Crosby Ratio | QuantumResearch ⚖️ Crosby Ratio | QuantumResearch
A Heikin-Ashi Smoothed Momentum Oscillator for Trend Strength & Market Rotation
Inspired by the Original Work of Bitcoin Magazine Pro
🔗 www.bitcoinmagazinepro.com
📘 Overview
The Crosby Ratio, as originally conceptualized by Bitcoin Magazine Pro, is a powerful tool used to evaluate the momentum and directional strength of price movement by analyzing the slope of market trends in degrees.
This enhanced implementation by QuantumResearch builds on the original concept with a Pine Script version tailored for trading charts, integrating Heikin-Ashi smoothing, ATR scaling, and customizable visual modes to fit traders' unique styles.
🧠 What Is the Crosby Ratio?
At its core, the Crosby Ratio uses angular measurement to quantify price movement — translating price trend strength into degrees. This approach allows traders to:
📈 Identify when the market is exhibiting strong upward or downward pressure
🚨 Spot overextended or overheated trend conditions
⚖ Filter out short-term noise and focus on macro momentum
🔍 1. Key Innovations by QuantumResearch
✅ Heikin-Ashi Smoothing: Reduces noise and stabilizes price action before computing momentum angles
✅ Custom atan2() Angular Function: Measures the directional angle between smoothed price changes and ATR-based scaling
✅ Dynamic Threshold Bands: Color-coded zones highlight overbought/oversold momentum regions
✅ Fully Customizable Palette: Choose from 8 visual themes with automatic color adaptation
📊 2. Interpretation Guide
Crosby Value Interpretation
> +18° 🚀 Strong bullish trend acceleration
+13° to +18° 📈 Moderate upward momentum
-9° to +13° ⚖ Neutral/transition phase
-15° to -9° 📉 Moderate bearish pressure
< -15° 🛑 Strong bearish acceleration
The indicator also features background shading when values exceed key thresholds, improving visual clarity during trend inflection points.
📌 Ideal Use Cases
🔄 Rotational Momentum Strategies: Spot the strongest assets during rapid shifts
⚡ Breakout Filtering: Confirm whether breakouts have directional strength
🧘 Noise Reduction: Heikin-Ashi smoothing filters chaotic wicks, especially in crypto
📉 Bearish Exhaustion Detection: Quickly identify when bearish momentum might be overdone
🔗 Original Inspiration & Acknowledgment
This indicator draws its core idea and naming convention from the original Crosby Ratio developed and introduced by Bitcoin Magazine Pro in their excellent write-up:
🔗 The Crosby Ratio – Bitcoin Magazine Pro
Their work on quantifying market sentiment via angle-based momentum inspired this script adaptation for TradingView with added visual features, smoothing techniques, and alerts.
⚠️ Disclaimer
This indicator is a momentum oscillator and should be used in conjunction with other confirmation tools. Market dynamics can vary, and no single metric ensures profitable trades. Always apply proper risk management.
Cerca negli script per "profitable"
Rendon1 Swing Market Turns**Swing Market Turns Indicator**
This indicator identifies potential swing highs and swing lows by integrating Relative Strength Index (RSI), volume confirmation, and higher timeframe (HTF) levels to accurately detect market reversals and turning points. Specifically optimized for swing traders, this tool aims to pinpoint moments when price momentum is shifting, providing clear signals for trade entries and exits.
### How It Works:
- **RSI Divergence:** Detects momentum shifts through RSI overbought and oversold conditions.
- **Higher Timeframe Levels:** Confirms reversals using support and resistance levels from higher timeframes.
- **Volume Confirmation:** Ensures stronger validity of signals by checking if current volume exceeds the moving average of recent volume.
### Key Features:
- Visual labels on chart clearly indicating potential swing highs and lows.
- Customizable RSI period, RSI overbought/oversold thresholds, volume moving average length, and higher timeframe selections.
- Built-in alert conditions for immediate notifications when swing opportunities are detected.
### Recommended Use:
- Ideal for traders focusing on swing trading strategies, particularly those looking for high-probability turning points.
- Effective across multiple assets including forex, stocks, commodities, and crypto.
- Suitable for various intraday and higher timeframes, with customization options available.
### Settings:
- **RSI Period:** Adjust the sensitivity of RSI calculation.
- **Higher Timeframe:** Select the timeframe used for support/resistance reference.
- **RSI Overbought/Oversold:** Customize thresholds defining extreme RSI values.
- **Volume MA Length:** Specify the length for volume moving average calculation.
Feel free to customize the parameters to best fit your trading style and asset of choice.
**Disclaimer:**
This indicator does not guarantee profitable trades and should be used in conjunction with proper risk management and additional analysis methods.
Trend Confirmation StrategyComprehensive Trend Confirmation System
Indicator Features (Professional Description):
Comprehensive Trend Confirmation System is a versatile indicator meticulously designed to identify and confirm trend-based trading opportunities with exceptional efficiency. By seamlessly integrating analysis from a suite of leading technical tools, it aims to provide superior accuracy and reliability for informed trading decisions.
Key Features:
Intelligent Trend Identification: A robust trend analysis system that considers:
Adjustable Moving Averages: Utilizes three customizable moving average periods (fast, medium, slow) with user-selectable lengths and types (SMA, EMA, WMA, VWMA) to accurately determine the prevailing trend across different timeframes.
In-depth Price Action Analysis: Examines the formation of Higher Highs/Higher Lows (uptrend) and Lower Highs/Lower Lows (downtrend) to validate price direction.
Average Directional Index (ADX) with Adjustable Threshold: Measures the strength of a trend and employs the comparison between +DI and -DI to pinpoint the dominant momentum, featuring a customizable threshold to filter out weak signals.
Multi-Factor Signal Confirmation System: Enhances the reliability of trading signals through verification from four distinct confirmation tools:
Volume Analysis with Average Reference: Assesses whether trading volume supports price movements by comparing it to historical averages.
Relative Strength Index (RSI) with Reference Levels: Measures price momentum and identifies overbought/oversold conditions to confirm trend strength.
Moving Average Convergence Divergence (MACD) Divergence and Crossovers: Detects shifts in momentum and potential trend changes through the relationship between the MACD line and the Signal line.
Stochastic Oscillator with Reference Levels: Measures the current price's position relative to its historical range to evaluate overbought/oversold conditions and potential reversal opportunities.
Intelligent Signal Generation Logic:
Buy Signal: Triggered when a strong uptrend is identified (meeting defined criteria) and confirmed by at least three out of the four confirmation tools.
Sell Signal: Triggered when a strong downtrend is identified (meeting defined criteria) and confirmed by at least three out of the four confirmation tools.
User-Friendly Visualizations:
Moving Averages (MA): Displays three MA lines on the chart with user-configurable colors (default: fast-blue, medium-orange, slow-red) for easy visual trend analysis.
Clear Buy and Sell Signal Symbols: Presents distinct green upward-pointing triangles for buy signals and red downward-pointing triangles for sell signals at the corresponding candlestick.
Dynamic Candlestick Color Coding: Candlesticks are dynamically colored green upon a buy signal and red upon a sell signal for quick identification of trading opportunities.
Highly Customizable Parameters: Users have extensive control over the indicator's parameters, including:
Lengths and types of Moving Averages.
Length and Threshold of the ADX.
Length of the RSI.
Parameters for the MACD (Fast Length, Slow Length, Signal Length).
Parameters for the Stochastic Oscillator (%K Length, %D Length, Smoothing).
Ideal For:
Traders seeking a robust tool to accurately identify and confirm market trends.
Individuals aiming to reduce false signals and enhance the precision of their trading decisions.
Traders employing trend-following strategies in markets with clear directional movement.
Important Note:
While Comprehensive Trend Confirmation System is engineered to improve trading accuracy, no indicator can guarantee 100% profitable trades. Users are advised to utilize this indicator in conjunction with relevant fundamental analysis and sound risk management practices for optimal trading outcomes.
Multi-MA Strategy Analyzer with BacktestMulti-MA Strategy Analyzer with Backtest
This TradingView Pine Script indicator is designed to analyze multiple moving averages (SMA or EMA) dynamically and identify the most profitable one based on historical performance.
Features
Dynamic MA Range:
Specify a minLength, maxLength, and step size.
Automatically calculates up to 20 MAs.
Custom MA Calculation:
Uses custom SMA and EMA implementations to support dynamic length values.
Buy/Sell Logic:
Buy when price crosses above a MA.
Sell when price crosses below.
Supports both long and short trades.
Performance Tracking:
Tracks PnL, number of trades, win rate, average profit, and drawdown.
Maintains individual stats for each MA.
Best MA Detection:
Automatically highlights the best-performing MA.
Optional showBestOnly toggle to focus only on the best line and its stats.
Visualization:
Up to 20 plot() calls (static) for MAs.
Green highlight for the best MA.
Color-coded result table and chart.
Table View
When showBestOnly = false, the table displays all MAs with stats.
When showBestOnly = true, the table displays only the best MA with a summary row.
Includes:
Best MA length
Total PnL
Number of trades
Win rate
Avg PnL per trade
Max Drawdown
Configuration
minLength (default: 10)
maxLength (default: 200)
step (default: 10)
useEMA: Toggle between EMA and SMA
showBestOnly: Focus on best-performing MA only
Notes
MA plotting is static, limited to 20 total.
Table supports highlighting and is optimized for performance.
Script is structured to run efficiently using arrays and simple int where required.
Potential Extensions
Add visual buy/sell arrows
Export stats to CSV
Strategy tester conversion
Custom date range filtering for backtesting
Author: Muhammad Wasim
Version: 1.0
Adaptive Regression Channel [MissouriTim]The Adaptive Regression Channel (ARC) is a technical indicator designed to empower traders with a clear, adaptable, and precise view of market trends and price boundaries. By blending advanced statistical techniques with real-time market data, ARC delivers a comprehensive tool that dynamically adjusts to price action, volatility, volume, and momentum. Whether you’re navigating the fast-paced world of cryptocurrencies, the steady trends of stocks, or the intricate movements of FOREX pairs, ARC provides a robust framework for identifying opportunities and managing risk.
Core Components
1. Color-Coded Regression Line
ARC’s centerpiece is a linear regression line derived from a Weighted Moving Average (WMA) of closing prices. This line adapts its calculation period based on market volatility (via ATR) and is capped between a minimum of 20 bars and a maximum of 1.5 times the user-defined base length (default 100). Visually, it shifts colors to reflect trend direction: green for an upward slope (bullish) and red for a downward slope (bearish), offering an instant snapshot of market sentiment.
2. Dynamic Residual Channels
Surrounding the regression line are upper (red) and lower (green) channels, calculated using the standard deviation of residuals—the difference between actual closing prices and the regression line. This approach ensures the channels precisely track how closely prices follow the trend, rather than relying solely on overall price volatility. The channel width is dynamically adjusted by a multiplier that factors in:
Volatility: Measured through the Average True Range (ATR), widening channels during turbulent markets.
