Triple Confirmation Buy/Sell Engine VWAP + MACD + RSIDescription:
This custom-built indicator generates high-confidence Buy/Sell signals using a powerful combination of MACD momentum, RSI strength, and VWAP trend confirmation — designed for cleaner entries and fewer false signals.
Unlike traditional scripts that rely on only one indicator (and produce noisy or early signals), this system requires triple confirmation, greatly increasing signal quality and reducing false trades.
✅ Buy Signal Conditions:
MACD histogram turns green (momentum shift positive)
RSI crosses above 50 (bullish strength confirmation)
Price closes above VWAP (trend confirmation)
🔻 Sell Signal Conditions:
MACD histogram turns red (momentum shift negative)
RSI crosses below 50 (weakening trend)
Price closes below VWAP (bearish confirmation)
🛠 Best For:
Trend traders seeking higher probability entries
Swing traders who want to catch bigger moves
Crypto, stocks, forex traders looking for simple, effective signals
Cari dalam skrip untuk "crypto"
Whale Psychology Insights
### 🧠 Whale Psychology Insights – Unmasking Smart Money Moves
**Understand the mind games behind every candle.**
This advanced indicator is designed to reveal the psychological warfare played by whales and market manipulators in the crypto space. Stop trading blind—start trading with the insights of the smart money.
#### 🔍 What It Does:
- **Liquidity Zone Detection** – Automatically identifies key **swing highs/lows** where stop hunts are likely.
- **Volume Spike Alerts** – Spot **suspicious activity** where big players enter or exit.
- **Order Block Zones** – Highlights **bullish/bearish engulfing patterns** used by institutions.
- **Fair Value Gaps (FVG)** – Marks price inefficiencies where price may return.
- **Fakeout Detection** – Finds **manipulative wicks** designed to trap retail traders.
#### 💡 Use Cases:
- Avoid getting stopped out by **liquidity grabs**
- Enter after the **whales have made their move**
- Identify **high-probability reversal zones**
- Trade **with smart money**, not against it
Perfect for scalpers, intraday traders, and swing traders looking to understand *why* price moves—not just *where*.
> 🧠 **Trade the psychology, not just the chart.**
market relative strengthOverview
market relative strength is a custom indicator that visualizes how strong or weak a given asset is compared to a selected market benchmark — such as KOSPI, NASDAQ100, BTC dominance, or total crypto market cap.
How It Works
The indicator calculates the relative return between the current asset and the selected benchmark over a user-defined period. It then normalizes the difference into a 0–100 score:
Above 50 = outperforming the market
Below 50 = underperforming the market
Above 70 / Below 30 = strong divergence from market trend
Use Case
This is ideal for identifying assets with strong relative performance, detecting trend leaders or laggards, and rotating positions between sectors or assets based on strength.
Customization
Choose from a list of market indexes or crypto metrics
Set the comparison period and normalization range
Visual cues with background shading for strong/weak zones
Note
This is not the same as RSI. This indicator is based on relative performance to a benchmark, not price momentum.
Volume-Price Momentum IndicatorVolume-Price Momentum Indicator (VPMI)
Overview
The Volume-Price Momentum Indicator (VPMI), developed by Kevin Svenson , is a powerful technical analysis tool designed to identify strong bullish and bearish momentum in price movements, driven by volume dynamics. By analyzing price changes and volume surges over a user-defined lookback period, VPMI highlights potential trend shifts and continuation patterns through a smoothed histogram, optional labels, and background highlights. Ideal for traders seeking to capture momentum-driven opportunities, VPMI is suitable for various markets, including stocks, forex, and cryptocurrencies.
How It Works
VPMI calculates the difference between volume-weighted buying and selling pressure based on price changes over a specified lookback period. It amplifies signals during high-volume periods, applies smoothing to reduce noise, and uses momentum checks to detect sustained trends.
Indicator display:
A histogram that oscillates above (bullish) or below (bearish) a zero line, with brighter colors indicating stronger momentum and faded colors for weaker signals.
Optional labels ("Bullish" or "Bearish") to mark significant momentum shifts.
Optional background highlights to visually emphasize strong trend conditions.
Alerts to notify users when strong bullish or bearish momentum is detected.
