positions (no “stop-and-reverse” trades)
3. Strategy Parameters
The following settings can be specified:
3-1. Period Settings
- Start date: Set the start date for the backtest period
- Stop date: Set the end date for the backtest period
3-2. Display of Trend and Signals
- Show trend: When checked, the background color of the bars is light red for an uptrend and light blue for a downtrend
- Show signal: When checked, entry and exit signals are displayed (note: signals are executed at the next day’s open, so there is a one-day lag in the display)
3-3. Capital Management Settings
- Funds: Capital available for trading (in JPY)
- Risk rate: Specify what percentage of the capital to risk per trade
Settings in the “Properties” tab are not used in this strategy.
4. Backtest Results (Example)
Here are the backtest results conducted by the author:
- Target Stocks: All components of the Nikkei 225
- Test Period: January 4, 2000 – December 30, 2024
- Data Points: 12,886
- Win Rate: 33.45%
- Net Profit: ¥82,132,380
- Payoff Ratio: 2.450
- Expected Value: ¥6,373.8
- Risk Rate: 1.0%
- Probability of Ruin: 0.00%
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デイリー・ボリンジャーバンド・ストラテジーの概要
1. ストラテジーの概要と特徴
このストラテジーは、ボリンジャーバンドを使ったトレード手法のバックテストを行うツールです。自動売買を行うツールではありません。
1-1. 主な表示項目
メインチャートにボリンジャーバンドと 200日移動平均線を表示します。
また、エントリーと手仕舞いのタイミングと数量（100株単位）も表示されます。
1-2. トレードルールの概要
買い戦略の場合、ボリンジャーバンドの +1σ 超えでエントリーして上昇トレンドに乗り、ミドルバンドを割ったら決済します。
売り戦略の場合、ボリンジャーバンドの -1σ 割りでエントリーして下降トレンドに乗り、ミドルバンドを上抜けたら決済します。
1-3. ストラテジーの工夫点
200日移動平均線の傾きを見てトレンド方向にエントリーをしています。こうして勝率とペイオフレシオの成績を向上しています。
また、破産確率を抑えるために、リスク資金比率を 1.0% にして、ATR（ボラティリティ指標） を使って注文数を調整しています。
2. 売買ルール
2-1. 使用するチャート
日足チャートに限定します
2-2. 使用する指標
(1) ボリンジャーバンド（仕掛けと手仕舞いのシグナルに使用）
期間は80日に固定
上下バンドは ±1σ に固定
(2) 移動平均線（トレンドの方向を見るために使用）
期間は200日に固定
移動平均の値の前日との差がプラスのとき上向き、マイナスのとき下向きと判断
2-3. 買いのルール
セットアップ：ボリンジャーバンドの +1σ を価格が下から上に交差 かつ ミドルバンドと 200日移動平均線が上向き
仕掛け：翌日の寄り付きに成行で買う
手仕舞い：ボリンジャーバンドのミドルバンドを価格が上から下に交差したら、翌日の寄り付きに成行で売る
2-4. 売りのルール
セットアップ：ボリンジャーバンドの -1σ を価格が上から下に交差 かつ ミドルバンドと 200日移動平均線が下向き
仕掛け：翌日の寄り付きに成行で売る
手仕舞い：ボリンジャーバンドのミドルバンドを価格が下から上に交差したら、翌日の寄り付きに成行で買い戻す
2-5. 資金管理のルール
リスク資金比率：資産の 1.0%（許容損失 = 資産 × 1.0%）
注文数：許容損失 ÷ 2ATR（単元株数未満は切り捨て）
2-6. その他
仲介手数料：なし
ピラミッディング：なし
分割決済：なし
ドテン：しない
3. ストラテジーのパラメーター
次の項目が指定できます。
3-1. 期間の設定
Staer date : バックテストの検証期間の開始日を指定します
Stop date : バックテストの検証期間の終了日を指定します
3-2. トレンドとシグナルの表示
Show trend : チェックを入れると、バーの背景色が、トレンドが上昇のときは薄い赤で、下落のときは薄い青で表示されます
Show signal : チェックを入れると、エントリーと手仕舞いのシグナルを表示します（シグナルの出た翌日の寄り付きに売買をするので表示に1日のずれがあります）
3-3. 資金管理用の設定
Funds : トレード用の資金(円)
Risk rate : 許容損失を資金の何%にするかで指定します
「プロパティタブ」で設定する値は、このストラテジーでは有効ではありません。
4. バックテストの結果（例）
作者がバックテストを実施した結果をお知らせします。
対象銘柄：日経225構成銘柄すべて
対象期間：2000年1月4日～2024年12月30日
データ件数：12,886
勝率：33.45%
純利益：82,132,380
ペイオフレシオ：2.450
期待値：6,373.8
リスク資金比率：1.0%
破産確率：0.00%