Trend Strength: Based on the regression slope, expanding channels in strong trends and contracting them in consolidation phases.
3. Volume-Weighted Moving Average (VWMA)
Plotted in orange, the VWMA overlays a volume-weighted price trend, emphasizing movements backed by significant trading activity. This complements the regression line, providing additional confirmation of trend validity and potential breakout strength.
4. Scaled RSI Overlay
ARC features a Relative Strength Index (RSI) overlay, plotted in purple and scaled to hover closely around the regression line. This compact display reflects momentum shifts within the trend’s context, keeping RSI visible on the price chart without excessive swings. User-defined overbought (default 70) and oversold (default 30) levels offer reference points for momentum analysis."
Technical Highlights
ARC leverages a volatility-adjusted lookback period, residual-based channel construction, and multi-indicator integration to achieve high accuracy. Its parameters—such as base length, channel width, ATR period, and RSI length—are fully customizable, allowing traders to tailor it to their specific needs.
Why Choose ARC?
ARC stands out for its adaptability and precision. The residual-based channels offer tighter, more relevant support and resistance levels compared to standard volatility measures, while the dynamic adjustments ensure it performs well in both trending and ranging markets. The inclusion of VWMA and scaled RSI adds depth, merging trend, volume, and momentum into a single, cohesive overlay. For traders seeking a versatile, all-in-one indicator, ARC delivers actionable insights with minimal noise.
Best Ways to Use the Adaptive Regression Channel (ARC)
The Adaptive Regression Channel (ARC) is a flexible tool that supports a variety of trading strategies, from trend-following to breakout detection. Below are the most effective ways to use ARC, along with practical tips for maximizing its potential. Adjustments to its settings may be necessary depending on the timeframe (e.g., intraday vs. daily) and the asset being traded (e.g., stocks, FOREX, cryptocurrencies), as each market exhibits unique volatility and behavior.
1. Trend Following
• How to Use: Rely on the regression line’s color to guide your trades. A green line (upward slope) signals a bullish trend—consider entering or holding long positions. A red line (downward slope) indicates a bearish trend—look to short or exit longs.
• Best Practice: Confirm the trend with the VWMA (orange line). Price above the VWMA in a green uptrend strengthens the bullish case; price below in a red downtrend reinforces bearish momentum.
• Adjustment: For short timeframes like 15-minute crypto charts, lower the Base Regression Length (e.g., to 50) for quicker trend detection. For weekly stock charts, increase it (e.g., to 200) to capture broader movements.
2. Channel-Based Trades
• How to Use: Use the upper channel (red) as resistance and the lower channel (green) as support. Buy when the price bounces off the lower channel in an uptrend, and sell or short when it rejects the upper channel in a downtrend.
• Best Practice: Check the scaled RSI (purple line) for momentum cues. A low RSI (e.g., near 30) at the lower channel suggests a stronger buy signal; a high RSI (e.g., near 70) at the upper channel supports a sell.
• Adjustment: In volatile crypto markets, widen the Base Channel Width Coefficient (e.g., to 2.5) to reduce false signals. For stable FOREX pairs (e.g., EUR/USD), a narrower width (e.g., 1.5) may work better.
3. Breakout Detection
• How to Use: Watch for price breaking above the upper channel (bullish breakout) or below the lower channel (bearish breakout). These moves often signal strong momentum shifts.
• Best Practice: Validate breakouts with VWMA position—price above VWMA for bullish breaks, below for bearish—and ensure the regression line’s slope aligns (green for up, red for down).
• Adjustment: For fast-moving assets like crypto on 1-hour charts, shorten ATR Length (e.g., to 7) to make channels more reactive. For stocks on daily charts, keep it at 14 or higher for reliability.
4. Momentum Analysis
• How to Use: The scaled RSI overlay shows momentum relative to the regression line. Rising RSI in a green uptrend confirms bullish strength; falling RSI in a red downtrend supports bearish pressure.
• Best Practice: Look for RSI divergences—e.g., price hitting new highs at the upper channel while RSI flattens or drops could signal an impending reversal.
• Adjustment: Reduce RSI Length (e.g., to 7) for intraday trading in FOREX or crypto to catch short-term momentum shifts. Increase it (e.g., to 21) for longer-term stock trades.
5. Range Trading
• How to Use: When the regression line’s slope is near zero (flat) and channels are tight, ARC indicates a ranging market. Buy near the lower channel and sell near the upper channel, targeting the regression line as the mean price.
• Best Practice: Ensure VWMA hovers close to the regression line to confirm the range-bound state.
• Adjustment: For low-volatility stocks on daily charts, use a moderate Base Regression Length (e.g., 100) and tight Base Channel Width (e.g., 1.5). For choppy crypto markets, test shorter settings.
Optimization Strategies
• Timeframe Customization: Adjust ARC’s parameters to match your trading horizon. Short timeframes (e.g., 1-minute to 1-hour) benefit from lower Base Regression Length (20–50) and ATR Length (7–10) for agility, while longer timeframes (e.g., daily, weekly) favor higher values (100–200 and 14–21) for stability.
• Asset-Specific Tuning:
○ Stocks: Use longer lengths (e.g., 100–200) and moderate widths (e.g., 1.8) for stable equities; tweak ATR Length based on sector volatility (shorter for tech, longer for utilities).
○ FOREX: Set Base Regression Length to 50–100 and Base Channel Width to 1.5–2.0 for smoother trends; adjust RSI Length (e.g., 10–14) based on pair volatility.
○ Crypto: Opt for shorter lengths (e.g., 20–50) and wider widths (e.g., 2.0–3.0) to handle rapid price swings; use a shorter ATR Length (e.g., 7) for quick adaptation.
• Backtesting: Test ARC on historical data for your asset and timeframe to optimize settings. Evaluate how often price respects channels and whether breakouts yield profitable trades.
• Enhancements: Pair ARC with volume surges, key support/resistance levels, or candlestick patterns (e.g., doji at channel edges) for higher-probability setups.
Practical Considerations
ARC’s adaptability makes it suitable for diverse markets, but its performance hinges on proper calibration. Cryptocurrencies, with their high volatility, may require shorter, wider settings to capture rapid moves, while stocks on longer timeframes benefit from broader, smoother configurations. FOREX pairs often fall in between, depending on their inherent volatility. Experiment with the adjustable parameters to align ARC with your trading style and market conditions, ensuring it delivers the precision and reliability you need.
FVG Visual Trading ToolHow to Use the FVG Tool
1. Identify the FVG Zone
Bullish FVG: Look for green boxes that represent potential support zones. These are areas where price is likely to retrace before continuing upward.
Bearish FVG: Look for red boxes that represent potential resistance zones. These are areas where price is likely to retrace before continuing downward.
2. Set Up Your Trade
Entry: Place a limit order at the retracement zone (inside the FVG box). This ensures you enter the trade when the price retraces into the imbalance.
Stop-Loss (SL): Place your stop-loss just below the FVG box for bullish trades or just above the FVG box for bearish trades. The tool provides a suggested SL level.
Take-Profit (TP): Set your take-profit level at a 2:1 risk-reward ratio (or higher). The tool provides a suggested target level.
3. Let the Trade Run
Once your trade is set up, let it play out. Avoid micromanaging the trade unless market conditions change drastically.
Step-by-Step Example
Bullish FVG Trade
Identify the FVG:
A green box appears, indicating a bullish FVG.
The tool provides the target price (e.g., 0.6371) and the stop-loss level (e.g., 0.6339).
Set Up the Trade:
Place a limit buy order at the retracement zone (inside the green box).
Set your stop-loss just below the FVG box (e.g., 0.6339).
Set your take-profit at a 2:1 risk-reward ratio or the suggested target (e.g., 0.6371).
Monitor the Trade:
Wait for the price to retrace into the FVG zone and trigger your limit order.
Let the trade run until it hits the take-profit or stop-loss.
Bearish FVG Trade
Identify the FVG:
A red box appears, indicating a bearish FVG.
The tool provides the target price and the stop-loss level.
Set Up the Trade:
Place a limit sell order at the retracement zone (inside the red box).
Set your stop-loss just above the FVG box.
Set your take-profit at a 2:1 risk-reward ratio or the suggested target.
Monitor the Trade:
Wait for the price to retrace into the FVG zone and trigger your limit order.
Let the trade run until it hits the take-profit or stop-loss.
Key Features of the Tool in Action
Visual Clarity:
The green and red boxes clearly show the FVG zones, making it easy to identify potential trade setups.
Labels provide the target price and stop-loss level for quick decision-making.
Risk-Reward Management:
The tool encourages disciplined trading by providing predefined SL and TP levels.
A 2:1 risk-reward ratio ensures that profitable trades outweigh losses.
Hands-Off Execution:
By placing limit orders, you can let the trade execute automatically without needing to monitor the market constantly.
Best Practices
Trade in the Direction of the Trend:
Use higher timeframes (e.g., 4-hour or daily) to identify the overall trend.
Focus on bullish FVGs in an uptrend and bearish FVGs in a downtrend.
Combine with Confirmation Signals:
Look for additional confirmation, such as candlestick patterns (e.g., engulfing candles) or indicator signals (e.g., RSI, MACD).
Adjust Parameters for Volatility:
For highly volatile markets, consider increasing the stop-loss percentage to avoid being stopped out prematurely.
Avoid Overtrading:
Not every FVG is a good trading opportunity. Be selective and only trade setups that align with your strategy.
Backtest and Optimize:
Use historical data to test the tool and refine your approach before trading live.
Common Mistakes to Avoid
Entering Without Confirmation:
Wait for price to retrace into the FVG zone before entering a trade.
Avoid chasing trades that have already moved away from the zone.
Ignoring Risk Management:
Always use a stop-loss to protect your account.
Stick to a consistent risk-reward ratio.
Trading Against the Trend:
Avoid taking trades that go against the prevailing market trend unless there is strong evidence of a reversal.
Final Thoughts
The FVG Visual Trading Tool is a powerful aid for identifying high-probability trade setups. By following the steps outlined above, you can use the tool to trade with confidence and discipline. Remember, no tool guarantees success, so always combine it with sound trading principles and proper risk management
Williams Fractals Ultimate (Donchian Adjusted)Williams Fractals Ultimate (Donchian Adjusted)
Understanding Williams Fractals
Williams Fractals are a simple yet powerful tool used to identify potential turning points in the market. They highlight local highs (up fractals) and local lows (down fractals) based on a set period.
An up fractal appears when a price peak is higher than the surrounding prices.
A down fractal appears when a price low is lower than the surrounding prices.
Fractals help traders spot support and resistance levels, potential trend reversals, and price breakout zones.