Key Features
Customizable Settings:
Adjust the lookback period, volume threshold, momentum length, and smoothing to suit your trading style.
Volume Sensitivity:
Emphasizes price movements during high-volume surges, enhancing signal reliability.
Momentum Detection: Uses linear regression and momentum change to confirm sustained trends, reducing false signals.
Visual Clarity:
Offers a clear histogram with color-coded signals, plus optional labels and backgrounds for enhanced chart readability.
Alerts:
Configurable alerts for strong momentum signals, enabling timely trade decisions.
Inputs and Customization
Lookback Period (Default: 9):
Sets the number of bars to analyze price changes. Higher values smooth signals but may lag.
Volume Threshold (Default: 1.4):
Defines the volume level (relative to a 20-period SMA) that qualifies as a surge, amplifying signals.
High Volume Multiplier (Default: 1.5):
Boosts histogram values during high-volume periods for stronger signals.
Histogram Smoothing Length (Default: 4):
Controls the EMA smoothing applied to the histogram, reducing noise.
Momentum Check Length (Default: 4):
Sets the period for momentum trend analysis (recommended to be less than Lookback Period).
Momentum Threshold (Default: 6):
Defines the minimum momentum change required for strong signals.
Show Labels (Default: Off):
Toggle to display "Bullish" or "Bearish" labels on significant momentum shifts.
Show Backgrounds (Default: Off):
Toggle to highlight chart backgrounds during strong momentum periods.
Bullish/Bearish Colors:
Customize colors for bullish (default: green) and bearish (default: red) signals.
Faded Transparency (Default: 40):
Adjusts the transparency of weaker signals for visual distinction.
How to Use
Interpret Signals:
Above Zero (Green):
Indicates bullish momentum. Bright green suggests strong, sustained buying pressure.
Below Zero (Red):
Indicates bearish momentum. Bright red suggests strong, sustained selling pressure.
Faded Colors:
Weaker momentum, potentially signaling consolidation or trend exhaustion.
Enable Visuals:
Turn on "Show Labels" and "Show Backgrounds" in the settings for additional context on strong momentum signals.
Set Alerts:
Use the built-in alert conditions ("Strong Bullish Momentum" or "Strong Bearish Momentum") to receive notifications when significant trends emerge.
Combine with Other Tools:
Pair VPMI with support/resistance levels, trendlines, or other indicators (e.g., RSI, MACD) for confirmation.
Best Practices
Timeframe:
VPMI works on all timeframes, but shorter timeframes (e.g., 5m, 15m) may produce more signals, while longer timeframes (e.g., 1h, 4h, 1D) offer higher reliability.
Market Conditions:
Most effective in trending markets. In choppy or sideways markets, consider increasing the smoothing length or momentum threshold to filter noise.
Risk Management:
Always use VPMI signals in conjunction with a robust trading plan, including stop-losses and position sizing.
Limitations
Lagging Nature:
As a momentum indicator, VPMI may lag in fast-moving markets due to smoothing and lookback calculations.
False Signals:
In low-volume or ranging markets, signals may be less reliable. Adjust the volume threshold or momentum settings to improve accuracy.
Customization Required:
Optimal settings vary by asset and timeframe. Experiment with inputs to align with your trading strategy.
Why Use VPMI?
VPMI offers a unique blend of volume and price momentum analysis, making it a versatile tool for traders seeking to identify high-probability trend opportunities. Its customizable inputs, clear visuals, and alert capabilities empower users to tailor the indicator to their needs, whether for day trading, swing trading, or long-term analysis.
Get Started
Apply VPMI to your chart, tweak the settings to match your trading style, and start exploring momentum-driven opportunities. For questions or feedback, consult TradingView’s community forums or documentation. Happy trading!
SwiftEdge NW EnvelopeSwiftEdge NW Envelope
Overview
The SwiftEdge NW Envelope is a visually striking technical indicator designed for traders seeking to identify high-probability buy and sell opportunities in volatile markets. By combining the Relative Strength Index (RSI), Average True Range (ATR), and Nadaraya-Watson Envelope, this indicator provides a unique blend of momentum, volatility, and non-linear trend analysis. Its futuristic, AI-inspired aesthetic—featuring neon gradients and dynamic colors—enhances chart readability while delivering actionable trading signals.