Why Adjust Fractals with the Donchian Channel?
The standard Williams Fractals method identifies local highs and lows without considering broader market context. This script enhances fractal accuracy by integrating the Donchian Channel, which tracks the highest highs and lowest lows over a set period.
- The Donchian Baseline is calculated as the average of the highest high and lowest low over a selected period.
- Fractals are filtered based on this baseline:
Up Fractals are only shown if they are above the Donchian baseline.
Down Fractals are only shown if they are below the Donchian baseline.
This filtering method removes weak signals and ensures that only relevant fractals aligned with market structure are displayed.
Key Features of the Script
Customizable Fractal & Donchian Periods – Allows traders to fine-tune fractal sensitivity.
Donchian-Based Filtering – Reduces noise and highlights meaningful fractals.
Fractal ZigZag Line (Optional) – Helps visualize price swings more clearly.
Why Is This So Effective?
Stronger trend signals – Filtering with the Donchian baseline eliminates unreliable fractals.
Clearer price action – The optional ZigZag line visually connects significant highs and lows.
Easy trend identification – Helps traders confirm breakout zones and key price levels.
This script is a technical analysis tool and does not guarantee profitable trades. Always combine it with other indicators and risk management strategies before making trading decisions.
Alpha Wave System @DaviddTechAlpha Wave DaviddTech System by DaviddTech is an advanced, meticulously engineered trading indicator adhering strictly to the DaviddTech methodology. Rather than simply combining popular indicators, Alpha Wave strategically integrates specially-selected technical components—each optimized to enhance their combined strengths while neutralizing individual weaknesses, providing traders with clear, consistent, and high-probability trading signals.
Valid Setup:
🎯 Why This Combination Matters:
Quantum Adaptive Moving Average (Baseline):
This advanced adaptive MA provides superior responsiveness to market shifts by dynamically adjusting its sensitivity, clearly indicating the primary market direction and reducing lag compared to standard moving averages.
WavePulse Indicator (CoralChannel-based Confirmation #1):
Precisely detects shifts in momentum and price acceleration, allowing traders to anticipate trend continuation or reversals effectively, significantly enhancing trade accuracy.
Quantum Channel (G-Channel-based Confirmation #2):
Dynamically captures price volatility ranges, offering reliable trend structure validation and clear support/resistance channels, further increasing signal reliability.
Momentum Density (Volatility Filter):
Ensures traders enter only during optimal volatility conditions by quantifying momentum intensity, effectively filtering out low-quality, low-momentum scenarios.
Dynamic ATR-based Trailing Stop (Exit System):
Automatically manages trade exits with optimized ATR-based stop levels, systematically securing profits while effectively managing risk.
These meticulously integrated components reinforce each other's strengths, providing traders with a robust, disciplined, and clearly structured approach aligned with the DaviddTech methodology.
🔥 Latest Update – Enhanced BUY & SELL Signals:
Alpha Wave now clearly displays automated BUY and SELL signals directly on your chart, coupled with a comprehensive dashboard table for immediate signal validation. Signals appear only when all components—including baseline, confirmations, and volatility—are in alignment, significantly improving trade accuracy and confidence.
📌 How Traders Benefit from the New Signals:
BUY Signal: Execute long trades when Quantum Adaptive MA signals bullish, confirmed by bullish WavePulse momentum, bullish Quantum Channel structure, and strong Momentum Density readings.
SELL Signal: Clearly marked for entering short positions under bearish market conditions verified through Quantum Adaptive MA, WavePulse bearish momentum, Quantum Channel confirmation, and sufficient Momentum Density.
Signal Validation: A dedicated dashboard provides immediate visual strength metrics, allowing traders to quickly validate signals before execution, significantly enhancing trading discipline and consistency.
📊 Recommended DaviddTech Trading Plan:
Baseline: Determine overall market direction using Quantum Adaptive MA. Only trade in the indicated baseline direction.
Confirmations: Validate potential entries with WavePulse and Quantum Channel alignment.
Volatility Filter: Confirm sufficient market volatility with Momentum Density before entry.
Trailing Stop Loss: Manage risk and secure profits using the dynamic ATR-based trailing stop system.
Entries & Exits: Only execute trades when signals and dashboard components unanimously align.
🖼️ Visual Examples:
Alpha Wave by DaviddTech clearly demonstrates how an intelligently integrated system provides significantly superior trading insights compared to standalone indicators, ensuring precise, disciplined, and profitable market entries and exits across all trading environments.
CVD Oscillator - Short Term SwiftEdgeOverview
The CVD Oscillator - Short Term is a technical indicator designed to assist traders in identifying short-term buying and selling pressure in the market. It calculates the Cumulative Volume Delta (CVD) to measure the net volume difference between buying and selling activity, displayed as an oscillator in a separate panel. This indicator is tailored for short-term trading strategies, such as scalping or day trading, on low timeframes (e.g., 1-minute, 5-minute, or 15-minute charts).
How It Works
Cumulative Volume Delta (CVD): The indicator calculates CVD by assigning volume to buyers (when close > open) or sellers (when close < open). If close = open, the volume is neutral.
Short-Term Focus: The CVD is calculated over a user-defined lookback period (default: 10 candles), making it sensitive to recent market activity.
Normalization: The raw CVD is normalized by dividing it by the average volume (over a short period, default: 5 candles) and scaled to fit within a range of -100 to +100, creating an oscillator-like behavior.
Reset Options: Users can reset the CVD at specific intervals (e.g., every minute, 5 minutes, 15 minutes, or daily) to focus on intraday movements.
Live CVD Value: The raw (unnormalized) CVD value is displayed as a label on each candle for real-time monitoring.
Key Features
Customizable Lookback Period: Adjust the number of recent candles (default: 10) to calculate CVD, allowing for precise short-term analysis.
Flexible Reset Periods: Choose to reset the CVD every 1 minute, 5 minutes, 15 minutes, daily, or never, to suit your trading style.
Normalized Oscillator: The CVD is scaled between -100 and +100, making it easier to visualize short-term momentum.
Live CVD Labels: Displays the raw CVD value on each candle, with options to position the label above or below the oscillator line.
How to Use
Add to Chart: Apply the indicator to your chart on a low timeframe (e.g., 1m, 5m, or 15m) for short-term trading.
Interpret the Oscillator:
Above 0 (Green): Indicates buying pressure dominates.
Below 0 (Red): Indicates selling pressure dominates.
Near 0: Suggests neutral market conditions.
Monitor Live CVD: Use the raw CVD value (shown in the label) to assess the exact net volume difference over the lookback period.
Combine with Other Tools: Use the oscillator alongside price action, support/resistance levels, or other indicators to confirm trading decisions.
Adjust Settings:
CVD Lookback Period: Set to a small value (e.g., 5-20 candles) for scalping.
CVD Reset Period: Choose "1m" or "5m" for intraday resets to focus on very short-term trends.
Volume Average Length: Use a short length (e.g., 3-5) for faster responsiveness.
Scale Factor: Increase (e.g., 2.0-3.0) to amplify small changes in CVD.
Settings
CVD Reset Period: Defines when to reset the CVD calculation ("None", "D" for daily, "15m", "5m", "1m").
CVD Lookback Period (Candles): Number of recent candles to calculate CVD (default: 10).
Volume Average Length: Period for averaging volume to normalize CVD (default: 5).
CVD Scale Factor: Adjusts the sensitivity of the normalized CVD (default: 2.0).
CVD Label Position: Choose to display the raw CVD label above or below the oscillator line.
CVD Label Color: Customize the color of the CVD label (default: white).
Limitations
Not a Standalone Tool: This indicator should be used in conjunction with other technical analysis tools, as it does not guarantee profitable trades.
Volume Dependency: The accuracy of CVD relies on the quality of volume data provided by your broker or exchange.
Short-Term Focus: The indicator is optimized for low timeframes and may produce noise on higher timeframes unless adjusted.
No Predictive Claims: The CVD Oscillator reflects past and current market activity but does not predict future price movements.
Notes
This indicator is designed for informational purposes and does not constitute financial advice. Trading involves risk, and past performance is not indicative of future results.
Test the indicator on a demo account to understand its behavior before using it in live trading.
Feedback is welcome! If you have suggestions for improvements, feel free to share them in the comments.
[GYTS-CE] Market Regime Detector🧊 Market Regime Detector (Community Edition)
🌸 Part of GoemonYae Trading System (GYTS) 🌸
🌸 --------- INTRODUCTION --------- 🌸
💮 What is the Market Regime Detector?
The Market Regime Detector is an advanced, consensus-based indicator that identifies the current market state to increase the probability of profitable trades. By distinguishing between trending (bullish or bearish) and cyclic (range-bound) market conditions, this detector helps you select appropriate tactics for different environments. Instead of forcing a single strategy across all market conditions, our detector allows you to adapt your approach based on real-time market behaviour.
💮 The Importance of Market Regimes
Markets constantly shift between different behavioural states or "regimes":
• Bullish trending markets - characterised by sustained upward price movement
• Bearish trending markets - characterised by sustained downward price movement
• Cyclic markets - characterised by range-bound, oscillating behaviour
Each regime requires fundamentally different trading approaches. Trend-following strategies excel in trending markets but fail in cyclic ones, while mean-reversion strategies shine in cyclic markets but underperform in trending conditions. Detecting these regimes is essential for successful trading, which is why we've developed the Market Regime Detector to accurately identify market states using complementary detection methods.
🌸 --------- KEY FEATURES --------- 🌸
💮 Consensus-Based Detection
Rather than relying on a single method, our detector employs two complementary detection methodologies that analyse different aspects of market behaviour:
• Dominant Cycle Average (DCA) - analyzes price movement relative to its lookback period, a proxy for the dominant cycle
• Volatility Channel - examines price behaviour within adaptive volatility bands
These diverse perspectives are synthesised into a robust consensus that minimises false signals while maintaining responsiveness to genuine regime changes.
💮 Dominant Cycle Framework
The Market Regime Detector uses the concept of dominant cycles to establish a reference framework. You can input the dominant cycle period that best represents the natural rhythm of your market, providing a stable foundation for regime detection across different timeframes.
💮 Intuitive Parameter System
We've distilled complex technical parameters into intuitive controls that traders can easily understand:
• Adaptability - how quickly the detector responds to changing market conditions
• Sensitivity - how readily the detector identifies transitions between regimes
• Consensus requirement - how much agreement is needed among detection methods
This approach makes the detector accessible to traders of all experience levels while preserving the power of the underlying algorithms.
💮 Visual Market Feedback
The detector provides clear visual feedback about the current market regime through:
• Colour-coded chart backgrounds (purple shades for bullish, pink for bearish, yellow for cyclic)
• Colour-coded price bars
• Strength indicators showing the degree of consensus
• Customizable colour schemes to match your preferences or trading system
💮 Integration in the GYTS suite
The Market Regime Detector is compatible with the GYTS Suite , i.e. it passes the regime into the 🎼 Order Orchestrator where you can set how to trade the trending and cyclic regime.
🌸 --------- CONFIGURATION SETTINGS --------- 🌸
💮 Adaptability
Controls how quickly the Market Regime detector adapts to changing market conditions. You can see it as a low-frequency, long-term change parameter:
Very Low: Very slow adaptation, most stable but may miss regime changes
Low: Slower adaptation, more stability but less responsiveness
Normal: Balanced between stability and responsiveness
High: Faster adaptation, more responsive but less stable
Very High: Very fast adaptation, highly responsive but may generate false signals
This setting affects lookback periods and filter parameters across all detection methods.
💮 Sensitivity
Controls how sensitive the detector is to market regime transitions. This acts as a high-frequency, short-term change parameter:
Very Low: Requires substantial evidence to identify a regime change
Low: Less sensitive, reduces false signals but may miss some transitions
Normal: Balanced sensitivity suitable for most markets
High: More sensitive, detects subtle regime changes but may have more noise
Very High: Very sensitive, detects minor fluctuations but may produce frequent changes
This setting affects thresholds for regime detection across all methods.
💮 Dominant Cycle Period
This parameter allows you to specify the market's natural rhythm in bars. This represents a complete market cycle (up and down movement). Finding the right value for your specific market and timeframe might require some experimentation, but it's a crucial parameter that helps the detector accurately identify regime changes. Most of the times the cycle is between 20 and 40 bars.
💮 Consensus Mode
Determines how the signals from both detection methods are combined to produce the final market regime:
• Any Method (OR) : Signals bullish/bearish if either method detects that regime. If methods conflict (one bullish, one bearish), the stronger signal wins. More sensitive, catches more regime changes but may produce more false signals.
• All Methods (AND) : Signals only when both methods agree on the regime. More conservative, reduces false signals but might miss some legitimate regime changes.
• Weighted Decision : Balances both methods with equal weighting. Provides a middle ground between sensitivity and stability.
Each mode also calculates a continuous regime strength value that's used for colour intensity in the 'unconstrained' display mode.
💮 Display Mode
Choose how to display the market regime colours:
• Unconstrained regime: Shows the regime strength as a continuous gradient. This provides more nuanced visualisation where the intensity of the colour indicates the strength of the trend.
• Consensus only: Shows only the final consensus regime with fixed colours based on the detected regime type.
The background and bar colours will change to indicate the current market regime:
• Purple shades: Bullish trending market (darker purple indicates stronger bullish trend)
• Pink shades: Bearish trending market (darker pink indicates stronger bearish trend)
• Yellow: Cyclic (range-bound) market
💮 Custom Colour Options
The Market Regime Detector allows you to customize the colour scheme to match your personal preferences or to coordinate with other indicators:
• Use custom colours: Toggle to enable your own colour choices instead of the default scheme
• Transparency: Adjust the transparency level of all regime colours
• Bullish colours: Define custom colours for strong, medium, weak, and very weak bullish trends
• Bearish colours: Define custom colours for strong, medium, weak, and very weak bearish trends
• Cyclic colour: Define a custom colour for cyclic (range-bound) market conditions
🌸 --------- DETECTION METHODS --------- 🌸
💮 Dominant Cycle Average (DCA)
The Dominant Cycle Average method forms a key part of our detection system:
1. Theoretical Foundation :
The DCA method builds on cycle analysis and the observation that in trending markets, price consistently remains on one side of a moving average calculated using the dominant cycle period. In contrast, during cyclic markets, price oscillates around this average.
2. Calculation Process :
• We calculate a Simple Moving Average (SMA) using the specified lookback period - a proxy for the dominant cycle period
• We then analyse the proportion of time that price spends above or below this SMA over a lookback window. The theory is that the price should cross the SMA each half cycle, assuming that the dominant cycle period is correct and price follows a sinusoid.
• This lookback window is adaptive, scaling with the dominant cycle period (controlled by the Adaptability setting)
• The different values are standardised and normalised to possess more resolving power and to be more robust to noise.
3. Regime Classification :
• When the normalised proportion exceeds a positive threshold (determined by Sensitivity setting), the market is classified as bullish trending
• When it falls below a negative threshold, the market is classified as bearish trending
• When the proportion remains between these thresholds, the market is classified as cyclic
💮 Volatility Channel
The Volatility Channel method complements the DCA method by focusing on price movement relative to adaptive volatility bands:
1. Theoretical Foundation :
This method is based on the observation that trending markets tend to sustain movement outside of normal volatility ranges, while cyclic markets tend to remain contained within these ranges. By creating adaptive bands that adjust to current market volatility, we can detect when price behaviour indicates a trending or cyclic regime.
2. Calculation Process :
• We first calculate a smooth base channel center using a low pass filter, creating a noise-reduced centreline for price
• True Range (TR) is used to measure market volatility, which is then smoothed and scaled by the deviation factor (controlled by Sensitivity)
• Upper and lower bands are created by adding and subtracting this scaled volatility from the centreline
• Price is smoothed using an adaptive A2RMA filter, which has a very flat and stable behaviour, to reduce noise while preserving trend characteristics
• The position of this smoothed price relative to the bands is continuously monitored
3. Regime Classification :
• When smoothed price moves above the upper band, the market is classified as bullish trending
• When smoothed price moves below the lower band, the market is classified as bearish trending
• When price remains between the bands, the market is classified as cyclic
• The magnitude of price's excursion beyond the bands is used to determine trend strength
4. Adaptive Behaviour :
• The smoothing periods and deviation calculations automatically adjust based on the Adaptability setting
• The measured volatility is calculated over a period proportional to the dominant cycle, ensuring the detector works across different timeframes
• Both the center line and the bands adapt dynamically to changing market conditions, making the detector responsive yet stable
This method provides a unique perspective that complements the DCA approach, with the consensus mechanism synthesising insights from both methods.
🌸 --------- USAGE GUIDE --------- 🌸
💮 Starting with Default Settings
The default settings (Normal for Adaptability and Sensitivity, Weighted Decision for Consensus Mode) provide a balanced starting point suitable for most markets and timeframes. Begin by observing how these settings identify regimes in your preferred instruments.
💮 Finding the Optimal Dominant Cycle
The dominant cycle period is a critical parameter. Here are some approaches to finding an appropriate value:
• Start with typical values, usually something around 25 works well
• Visually identify the average distance between significant peaks and troughs
• Experiment with different values and observe which provides the most stable regime identification
• Consider using cycle-finding indicators to help identify the natural rhythm of your market
💮 Adjusting Parameters
• If you notice too many regime changes → Decrease Sensitivity or increase Consensus requirement
• If regime changes seem delayed → Increase Adaptability
• If a trending regime is not detected, the market is automatically assigned to be in a cyclic state
• If you want to see more nuanced regime transitions → Try the "unconstrained" display mode (note that this will not affect the output to other indicators)
💮 Trading Applications
Regime-Specific Strategies:
• Bullish Trending Regime - Use trend-following strategies, trail stops wider, focus on breakouts, consider holding positions longer, and emphasize buying dips
• Bearish Trending Regime - Consider shorts, tighter stops, focus on breakdown points, sell rallies, implement downside protection, and reduce position sizes
• Cyclic Regime - Apply mean-reversion strategies, trade range boundaries, apply oscillators, target definable support/resistance levels, and use profit-taking at extremes
Strategy Switching:
Create a set of rules for each market regime and switch between them based on the detector's signal. This approach can significantly improve performance compared to applying a single strategy across all market conditions.
GYTS Suite Integration:
• In the GYTS 🎼 Order Orchestrator, select the '🔗 STREAM-int 🧊 Market Regime' as the market regime source
• Note that the consensus output (i.e. not the "unconstrained" display) will be used in this stream
• Create different strategies for trending (bullish/bearish) and cyclic regimes. The GYTS 🎼 Order Orchestrator is specifically made for this.
• The output stream is actually very simple, and can possibly be used in indicators and strategies as well. It outputs 1 for bullish, -1 for bearish and 0 for cyclic regime.
🌸 --------- FINAL NOTES --------- 🌸
💮 Development Philosophy
The Market Regime Detector has been developed with several key principles in mind:
1. Robustness - The detection methods have been rigorously tested across diverse markets and timeframes to ensure reliable performance.
2. Adaptability - The detector automatically adjusts to changing market conditions, requiring minimal manual intervention.
3. Complementarity - Each detection method provides a unique perspective, with the collective consensus being more reliable than any individual method.
4. Intuitiveness - Complex technical parameters have been abstracted into easily understood controls.
💮 Ongoing Refinement
The Market Regime Detector is under continuous development. We regularly:
• Fine-tune parameters based on expanded market data
• Research and integrate new detection methodologies
• Optimise computational efficiency for real-time analysis
Your feedback and suggestions are very important in this ongoing refinement process!
Gradient Trend Filter STRATEGY [ChartPrime/PineIndicators]This strategy is based on the Gradient Trend Filter indicator developed by ChartPrime. Full credit for the concept and indicator goes to ChartPrime.
The Gradient Trend Filter Strategy is designed to execute trades based on the trend analysis and filtering system provided by the Gradient Trend Filter indicator. It integrates a noise-filtered trend detection system with a color-gradient visualization, helping traders identify trend strength, momentum shifts, and potential reversals.
How the Gradient Trend Filter Strategy Works
1. Noise Filtering for Smoother Trends
To reduce false signals caused by market noise, the strategy applies a three-stage smoothing function to the source price. This function ensures that trend shifts are detected more accurately, minimizing unnecessary trade entries and exits.
The filter is based on an Exponential Moving Average (EMA)-style smoothing technique.
It processes price data in three successive passes, refining the trend signal before generating trade entries.
This filtering technique helps eliminate minor fluctuations and highlights the true underlying trend.
2. Multi-Layered Trend Bands & Color-Based Trend Visualization
The Gradient Trend Filter constructs multiple trend bands around the filtered trend line, acting as dynamic support and resistance zones.
The mid-line changes color based on the trend direction:
Green for uptrends
Red for downtrends
A gradient cloud is formed around the trend line, dynamically shifting colors to provide early warning signals of trend reversals.
The outer bands function as potential support and resistance, helping traders determine stop-loss and take-profit zones.
Visualization elements used in this strategy:
Trend Filter Line → Changes color between green (bullish) and red (bearish).
Trend Cloud → Dynamically adjusts color based on trend strength.
Orange Markers → Appear when a trend shift is confirmed.
Trade Entry & Exit Conditions
This strategy automatically enters trades based on confirmed trend shifts detected by the Gradient Trend Filter.
1. Trade Entry Rules
Long Entry:
A bullish trend shift is detected (trend direction changes to green).
The filtered trend value crosses above zero, confirming upward momentum.