What It Does
The SwiftEdge NW Envelope generates buy and sell signals based on price interactions with dynamically calculated support and resistance bands, confirmed by RSI conditions. The indicator:
Plots a Nadaraya-Watson Envelope to identify smooth, non-linear price trends and dynamic support/resistance zones.
Uses ATR to scale the envelope’s bands, adapting to market volatility.
Employs RSI to confirm overbought/oversold conditions, ensuring signals align with momentum.
Visualizes signals with neon-colored markers, background zones, and labels for intuitive decision-making.
How It Works
The indicator integrates three key components:
Nadaraya-Watson Envelope:
A kernel-based regression technique that smooths price data to create a central trend line (mean) and dynamic upper/lower bands.
Unlike traditional moving averages, it provides a non-linear, adaptive view of price trends, making it ideal for capturing complex market movements.
The band width is determined by ATR, ensuring responsiveness to volatility.
Average True Range (ATR):
Measures market volatility to scale the envelope’s bands.
A multiplier (default: 0.5) adjusts the sensitivity of the bands, allowing traders to fine-tune the indicator for different assets or market conditions.
Relative Strength Index (RSI):
A momentum oscillator with a shortened period (default: 5) for increased sensitivity.
Confirms buy signals when RSI is oversold (default: <30) and sell signals when RSI is overbought (default: >70).
Signal Logic
Buy Signal: Triggered when the price crosses above the lower band of the Nadaraya-Watson Envelope and RSI is below the oversold threshold. Marked by a green circle and a "BUY" label below the candle.
Sell Signal: Triggered when the price crosses below the upper band and RSI is above the overbought threshold. Marked by a magenta circle and a "SELL" label above the candle.
Background Zones: Green (buy) or red (sell) translucent zones highlight signal areas for quick recognition.
Visual Features
Dynamic Colors: The central trend line shifts between cyan (uptrend), purple (downtrend), or gray (neutral) based on price position relative to the mean.
Neon Gradient Fill: A translucent blue fill between the upper (green) and lower (red) bands creates a glowing, futuristic effect.
Modern Signal Markers: Small, vibrant circles (green for buy, magenta for sell) and clear labels enhance visual clarity.
Why This Combination?
The SwiftEdge NW Envelope combines RSI, ATR, and Nadaraya-Watson Envelope to create a robust trading tool:
RSI provides momentum confirmation, filtering out false signals in choppy markets.
ATR ensures the envelope adapts to changing volatility, making it suitable for both trending and ranging markets.
Nadaraya-Watson Envelope offers a sophisticated, non-linear alternative to traditional bands (e.g., Bollinger Bands), capturing subtle price dynamics. Together, these components deliver a balanced approach to trend-following and mean-reversion strategies, with RSI acting as a gatekeeper to improve signal reliability.
Customize Settings:
RSI Period (5): Adjust for more/less sensitivity to momentum.
RSI Overbought/Oversold (70/30): Modify thresholds to tighten or loosen signal conditions.
ATR Period (14) and Multiplier (0.5): Tune volatility sensitivity.
NW Length (25), Bandwidth (8.0), Multiplier (3.0): Adjust the smoothness and width of the envelope.
Interpret Signals:
Buy: Look for green circles and "BUY" labels when price crosses above the lower band, confirmed by low RSI.
Sell: Look for magenta circles and "SELL" labels when price crosses below the upper band, confirmed by high RSI.
Use background zones to quickly spot active signal areas.
Combine with Other Tools:
Pair with support/resistance levels or volume analysis for additional confirmation.
Test signals on a demo account before live trading.
Originality
The SwiftEdge NW Envelope stands out due to:
Its innovative use of Nadaraya-Watson regression, a less common but powerful tool for non-linear trend analysis.
A unique visual design with neon gradients and dynamic colors, inspired by AI and futuristic interfaces, making it both functional and visually engaging.
A streamlined signal system that balances momentum (RSI), volatility (ATR), and trend (Nadaraya-Watson), reducing noise and enhancing trade precision.