The strategy enters a long position.
Short Entry:
A bearish trend shift is detected (trend direction changes to red).
The filtered trend value crosses below zero, confirming downward momentum.
The strategy enters a short position.
2. Trade Exit Rules
Closing a Long Position:
If a bearish trend shift occurs, the strategy closes the long position.
Closing a Short Position:
If a bullish trend shift occurs, the strategy closes the short position.
The trend shift markers (orange diamonds) act as a confirmation signal, reinforcing the validity of trade entries and exits.
Customization Options
This strategy allows traders to adjust key parameters for flexibility in different market conditions:
Trade Direction: Choose between Long Only, Short Only, or Long & Short .
Trend Length: Modify the length of the smoothing function to adapt to different timeframes.
Line Width & Colors: Customize the visual appearance of trend lines and cloud colors.
Performance Table: Enable or disable the equity performance table that tracks historical trade results.
Performance Tracking & Reporting
A built-in performance table is included to monitor monthly and yearly trading performance.
The table calculates monthly percentage returns, displaying them in a structured format.
Color-coded values highlight profitable months (blue) and losing months (red).
Tracks yearly cumulative performance to assess long-term strategy effectiveness.
Traders can use this feature to evaluate historical performance trends and optimize their strategy settings accordingly.
How to Use This Strategy
Identify Trend Strength & Reversals:
Use the trend line and cloud color changes to assess trend strength and detect potential reversals.
Monitor Momentum Shifts:
Pay attention to gradient cloud color shifts, as they often appear before the trend line changes color.
This can indicate early momentum weakening or strengthening.
Act on Trend Shift Markers:
Use orange diamonds as confirmation signals for trend shifts and trade entry/exit points.
Utilize Cloud Bands as Support/Resistance:
The outer bands of the cloud serve as dynamic support and resistance, helping with stop-loss and take-profit placement.
Considerations & Limitations
Trend Lag: Since the strategy applies a smoothing function, entries may be slightly delayed compared to raw price action.
Volatile Market Conditions: In high-volatility markets, trend shifts may occur more frequently, leading to higher trade frequency.
Optimized for Trend Trading: This strategy is best suited for trending markets and may produce false signals in sideways (ranging) conditions.
Conclusion
The Gradient Trend Filter Strategy is a trend-following system based on the Gradient Trend Filter indicator by ChartPrime. It integrates noise filtering, trend visualization, and gradient-based color shifts to help traders identify strong market trends and potential reversals.
By combining trend filtering with a multi-layered cloud system, the strategy provides clear trade signals while minimizing noise. Traders can use this strategy for long-term trend trading, momentum shifts, and support/resistance-based decision-making.
This strategy is a fully automated system that allows traders to execute long, short, or both directions, with customizable settings to adapt to different market conditions.
Credit for the original concept and indicator goes to ChartPrime.
Uptrick: Time Based ReversionIntroduction
The Uptrick: Time Based Reversion indicator is designed to provide a comprehensive view of market momentum and potential trend shifts by combining multiple moving averages, a streak-based trend analysis system, and adaptive color visualization. It helps traders identify strong trends, spot potential reversals, and make more informed trading decisions.
Purpose
The primary goal of this indicator is to assist traders in distinguishing between sustained market movements and short-lived fluctuations. By evaluating how price behaves relative to its moving averages, and by measuring consecutive streaks above or below these averages, the indicator highlights areas where trends are likely to continue or lose momentum.
Overview
Uptrick: Time Based Reversion calculates one or more moving averages of price data and then tracks the number of consecutive bars (streaks) above or below these averages. This streak-based detection provides insight into whether a trend is gaining strength or nearing a potential reversal point. The indicator offers:
• Multiple moving average types (SMA, EMA, WMA)
• Optional second and third moving average layers for additional smoothing of first moving average
• A streak detection system to quantify trend intensity
• A dynamic color scheme that changes with streak strength
• Optional buy and sell signals for potential trade entries and exits
• A ribbon mode that applies moving averages to Open, High, Low, and Close prices for a more detailed visualization of overall trend alignment
Originality and Uniqueness
Unlike traditional moving average indicators, Uptrick: Time Based Reversion incorporates a streak measurement system to detect trend strength. This approach helps clarify whether a price movement is merely a quick fluctuation or part of a longer-lasting trend. Additionally, the optional ribbon mode extends this logic to Open, High, Low, and Close prices, creating a layered and intuitive visualization that shows complete trend alignment.
Inputs and Features
1. Enable Ribbon Mode
This input lets you activate or deactivate the ribbon display of multiple moving averages. When enabled, the script plots moving averages for the Open, High, Low, and Close prices and uses color fills to show whether these four data points are collectively above or below their respective moving averages.
2. Color Scheme Selection
Users can choose from several predefined color schemes, such as Default, Emerald, Crimson, Sapphire, Gold, Purple, Teal, Orange, Gray, Lime, or Aqua. Each scheme assigns distinct bullish, bearish and neutral colors..
3. Show Buy/Sell Signals
The indicator can display buy or sell signals based on its streak analysis logic. These signals appear as markers on the chart, indicating a “Safe Uptrend” (buy) or “Safe Downtrend” (sell).
4. Moving Average Types and Lengths
• First MA Type and Length: Choose SMA, EMA, or WMA along with a customizable period.
• Second and Third MA Types and Lengths: You can optionally stack additional moving averages for further smoothing, each with its own customizable type and period.
5. Streak Threshold Multiplier
This numeric input determines how strong a streak must be before the script considers it a “safe” trend. A higher multiplier requires a longer or more intense streak for a buy or sell signal.
6. Dynamic Transparency Calculation
The color intensity adapts to the streak’s strength. Longer streaks increase the transparency of the opposing color, making the current dominant color stand out. This feature ensures that a vigorous uptrend or downtrend is visually distinct from short-lived or weaker moves.
7. Ribbon Moving Averages
In ribbon mode, the script calculates moving averages for the Open, High, Low, and Close prices. Each of these is optionally smoothed again if the second and/or third moving average layers are active. The final result is a ribbon of moving averages that helps confirm whether the market is uniformly aligned above or below these key reference points.
Calculation Methodology
1. Initial Moving Average
The script calculates the first moving average (SMA, EMA, or WMA) of the closing price over a user-defined period.
2. Optional Secondary and Tertiary Averages
If selected, the script then applies a second and/or third smoothing step. Each of these steps can be a different type of moving average (SMA, EMA, or WMA) with its own period length.
3. Streak Detection
The indicator counts consecutive bars above or below the smoothed moving average. A running total (streakUp or streakDown) increments with every bar that remains above or below that average.
4. Reversion Intensity
The script compares the current streak value to its own average (calculated over the final chosen period). This ratio determines whether the streak is nearing a likely reversion or is strong enough to continue.
5. Color Assignment and Signals
The indicator calculates color transparency based on streak intensity. Buy and sell signals appear when the streak meets or exceeds the threshold multiplier, indicating a safe uptrend or downtrend.
Color Schemes and Visualization
This indicator offers multiple predefined color sets. Each scheme specifies a unique bullish color, bearish color and neutral color. The script automatically varies transparency to highlight strong trends and fade weaker ones, making it visually clear when a trend is intensifying or losing momentum.
Smoothing Techniques
By allowing up to three layers of moving average smoothing, the indicator accommodates different trading styles. A single layer provides faster reactions to market changes, while more layers reduce noise at the cost of slower responsiveness. Traders can choose the right balance between responsiveness and stability for their strategy, whether it is short-term scalping or long-term trend following.
Why It Combines Specific Smoothing Techniques
The Uptrick: Time Based Reversion indicator strategically combines specific smoothing techniques—SMA, EMA, and WMA—to leverage their complementary strengths. The SMA provides stable and consistent trend identification by equally weighting all data points, while the EMA emphasizes recent price movements, allowing quicker responses to market changes. WMA enhances sensitivity to recent price shifts, which helps in detecting subtle momentum changes early. By integrating these methods in layers, the indicator effectively balances responsiveness with stability, helping traders clearly identify genuine trend changes while filtering out short-term noise and false signals.
Ribbon Mode
If Open, High, Low, and Close prices remain above or below their respective moving averages consistently, the script colors the bars fully bullish or bearish. When the data points are mixed, a neutral color is applied. This mode provides a thorough perspective on whether the entire price range is aligned in one direction or showing conflicting signals.
Summary
Uptrick: Time Based Reversion combines multiple moving averages, streak detection, and dynamic color adjustments to help traders identify significant trends and potential reversal areas. Its flexibility allows it to be used either in a simpler form, with one moving average and streak analysis, or in a more advanced configuration with ribbon mode that charts multiple smoothed averages for a deeper understanding of price alignment. By adapting color intensities based on streak strength and providing optional buy/sell signals, this indicator delivers a clear and flexible tool suited to various trading strategies.
Disclaimer
This indicator is designed as an analysis aid and does not guarantee profitable trades. Past performance does not indicate future success, and market conditions can change unexpectedly. Users are advised to employ proper risk management and thoroughly evaluate trades before taking positions. Use this indicator as part of a broader strategy, not as a sole decision-making tool.
PnL MonitorThe PnL Monitor is a customizable tool designed to help traders track the Profit and Loss (PnL) of up to 20 currency pairs or assets in real-time. This script provides a clear and organized table that displays the entry price, and PnL percentage for each pair, making it an essential tool for monitoring open positions or tracking potential trades.
Key Features:
Multi-Asset Tracking:
Monitor up to 20 currency pairs or assets simultaneously. Simply input the pair symbol and your entry price, and the script will calculate the PnL in real-time.
Dynamic Table Positioning:
Choose where the table appears on your chart with the Table Position input. Options include:
Top Left
Top Right
Bottom Left
Bottom Right
Real-Time PnL Calculation:
The script fetches the current price of each pair and calculates the PnL percentage based on your entry price. Positive PnL is highlighted in green, while negative PnL is highlighted in red.
Exchange and Pair Separation:
The script automatically separates the exchange name (if provided) from the pair symbol, making it easier to identify the source of the data.
Customizable Inputs:
Add or remove pairs as needed.
Leave the price field blank for pairs you don’t want to track.
How to Use:
Input Your Pairs:
In the script settings, input the symbol of the pair (e.g., NASDAQ:AAPL or BTCUSD) and your entry price. Leave the price field blank for pairs you don’t want to track.
Choose Table Position:
Select where you want the table to appear on your chart.
Monitor PnL:
The table will automatically update with the current price and PnL percentage for each pair.
Why Use This Script?
Efficiency: Track multiple pairs in one place without switching charts.
Clarity: Easily identify profitable and losing positions at a glance.
Flexibility: Customize the table to fit your trading style and preferences.
Ideal For:
Forex, crypto, and stock traders managing multiple positions.
Uwen FX: UWEN StrategyThis Pine Script defines a trading indicator called "Uwen FX: UWEN Strategy" Where ideas coming from Arab Syaukani and modified by Fiki Hafana. It combines a CCI-based T3 Smoothed Indicator with a MACD overlay. Here's a breakdown of what it does:
Key Components of the Script:
1. CCI (Commodity Channel Index) with T3 Smoothing
Uses a T3 smoothing algorithm on the CCI to generate a smoother momentum signal. The smoothing formula is applied iteratively using weighted averages. The final result (xccir) is plotted as a histogram, colored green for bullish signals and red for bearish signals.
2. MACD (Moving Average Convergence Divergence)
The MACD is scaled to match the range of the smoothed CCI for better visualization. Signal Line and MACD Line are plotted if showMACD is enabled. The normalization ensures that MACD values align with the CCI-based indicator.
3. Bar Coloring for Trend Indication
Green bars indicate a positive trend (pos = 1).
Red bars indicate a negative trend (pos = -1).
Blue bars appear when the trend is neutral.
How It Can Be Used:
Buy Signal: When the xccir (smoothed CCI) turns green, indicating bullish momentum.
Sell Signal: When xccir turns red, indicating bearish momentum.
MACD Confirmation: Helps confirm the trend direction by aligning with xccir.
I will add more interesting features if this indicator seems profitable
TEMA OBOS Strategy PakunTEMA OBOS Strategy
Overview
This strategy combines a trend-following approach using the Triple Exponential Moving Average (TEMA) with Overbought/Oversold (OBOS) indicator filtering.
By utilizing TEMA crossovers to determine trend direction and OBOS as a filter, it aims to improve entry precision.
This strategy can be applied to markets such as Forex, Stocks, and Crypto, and is particularly designed for mid-term timeframes (5-minute to 1-hour charts).
Strategy Objectives
Identify trend direction using TEMA
Use OBOS to filter out overbought/oversold conditions
Implement ATR-based dynamic risk management
Key Features
1. Trend Analysis Using TEMA
Uses crossover of short-term EMA (ema3) and long-term EMA (ema4) to determine entries.
ema4 acts as the primary trend filter.
2. Overbought/Oversold (OBOS) Filtering
Long Entry Condition: up > down (bullish trend confirmed)
Short Entry Condition: up < down (bearish trend confirmed)
Reduces unnecessary trades by filtering extreme market conditions.
3. ATR-Based Take Profit (TP) & Stop Loss (SL)
Adjustable ATR multiplier for TP/SL
Default settings:
TP = ATR × 5
SL = ATR × 2
Fully customizable risk parameters.
4. Customizable Parameters
TEMA Length (for trend calculation)
OBOS Length (for overbought/oversold detection)
Take Profit Multiplier
Stop Loss Multiplier
EMA Display (Enable/Disable TEMA lines)
Bar Color Change (Enable/Disable candle coloring)
Trading Rules
Long Entry (Buy Entry)
ema3 crosses above ema4 (Golden Cross)
OBOS indicator confirms up > down (bullish trend)
Execute a buy position
Short Entry (Sell Entry)
ema3 crosses below ema4 (Death Cross)
OBOS indicator confirms up < down (bearish trend)
Execute a sell position
Take Profit (TP)
Entry Price + (ATR × TP Multiplier) (Default: 5)
Stop Loss (SL)
Entry Price - (ATR × SL Multiplier) (Default: 2)
TP/SL settings are fully customizable to fine-tune risk management.
Risk Management Parameters
This strategy emphasizes proper position sizing and risk control to balance risk and return.
Trading Parameters & Considerations
Initial Account Balance: $7,000 (adjustable)
Base Currency: USD
Order Size: 10,000 USD
Pyramiding: 1
Trading Fees: $0.94 per trade
Long Position Margin: 50%
Short Position Margin: 50%
Total Trades (M5 Timeframe): 128
Deep Test Results (2024/11/01 - 2025/02/24)BTCUSD-5M
Total P&L：+1638.20USD
Max equity drawdown：694.78USD
Total trades：128
Profitable trades:44.53
Profit factor:1.45
These settings aim to protect capital while maintaining a balanced risk-reward approach.
Visual Support
TEMA Lines (Three EMAs)
Trend direction is indicated by color changes (Blue/Orange)
ema3 (short-term) and ema4 (long-term) crossover signals potential entries
OBOS Histogram
Green → Strong buying pressure
Red → Strong selling pressure
Blue → Possible trend reversal
Entry & Exit Markers
Blue Arrow → Long Entry Signal
Red Arrow → Short Entry Signal
Take Profit / Stop Loss levels displayed
Strategy Improvements & Uniqueness
This strategy is based on indicators developed by "l_lonthoff" and "jdmonto0", but has been significantly optimized for better entry accuracy, visual clarity, and risk management.
Enhanced Trend Identification with TEMA
Detects early trend reversals using ema3 & ema4 crossover
Reduces market noise for a smoother trend-following approach
Improved OBOS Filtering
Prevents excessive trading
Reduces unnecessary risk exposure
Dynamic Risk Management with ATR-Based TP/SL
Not a fixed value → TP/SL adjusts to market volatility
Fully customizable ATR multiplier settings
(Default: TP = ATR × 5, SL = ATR × 2)
Summary
The TEMA + OBOS Strategy is a simple yet powerful trading method that integrates trend analysis and oscillators.
TEMA for trend identification
OBOS for noise reduction & overbought/oversold filtering
ATR-based TP/SL settings for dynamic risk management
Before using this strategy, ensure thorough backtesting and demo trading to fine-tune parameters according to your trading style.
Non-Repainting Renko Emulation Strategy [PineIndicators]Introduction: The Repainting Problem in Renko Strategies
Renko charts are widely used in technical analysis for their ability to filter out market noise and emphasize price trends. Unlike traditional candlestick charts, which are based on fixed time intervals, Renko charts construct bricks only when price moves by a predefined amount. This makes them useful for trend identification while reducing small fluctuations.
However, Renko-based trading strategies often fail in live trading due to a fundamental issue: repainting .
Why Do Renko Strategies Repaint?
Most trading platforms, including TradingView, generate Renko charts retrospectively based on historical price data. This leads to the following issues:
Renko bricks can change or disappear when new data arrives.
Backtesting results do not reflect real market conditions. Strategies may appear highly profitable in backtests because historical data is recalculated with hindsight.
Live trading produces different results than backtesting. Traders cannot know in advance whether a new Renko brick will form until price moves far enough.
Objective of the Renko Emulator
This script simulates Renko behavior on a standard time-based chart without repainting. Instead of using TradingView’s built-in Renko charting, which recalculates past bricks, this approach ensures that once a Renko brick is formed, it remains unchanged .
Key benefits:
No past bricks are recalculated or removed.
Trading strategies can execute reliably without false signals.
Renko-based logic can be applied on a time-based chart.
How the Renko Emulator Works
1. Parameter Configuration & Initialization
The script defines key user inputs and variables:
brickSize : Defines the Renko brick size in price points, adjustable by the user.
renkoPrice : Stores the closing price of the last completed Renko brick.
prevRenkoPrice : Stores the price level of the previous Renko brick.
brickDir : Tracks the direction of Renko bricks (1 = up, -1 = down).
newBrick : A boolean flag that indicates whether a new Renko brick has been formed.
brickStart : Stores the bar index at which the current Renko brick started.
2. Identifying Renko Brick Formation Without Repainting
To ensure that the strategy does not repaint, Renko calculations are performed only on confirmed bars.
The script calculates the difference between the current price and the last Renko brick level.
If the absolute price difference meets or exceeds the brick size, a new Renko brick is formed.
The new Renko price level is updated based on the number of bricks that would fit within the price movement.
The direction (brickDir) is updated , and a flag ( newBrick ) is set to indicate that a new brick has been formed.
3. Visualizing Renko Bricks on a Time-Based Chart
Since TradingView does not support live Renko charts without repainting, the script uses graphical elements to draw Renko-style bricks on a standard chart.
Each time a new Renko brick forms, a colored rectangle (box) is drawn:
Green boxes → Represent bullish Renko bricks.
Red boxes → Represent bearish Renko bricks.
This allows traders to see Renko-like formations on a time-based chart, while ensuring that past bricks do not change.
Trading Strategy Implementation
Since the Renko emulator provides a stable price structure, it is possible to apply a consistent trading strategy that would otherwise fail on a traditional Renko chart.
1. Entry Conditions
A long trade is entered when:
The previous Renko brick was bearish .
The new Renko brick confirms an upward trend .
There is no existing long position .
A short trade is entered when:
The previous Renko brick was bullish .
The new Renko brick confirms a downward trend .
There is no existing short position .
2. Exit Conditions
Trades are closed when a trend reversal is detected:
Long trades are closed when a new bearish brick forms.
Short trades are closed when a new bullish brick forms.
Key Characteristics of This Approach
1. No Historical Recalculation
Once a Renko brick forms, it remains fixed and does not change.
Past price action does not shift based on future data.
2. Trading Strategies Operate Consistently
Since the Renko structure is stable, strategies can execute without unexpected changes in signals.
Live trading results align more closely with backtesting performance.
3. Allows Renko Analysis Without Switching Chart Types
Traders can apply Renko logic without leaving a standard time-based chart.
This enables integration with indicators that normally cannot be used on traditional Renko charts.
Considerations When Using This Strategy
Trade execution may be delayed compared to standard Renko charts. Since new bricks are only confirmed on closed bars, entries may occur slightly later.
Brick size selection is important. A smaller brickSize results in more frequent trades, while a larger brickSize reduces signals.
Conclusion
This Renko Emulation Strategy provides a method for using Renko-based trading strategies on a time-based chart without repainting. By ensuring that bricks do not change once formed, it allows traders to use stable Renko logic while avoiding the issues associated with traditional Renko charts.
This approach enables accurate backtesting and reliable live execution, making it suitable for trend-following and swing trading strategies that rely on Renko price action.
EPS Line Indicator - cristianhkrOverview
The EPS Line Indicator displays the Earnings Per Share (EPS) of a publicly traded company directly on a TradingView chart. It provides a historical trend of EPS over time, allowing investors to track a company's profitability per share.
Key Features
📊 Plots actual EPS data for the selected stock.
📅 Updates quarterly as new EPS reports are released.
🔄 Smooths missing values by holding the last reported EPS.
🔍 Helps track long-term profitability trends.
How It Works
The script retrieves quarterly EPS using request.financial(syminfo.tickerid, "EARNINGS_PER_SHARE", "Q", barmerge.gaps_off).
If EPS data is missing for a given period, the last available EPS value is retained to maintain continuity.
The EPS values are plotted as a continuous green line on the chart.
A baseline at EPS = 0 is included to easily identify profitable vs. loss-making periods.