Notes
Best suited for volatile markets (e.g., forex, crypto, stocks) where price swings create clear envelope breakouts.
Adjust input parameters to match your trading style (e.g., shorter RSI period for scalping, wider bands for swing trading).
Always backtest and validate signals in your specific market and timeframe before trading.
Aesthetic RSI [AlchimistOfCrypto]🌌 Aesthetic RSI – Unveiling the Fractal Forces of Markets 🌌
Category: Momentum Indicators 📈
"The RSI oscillator, formalized through an advanced mathematical prism, reveals the underlying fractal structures of price movements. This indicator draws inspiration from quantum principles of divergence-convergence where the probability of a return to equilibrium increases proportionally to the distance from the median point. Our implementation employs sophisticated algorithmic smoothing to filter out the stochastic noise inherent in financial markets, allowing visualization of the true momentum forces according to thermodynamic entropy principles applied to trading systems."
📊 Professional Trading Application
The Aesthetic RSI is a visually stunning and mathematically refined take on the classic Relative Strength Index. With customizable settings, advanced smoothing, and eight unique visual palettes, it empowers traders to detect momentum shifts and divergences with unparalleled clarity.
⚙️ Indicator Configuration
- Length 📏
The core parameter (default: 20) that determines the calculation period.
- Lower values (8-14): Increase sensitivity for short-term trading.
- Higher values (21-34): Provide stronger signals for position trading.
- OverBought/OverSold Thresholds 🎯
Customizable boundaries (default: 75/25) to identify extreme market conditions.
- Calibrate based on asset volatility: Higher volatility assets may need wider thresholds (80/20) to reduce false signals.
- Style 🎨
Eight meticulously crafted visual palettes optimized for pattern recognition:
- Miami Vice (default): High-contrast cyan/magenta scheme for spotting divergences.
- Cyberpunk: Yellow/purple combo to highlight momentum shifts.
- Classic: Traditional green/red for conventional analysis.
- High Contrast: Maximum visual separation for traders with visual impairments.
- Specialized palettes (Forest, Ocean, Fire, Monochrome): Tailored for diverse market conditions.
- Mode Selection 🔄
- Full: Displays a complete gradient spectrum across the RSI range, emphasizing momentum transitions between 35-65.
- OverZone: Focuses on actionable extreme zones, reducing noise in ranging markets.
🚀 How to Use
1. Adjust Length ⏰: Set the period based on your trading style (short-term or long-term).
2. Fine-Tune Thresholds 🎚️: Customize overbought/oversold levels to match the asset’s volatility.
3. Select a Palette 🌈: Choose a visual style that enhances your pattern recognition.
4. Choose Mode 🔍: Use "Full" for detailed momentum analysis or "OverZone" for extreme zone focus.
5. Spot Divergences ✅: Look for price-RSI divergences to anticipate reversals.
6. Trade with Precision 🛡️: Combine with other indicators for high-probability setups.
📅 Release Notes (April 2025)
Aesthetic RSI blends quantum-inspired mathematics with artistic visualization, redefining momentum analysis. Stay tuned for future enhancements! ✨
🏷️ Tags
#Trading #TechnicalAnalysis #RSI #Momentum #Divergence #MultiTimeframe #TradingStrategy #RiskManagement #Forex #Stocks #Crypto #Bitcoin #AlgoTrading #DayTrading #SwingTrading #TheAlchimist #QuantumTrading #VisualTrading #PatternRecognition
Global M2 Liquidity [TheAlchimist]🌍 Global M2 Liquidity – Navigating the Quantum Field of Markets 🌍
Category: Macroeconomic Indicators 📊
"In quantum physics, the observer effect states that the mere act of observation changes the system being observed. Similarly, in financial markets, global liquidity acts as a quantum field that permeates all market states simultaneously. Just as Heisenberg’s uncertainty principle suggests we cannot precisely measure both position and momentum, the M2 money supply’s influence on market dynamics creates a complex web of cause and effect across multiple timeframes."
📈 Overview
The Global M2 Liquidity indicator is a powerful tool that tracks the combined M2 money supply from five major economies (US, EU, China, Japan, UK), converted to USD 💵, offering a panoramic view of global liquidity conditions. With multi-timeframe analysis and a customizable forward-shift feature, it empowers traders to anticipate market movements driven by liquidity trends.
✨ Features
- Global Coverage 🌎: Monitors M2 money supply from 5 major economic regions (US, EU, China, Japan, UK).
- Real-Time Conversion 💱: Converts all data to USD for consistent analysis.
- Multi-Timeframe Analysis ⏰: Tracks liquidity from 15-minute to weekly charts.
- Forward-Shift Capability 🔮: Aligns M2 data with future price action for predictive insights.
- Color-Coded Trends 🎨: Visualizes liquidity trends (🟢 Expansion, 🔴 Contraction).
🚀 How to Use
1. Main Line 📉: Displays total global M2 liquidity in trillions of USD.
2. Golden Moving Average ⭐: Identifies the overall trend direction.
3. Trend Colors 🟢🔴:
- Green: Liquidity expanding above the moving average (bullish for risk assets).
- Red: Liquidity contracting below the moving average (bearish signal).
4. Forward Shift ⏩: Use the shift parameter to align M2 data with price action for predictive analysis.
5. Combine with Price Action 🔍: Correlate liquidity trends with assets like Bitcoin, stocks, or forex for strategic entries/exits.
⚙️ Settings
- MA Period 📏: Length of the moving average (default: 50).
- Shift ⏳: Number of days to shift data forward (default: 60).
🏷️ Tags
#Trading #Macroeconomic #M2Liquidity #GlobalLiquidity #MoneySupply #MultiTimeframe #TrendAnalysis #PredictiveAnalysis #Forex #Stocks #Crypto #Bitcoin #RiskAssets #CentralBanks #USD #TheAlchimist #QuantumTrading #AlgoTrading #DayTrading #SwingTrading
MACD [AlchimistOfCrypto]🌠 MACD Optimized with Python – Decoding the Chaos of Markets 🌠
Category: Trend Analysis 📈
"Like the dynamic systems studied in chaos theory, financial markets appear unpredictable at first glance. Yet, as Edward Lorenz demonstrated, even in apparent chaos reside harmonious mathematical structures. The MACD (Moving Average Convergence Divergence) represents this quest for order within disorder—a mathematical formulation that extracts coherent signals from price noise. By combining moving averages of different periods, this indicator reveals hidden cycles and precise moments when market energy shifts, like a pendulum obeying the immutable laws of physics."
📊 Technical Overview
The MACD Optimized with Python is a revolutionary take on the classic Moving Average Convergence Divergence indicator. Powered by Python-driven optimizations 🐍, it adapts to specific timeframes, delivering razor-sharp signals for traders seeking to navigate the market’s chaos with precision.
⚙️ How It Works
- Python-Optimized Parameters 🔧: Unlike the standard MACD (12,26,9), our version uses mathematically tailored parameters for each timeframe:
- 1H: 11/38/27
- 4H: 9/98/27
- 1D: 45/90/29
- 1W: 9/16/3
- 2W: 5/20/5
- Intuitive Visuals 🎨:
- Crossovers marked by colored dots 🟢🔴 for clear entry/exit signals.
- Histogram with a color gradient 🌈 to show direction and momentum intensity.
- Customizable Signals 🎯: Choose to display long, short, or both signals to match your trading style.
🚀 How to Use This Indicator
1. Select Your Timeframe ⏰: Choose the timeframe aligned with your trading horizon (1H, 4H, 1D, 1W, or 2W).
2. Spot Crossovers 🔍: Watch for the MACD line (green) crossing the signal line (red) to identify potential trend changes.
3. Confirm with Divergence ✅: Combine crossovers with price-MACD divergence for high-probability trend reversal signals.
📅 Release Notes
Unlock the hidden order of markets with this Python-optimized MACD. Stay tuned for future enhancements! ✨
🏷️ Tags
#Trading #TechnicalAnalysis #MACD #TrendAnalysis #Python #MultiTimeframe #Divergence #Momentum #TradingStrategy #RiskManagement #Forex #Stocks #Crypto #ChaosTheory #OptimizedTrading
Trend Breakout [Uncle Sam Trading]Trend Breakout Indicator
Overview
The Trend Breakout Indicator is a powerful, non-repainting tool designed to help traders identify high-probability breakout and trend reversal setups on any market and timeframe. By leveraging pivot points, this indicator draws dynamic support and resistance channels, highlights counter-trend breakouts, and provides visual cues for market direction. It’s ideal for traders looking to simplify their analysis while targeting key price levels for entries and exits.