How to Use This Indicator
If the EPS line is trending upwards 📈 → The company is growing earnings per share, a strong sign of profitability.
If the EPS line is declining 📉 → The company’s EPS is shrinking, which may indicate financial weakness.
If EPS is negative (below zero) ❌ → The company is reporting losses per share, which can be a warning sign.
Limitations
Only works with stocks that report EPS data (not applicable to cryptocurrencies or commodities).
Does not adjust for stock splits or other corporate actions.
Best used on daily, weekly, or monthly charts for clear earnings trends.
Conclusion
This indicator is a powerful tool for investors who want to visualize earnings per share trends directly on a price chart. By showing how EPS evolves over time, it helps assess a company's profitability trajectory, making it useful for both fundamental analysis and long-term investing.
🚀 Use this indicator to track EPS growth and make smarter investment decisions!
DS_Gurukul_5minTrendDS Gurukul (DS_5minTrend) Indicator: A Simple Yet Powerful Trend Tool
The Tushar Daily Bands (DS_5minTrend) indicator is a straightforward tool designed to help traders quickly visualize potential trend reversals and identify profitable trading opportunities. This indicator plots two bands—an upper band (green) and a lower band (red)—based on a small percentage deviation from the closing price of the first candle of each trading day.
How it Works:
The DS_5minTrend indicator calculates these bands at the start of each new trading day. The bands then remain fixed for the rest of that day. This daily reset allows traders to easily see how the current day's price action relates to the opening price and the calculated bands.
Trading Signals:
Potential Reversals: When the price approaches or touches the upper band (green), it can signal a potential overbought condition and a possible reversal to the downside. Conversely, when the price approaches or touches the lower band (red), it can suggest an oversold condition and a possible reversal to the upside.
Trend Confirmation: If the price consistently closes above the upper band for several periods, it may indicate a strong uptrend. Conversely, consistent closes below the lower band can suggest a strong downtrend.
Support and Resistance: The bands can also act as dynamic support and resistance levels. Traders can watch for price bounces off these levels as potential entry points.
How to Use:
Combine with other indicators: While DS_5minTrend can provide valuable insights, it's generally recommended to use it in conjunction with other technical indicators, such as RSI, MACD, or volume analysis, for confirmation.
Consider market context: Always consider the broader market context and news events that may be influencing price action.
Risk Management: Implement proper risk management strategies, including stop-loss orders, to protect your capital.
Disclaimer: The DS_5minTrend indicator is a tool for analysis and should not be the sole basis for making trading decisions. Trading involves substantial risk, and you could lose money. Always do your own research and consult with a financial advisor before making any investment decisions.
MACD Volume Strategy for XAUUSD (15m) [PineIndicators]The MACD Volume Strategy is a momentum-based trading system designed for XAUUSD on the 15-minute timeframe. It integrates two key market indicators: the Moving Average Convergence Divergence (MACD) and a volume-based oscillator to identify strong trend shifts and confirm trade opportunities. This strategy uses dynamic position sizing, incorporates leverage customization, and applies structured entry and exit conditions to improve risk management.
⚙️ Core Strategy Components
1️⃣ Volume-Based Momentum Calculation
The strategy includes a custom volume oscillator to filter trade signals based on market activity. The oscillator is derived from the difference between short-term and long-term volume trends using Exponential Moving Averages (EMAs)
Short EMA (default = 5) represents recent volume activity.
Long EMA (default = 8) captures broader volume trends.
Positive values indicate rising volume, supporting momentum-based trades.
Negative values suggest weak market activity, reducing signal reliability.
By requiring positive oscillator values, the strategy ensures momentum confirmation before entering trades.
2️⃣ MACD Trend Confirmation
The strategy uses the MACD indicator as a trend filter. The MACD is calculated as:
Fast EMA (16-period) detects short-term price trends.
Slow EMA (26-period) smooths out price fluctuations to define the overall trend.
Signal Line (9-period EMA) helps identify crossovers, signaling potential trend shifts.
Histogram (MACD – Signal) visualizes trend strength.
The system generates trade signals based on MACD crossovers around the zero line, confirming bullish or bearish trend shifts.
📌 Trade Logic & Conditions
🔹 Long Entry Conditions
A buy signal is triggered when all the following conditions are met:
✅ MACD crosses above 0, signaling bullish momentum.
✅ Volume oscillator is positive, confirming increased trading activity.
✅ Current volume is at least 50% of the previous candle’s volume, ensuring market participation.
🔻 Short Entry Conditions
A sell signal is generated when:
✅ MACD crosses below 0, indicating bearish momentum.
✅ Volume oscillator is positive, ensuring market activity is sufficient.
✅ Current volume is less than 50% of the previous candle’s volume, showing decreasing participation.
This multi-factor approach filters out weak or false signals, ensuring that trades align with both momentum and volume dynamics.
📏 Position Sizing & Leverage
Dynamic Position Calculation:
Qty = strategy.equity × leverage / close price
Leverage: Customizable (default = 1x), allowing traders to adjust risk exposure.
Adaptive Sizing: The strategy scales position sizes based on account equity and market price.
Slippage & Commission: Built-in slippage (2 points) and commission (0.01%) settings provide realistic backtesting results.
This ensures efficient capital allocation, preventing overexposure in volatile conditions.
🎯 Trade Management & Exits
Take Profit & Stop Loss Mechanism
Each position includes predefined profit and loss targets:
Take Profit: +10% of risk amount.
Stop Loss: Fixed at 10,100 points.
The risk-reward ratio remains balanced, aiming for controlled drawdowns while maximizing trade potential.
Visual Trade Tracking
To improve trade analysis, the strategy includes:
📌 Trade Markers:
"Buy" label when a long position opens.
"Close" label when a position exits.
📌 Trade History Boxes:
Green for profitable trades.
Red for losing trades.
📌 Horizontal Trade Lines:
Shows entry and exit prices.
Helps identify trend movements over multiple trades.
This structured visualization allows traders to analyze past performance directly on the chart.
⚡ How to Use This Strategy
1️⃣ Apply the script to a XAUUSD (Gold) 15m chart in TradingView.
2️⃣ Adjust leverage settings as needed.
3️⃣ Enable backtesting to assess past performance.
4️⃣ Monitor volume and MACD conditions to understand trade triggers.
5️⃣ Use the visual trade markers to review historical performance.
The MACD Volume Strategy is designed for short-term trading, aiming to capture momentum-driven opportunities while filtering out weak signals using volume confirmation.
Balance of Power for US30 4H [PineIndicators]The Balance of Power (BoP) Strategy is a momentum-based trading system for the US30 index on a 4-hour timeframe. It measures the strength of buyers versus sellers in each candle using the Balance of Power (BoP) indicator and executes trades based on predefined threshold crossovers. The strategy includes dynamic position sizing, adjustable leverage, and visual trade tracking.
⚙️ Core Strategy Mechanics
Positive values indicate buying strength.
Negative values indicate selling strength.
Values close to 1 suggest strong bullish momentum.
Values close to -1 indicate strong bearish pressure.
The strategy uses fixed threshold crossovers to determine trade entries and exits.
📌 Trade Logic
Entry Conditions
Long Entry: When BoP crosses above 0.8, signaling strong buying pressure.
Exit Conditions
Position Close: When BoP crosses below -0.8, indicating a shift to selling pressure.
This threshold-based system filters out low-confidence signals and focuses on high-momentum shifts.
📏 Position Sizing & Leverage
Leverage: Adjustable by the user (default = 5x).
Risk Management: Position size adapts dynamically based on equity fluctuations.
📊 Trade Visualization & History Tracking
Trade Markers:
"Buy" labels appear when a long position is opened.
"Close" labels appear when a position is exited.
Trade History Boxes:
Green for profitable trades.
Red for losing trades.
These elements provide clear visual tracking of past trade execution.
⚡ Usage & Customization
1️⃣ Apply the script to a US30 4H chart in TradingView.
2️⃣ Adjust leverage settings as needed.
3️⃣ Review trade signals and historical performance with visual markers.
4️⃣ Enable backtesting to evaluate past performance.
This strategy is designed for momentum-based trading and is best suited for volatile market conditions.
AO/AC Trading Zones Strategy [Skyrexio] Overview
AO/AC Trading Zones Strategy leverages the combination of Awesome Oscillator (AO), Acceleration/Deceleration Indicator (AC), Williams Fractals, Williams Alligator and Exponential Moving Average (EMA) to obtain the high probability long setups. Moreover, strategy uses multi trades system, adding funds to long position if it considered that current trend has likely became stronger. Combination of AO and AC is used for creating so-called trading zones to create the signals, while Alligator and Fractal are used in conjunction as an approximation of short-term trend to filter them. At the same time EMA (default EMA's period = 100) is used as high probability long-term trend filter to open long trades only if it considers current price action as an uptrend. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator to identify when current uptrend is likely to be over. In some special cases strategy uses AO and AC combination to trail profit (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Multilayer trades opening system: strategy uses only 10% of capital in every trade and open up to 5 trades at the same time if script consider current trend as strong one.
Short and long term trend trade filters: strategy uses EMA as high probability long-term trend filter and Alligator and Fractal combination as a short-term one.
Methodology
The strategy opens long trade when the following price met the conditions:
1. Price closed above EMA (by default, period = 100). Crossover is not obligatory.
2. Combination of Alligator and Williams Fractals shall consider current trend as an upward (all details in "Justification of Methodology" paragraph)
3. Both AC and AO shall print two consecutive increasing values. At the price candle close which corresponds to this condition algorithm opens the first long trade with 10% of capital.
4. If combination of Alligator and Williams Fractals shall consider current trend has been changed from up to downtrend, all long trades will be closed, no matter how many trades has been opened.
5. If AO and AC both continue printing the rising values strategy opens the long trade on each candle close with 10% of capital while number of opened trades reaches 5.
6. If AO and AC both has printed 5 rising values in a row algorithm close all trades if candle's low below the low of the 5-th candle with rising AO and AC values in a row.
Script also has additional visuals. If second long trade has been opened simultaneously the Alligator's teeth line is plotted with the green color. Also for every trade in a row from 2 to 5 the label "Buy More" is also plotted just below the teeth line. With every next simultaneously opened trade the green color of the space between teeth and price became less transparent.
Strategy settings
In the inputs window user can setup strategy setting:
EMA Length (by default = 100, period of EMA, used for long-term trend filtering EMA calculation).
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Let's explore the key concepts of this strategy and understand how they work together. We'll begin with the simplest: the EMA.