Key Features
Pivot-Based Channels: Draws a red upper channel (resistance) and a green lower channel (support) by connecting recent pivot highs and lows.
Counter-Trend Breakout Signals:
Blue “CT Breakup” signal (▲) when the price breaks above the upper channel during a downtrend, indicating a potential reversal or pullback.
Orange “CT Breakdown” signal (▼) when the price breaks below the lower channel during an uptrend, signaling a potential downmove.
Trend Visualization: Background color shifts to green for uptrends and red for downtrends, making it easy to gauge market direction.
Customizable Settings: Adjust pivot detection sensitivity with “Pivot Left Bars” (default: 5) and “Pivot Right Bars” (default: 1), and control channel extension with “Channel Extension Bars” (default: 50).
Optional Trend Signals: Enable “Show Trend Change Signals” to display trend shifts with green (uptrend) or red (downtrend) arrows.
Alert Conditions: Set alerts for counter-trend breakouts and trend changes directly on TradingView.
Example Performance (BTCUSDT, 1-Hour Chart)
On the BTCUSDT 1-hour chart:
A “CT Breakdown” signal appeared on April 6 at 8:00 AM at $82,700, followed by a drop to $74,400 within hours—a 10% move.
A “CT Breakup” signal occurred on April 9 at 1:00 AM at $76,600, leading to a rally to $86,600 in a few hours—a 9% gain.
These examples highlight the indicator’s ability to spot significant price movements, though results depend on market conditions, your trading style, and risk management.
Settings
Pivot Left Bars (default: 5): Number of bars to the left for pivot detection.
Pivot Right Bars (default: 1): Number of bars to the right for pivot confirmation (ensures non-repainting signals).
Channel Extension Bars (default: 50): How far the channels extend to the right.
Show Pivot Points (default: true): Displays small triangles at pivot highs (maroon) and lows (navy).
Show Counter-Trend Breakout Signals (default: true): Shows CT Breakup and CT Breakdown signals.
Show Trend Change Signals (default: false): Displays trend shift arrows when enabled.
How to Use
Add the indicator to your chart via TradingView’s indicator library.
Adjust the settings to match your trading style and timeframe.
Watch for “CT Breakup” and “CT Breakdown” signals to identify potential trade setups.
Use the background color (green/red) to confirm the current trend.
Set alerts for breakouts or trend changes to stay updated on key signals.
Always combine with proper risk management and your own analysis—past performance is not a guarantee of future results.
Notes
The indicator is non-repainting, meaning signals are confirmed and won’t disappear after they form.
Works on any market (crypto, forex, stocks) and timeframe, such as the BTCUSDT 1-hour chart shown.
Performance varies based on market volatility and your trading strategy.
This is a free tool created to support the TradingView community—feedback is welcome in the comments!
Disclaimer
Trading involves risk, and this indicator is not a guaranteed predictor of future price movements. Always conduct your own analysis and manage risk appropriately. The examples provided (e.g., BTCUSDT signals) are for educational purposes only and reflect past performance, which may not repeat.
Price Position Percentile (PPP)
Price Position Percentile (PPP)
A statistical analysis tool that dynamically measures where current price stands within its historical distribution. Unlike traditional oscillators, PPP adapts to market conditions by calculating percentile ranks, creating a self-adjusting framework for identifying extremes.
How It Works
This indicator analyzes the last 200 price bars (customizable) and calculates the percentile rank of the current price within this distribution. For example, if the current price is at the 80th percentile, it means the price is higher than 80% of all prices in the lookback period.
The indicator creates five dynamic zones based on percentile thresholds:
Extremely Low Zone (<5%) : Prices in the lowest 5% of the distribution, indicating potential oversold conditions.
Low Zone (5-25%) : Accumulation zone where prices are historically low but not extreme.
Neutral Zone (25-75%) : Fair value zone representing the middle 50% of the price distribution.