The Exponential Moving Average (EMA) is a type of moving average that assigns greater weight to recent price data, making it more responsive to current market changes compared to the Simple Moving Average (SMA). This tool is widely used in technical analysis to identify trends and generate buy or sell signals. The EMA is calculated as follows:
1.Calculate the Smoothing Multiplier:
Multiplier = 2 / (n + 1), Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
In this strategy, the EMA acts as a long-term trend filter. For instance, long trades are considered only when the price closes above the EMA (default: 100-period). This increases the likelihood of entering trades aligned with the prevailing trend.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
Fractals, another tool by Bill Williams, help identify potential reversal points on a price chart. A fractal forms over at least five consecutive bars, with the middle bar showing either:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often use fractals alongside other indicators to confirm trends or reversals, enhancing decision-making accuracy.
How do these tools work together in this strategy? Let’s consider an example of an uptrend.
When the price breaks above an up fractal, it signals a potential bullish trend. This occurs because the up fractal represents a shift in market behavior, where a temporary high was formed due to selling pressure. If the price revisits this level and breaks through, it suggests the market sentiment has turned bullish.
The breakout must occur above the Alligator’s teeth line to confirm the trend. A breakout below the teeth is considered invalid, and the downtrend might still persist. Conversely, in a downtrend, the same logic applies with down fractals.
In this strategy if the most recent up fractal breakout occurs above the Alligator's teeth and follows the last down fractal breakout below the teeth, the algorithm identifies an uptrend. Long trades can be opened during this phase if a signal aligns. If the price breaks a down fractal below the teeth line during an uptrend, the strategy assumes the uptrend has ended and closes all open long trades.
By combining the EMA as a long-term trend filter with the Alligator and fractals as short-term filters, this approach increases the likelihood of opening profitable trades while staying aligned with market dynamics.
Now let's talk about the trading zones concept and its signals. To understand this we need to briefly introduce what is AO and AC. The Awesome Oscillator (AO), developed by Bill Williams, is a momentum indicator designed to measure market momentum by contrasting recent price movements with a longer-term historical perspective. It helps traders detect potential trend reversals and assess the strength of ongoing trends.
The formula for AO is as follows:
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
The Acceleration/Deceleration (AC) Indicator, introduced by Bill Williams, measures the rate of change in market momentum. It highlights shifts in the driving force of price movements and helps traders spot early signs of trend changes. The AC Indicator is particularly useful for identifying whether the current momentum is accelerating or decelerating, which can indicate potential reversals or continuations. For AC calculation we shall use the AO calculated above is the following formula:
AC = AO − SMA5(AO) , where SMA5(AO)is the 5-period Simple Moving Average of the Awesome Oscillator
When the AC is above the zero line and rising, it suggests accelerating upward momentum.
When the AC is below the zero line and falling, it indicates accelerating downward momentum.
When the AC is below zero line and rising it suggests the decelerating the downtrend momentum. When AC is above the zero line and falling, it suggests the decelerating the uptrend momentum.
Now let's discuss the trading zones concept and how it can create the signal. Zones are created by the combination of AO and AC. We can divide three zone types:
Greed zone: when the AO and AC both are rising
Red zone: when the AO and AC both are decreasing
Gray zone: when one of AO or AC is rising, the other is falling
Gray zone is considered as uncertainty. AC and AO are moving in the opposite direction. Strategy skip such price action to decrease the chance to stuck in the losing trade during potential sideways. Red zone is also not interesting for the algorithm because both indicators consider the trend as bearish, but strategy opens only long trades. It is waiting for the green zone to increase the chance to open trade in the direction of the potential uptrend. When we have 2 candles in a row in the green zone script executes a long trade with 10% of capital.
Two green zone candles in a row is considered by algorithm as a bullish trend, but now so strong, that's the reason why trade is going to be closed when the combination of Alligator and Fractals will consider the the trend change from bullish to bearish. If id did not happens, algorithm starts to count the green zone candles in a row. When we have 5 in a row script change the trade closing condition. Such situation is considered is a high probability strong bull market and all trades will be closed if candle's low will be lower than fifth green zone candle's low. This is used to increase probability to secure the profit. If long trades are initiated, the strategy continues utilizing subsequent signals until the total number of trades reaches a maximum of 5. Each trade uses 10% of capital.
Why we use trading zones signals? If currently strategy algorithm considers the high probability of the short-term uptrend with the Alligator and Fractals combination pointed out above and the long-term trend is also suggested by the EMA filter as bullish. Rising AC and AO values in the direction of the most likely main trend signaling that we have the high probability of the fastest bullish phase on the market. The main idea is to take part in such rapid moves and add trades if this move continues its acceleration according to indicators.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.12.31. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 10%
Maximum Single Position Loss: -9.49%
Maximum Single Profit: +24.33%
Net Profit: +4374.70 USDT (+43.75%)
Total Trades: 278 (39.57% win rate)
Profit Factor: 2.203
Maximum Accumulated Loss: 668.16 USDT (-5.43%)
Average Profit per Trade: 15.74 USDT (+1.37%)
Average Trade Duration: 60 hours
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
Pure Price Action Breakout with 1:5 RR
Description of the Price Action Trading Script (Pine Script v6)
Overview
This script is a pure price action-based breakout strategy designed for TradingView. It identifies key breakout levels and executes long and short trades based on market structure. The strategy ensures a minimum risk-to-reward ratio (RR) of 1:5, aiming for high profitability with well-defined stop-loss and take-profit levels.
How the Script Works
1️⃣ Breakout Identification
The script uses a lookback period to find the highest high and lowest low over the last n bars.
A bullish breakout occurs when the price closes above the previous highest high.
A bearish breakout happens when the price closes below the previous lowest low.
2️⃣ Entry & Exit Strategy
Long Entry: If a bullish breakout is detected, the script enters a long position.
Short Entry: If a bearish breakout is detected, the script enters a short position.
The stop-loss is placed at the recent swing low (for long trades) or recent swing high (for short trades).
The target price is calculated based on a risk-to-reward ratio of 1:5, ensuring profitable trades.
3️⃣ Risk Management
The stop-loss prevents excessive losses by exiting trades when the market moves unfavorably.
The strategy ensures that each trade has a reward potential at least 5 times the risk.
Positions are executed based on price action only, without indicators like moving averages or RSI.
4️⃣ Visual Representation
The script plots breakout levels to help traders visualize potential trade setups.
Entry points, stop-loss, and take-profit levels are labeled on the chart for easy tracking.
Key Features & Benefits
✔ Pure Price Action – No lagging indicators, only real-time price movements.
✔ High Risk-to-Reward Ratio (1:5) – Ensures high-profit potential trades.
✔ Real-time Entry & Exit Signals – Provides accurate trade setups.
✔ Dynamic Stop-loss Calculation – Adjusts based on recent market structure.
✔ Customizable Parameters – Lookback periods and risk ratios can be modified.
Naive Bayes Candlestick Pattern Classifier v1.1 BETAAn intermezzo on why i made this script publication..
A : Candlestick Pattern took hours to backtest, why not using Machine Learning techniques?
B : Machine Learning, no that's gonna be really heavy bro!
A : Not really, because we use Naive Bayes.
B : The simplest, yet powerful machine learning algorithm to separate (a.k.a classify) multivariate data.
----------------------------------------------------------------------------------------------------------------------
Hello, everyone!
After deep research in extracting meaningful information from the market, I ended up building this powerful machine learning indicator based on the evolution of Bayesian Statistics. This indicator not only leverages the simplicity of Naive Bayes but also extends its application to candlestick pattern analysis, making it an invaluable tool for traders who are looking to enhance their technical analysis without spending countless hours manually backtesting each pattern on each market!.
What most interesting part is actually after learning all of likely useless methods like fibonacci, supply and demand, volume profile, etc. We always ended up back to basic like support and resistance and candlestick patterns, but with a slight twist on strategy algorithm design and statistical approach. Thus, the only reason why i made this, because i exactly know that you guys will ended up in this position as time goes by.
The essence of this indicator lies in its ability to automate the recognition and statistical evaluation of various candlestick patterns. Traditionally, traders have relied on visual inspection and manual backtesting to determine the effectiveness of patterns like Bullish Engulfing, Bearish Engulfing, Harami variations, Hammer formations, and even more complex multi-candle patterns such as Three White Soldiers, Three Black Crows, Dark Cloud Cover, and Piercing Pattern. However, these conventional methods are both time-consuming and prone to subjective bias.
To address these challenges, I employed Naive Bayes—a probabilistic classifier that, despite its simplicity, offers robust performance in various domains. Naive Bayes assumes that each feature is independent of the others given the class label, which, although a strong assumption, works remarkably well in practice, especially when the dataset is large like market data and the feature space is high-dimensional. In our case, each candlestick pattern acts as a feature that can be statistically evaluated based on its historical performance. The indicator calculates a probability that a given pattern will lead to a price reversal, by comparing the pattern’s close price to the highest or lowest price achieved in a lookahead window.
One of the standout features of this script is its flexibility. Each candlestick pattern is not only coded into the system but also comes with individual toggles to enable or disable them based on your trading strategy. This means you can choose to focus on single-candle patterns like Bullish Engulfing or more complex multi-candle formations such as Three White Soldiers, without modifying the core code. The built-in customization options allow you to adjust colors and labels for each pattern, giving you the freedom to tailor the visual output to your preference. This level of customization ensures that the indicator integrates seamlessly into your existing TradingView setup.
Moreover, the indicator isn’t just about pattern recognition—it also incorporates outcome-based learning. Every time a pattern is detected, it looks ahead a predefined number of bars to evaluate if the expected reversal actually materialized. This outcome is then stored in arrays, and over time, the script dynamically calculates the probability of success for each pattern. These probabilities are presented in a real-time updating table on your chart, which shows not only the percentage probability but also the count of historical occurrences. With this information at your fingertips, you can quickly gauge the reliability of each pattern in your chosen market and timeframe.
Another significant advantage of this approach is its speed and efficiency. While more complex machine learning models like neural networks might require heavy computational resources and longer training times, the Naive Bayes classifier in this script is lightweight, instantaneous and can be updated on the fly with each new bar. This real-time capability is essential for modern traders who need to make quick decisions in fast-paced markets.
Furthermore, by automating the process of backtesting, the indicator frees up your time to focus on other aspects of trading strategy development. Instead of manually analyzing hundreds or even thousands of candles, you can rely on the statistical power of Naive Bayes to provide you with insights on which patterns are most likely to result in profitable moves. This not only enhances your efficiency but also helps to eliminate the cognitive biases that often plague manual analysis.
In summary, this indicator represents a fusion of traditional candlestick analysis with modern machine learning techniques. It harnesses the simplicity and effectiveness of Naive Bayes to deliver a dynamic, real-time evaluation of various candlestick patterns. Whether you are a seasoned trader looking to refine your technical analysis or a beginner eager to understand market dynamics, this tool offers a powerful, customizable, and efficient solution. Welcome to a new era where advanced statistical methods meet practical trading insights—happy trading and may your patterns always be in your favor!
Note : On this current released beta version, you must manually adjust reversal percentage move based on each market. Further updates may include automated best range detection and probability.