High Zone (75-95%) : Distribution zone where prices are historically high but not extreme.
Extremely High Zone (>95%) : Prices in the highest 5% of the distribution, suggesting potential bubble conditions.
Mathematical Foundation
Unlike fixed-threshold indicators, PPP uses a non-parametric approach:
// Core percentile calculation
percentile = (count_of_prices_below_current / total_prices) * 100
// Threshold calculation using built-in function
p_extremely_low = ta.percentile_linear_interpolation(source, lookback, 5)
p_low = ta.percentile_linear_interpolation(source, lookback, 25)
p_neutral_high = ta.percentile_linear_interpolation(source, lookback, 75)
p_extremely_high = ta.percentile_linear_interpolation(source, lookback, 95)
Key Features
Dynamic Adaptation : All zones adjust automatically as price distribution changes
Statistical Robustness : Works on any timeframe and any market, including highly volatile cryptocurrencies
Visual Clarity : Color-coded zones provide immediate visual context
Non-parametric Analysis : Makes no assumptions about price distribution shape
Historical Context : Shows how zones evolved over time, revealing market regime changes
Practical Applications
PPP provides objective statistical context for price action, helping traders make more informed decisions based on historical price distribution rather than arbitrary levels.
Value Investment : Identify statistically significant low prices for potential entry points
Risk Management : Recognize when prices reach historical extremes for profit taking
Cycle Analysis : Observe how percentile zones expand and contract during different market phases
Market Regime Detection : Identify transitions between accumulation, markup, distribution, and markdown phases
Usage Guidelines
This indicator is particularly effective when:
- Used across multiple timeframes for confirmation
- Combined with volume analysis for validation of extremes
- Applied in conjunction with trend identification tools
- Monitored for divergences between price action and percentile ranking
BONK 1H Long Volatility StrategyGrok 1hr bonk strategy:
Key Changes and Why They’re Made
1. Indicator Adjustments
Moving Averages:
Fast MA: Changed to 5 periods (from, e.g., 9 on a higher timeframe).
Slow MA: Changed to 13 periods (from, e.g., 21).
Why: Shorter periods make the moving averages more sensitive to quick price changes on the 1-hour chart, helping identify trends faster.
ATR (Average True Range):
Length: Set to 10 periods (down from, e.g., 14).
Multiplier: Reduced to 1.5 (from, e.g., 2.0).
Why: A shorter ATR length tracks recent volatility better, and a lower multiplier lets the strategy catch smaller price swings, which are more common hourly.
RSI:
Kept at 14 periods with an overbought level of 70.
Why: RSI stays the same to filter out overbought conditions, maintaining consistency with the original strategy.
2. Entry Conditions
Trend: Requires the fast MA to be above the slow MA, ensuring a bullish direction.
Volatility: The candle’s range (high - low) must exceed 1.5 times the ATR, confirming a significant move.
Momentum: RSI must be below 70, avoiding entries at potential peaks.
Price: The close must be above the fast MA, signaling a pullback or trend continuation.
Why: These conditions are tightened to capture frequent volatility spikes while filtering out noise, which is more prevalent on a 1-hour chart.
3. Exit Strategy
Profit Target: Default is 5% (adjustable from 3-7%).
Stop-Loss: Default is 3% (adjustable from 1-5%).
Why: These levels remain conservative to lock in gains quickly and limit losses, suitable for the faster pace of a 1-hour timeframe.
4. Risk Management
The strategy may trigger more trades on a 1-hour chart. To avoid overtrading:
The ATR filter ensures only volatile moves are traded.
Trading fees (e.g., 0.5% on Coinbase) reduce the net profit to ~4% on winners and -3.5% on losers, requiring a win rate above 47% for profitability.
Suggestion: Risk only 1-2% of your capital per trade to manage exposure.
5. Visuals and Alerts
Plots: Blue fast MA, red slow MA, and green triangles for buy signals.
Alerts: Trigger when an entry condition is met, so you don’t need to watch the chart constantly.
How to Use the Strategy
Setup:
Load TradingView, select BONK/USD on the 1-hour chart (Coinbase pair).
Paste the script into the Pine Editor and add it to your chart.
Customize:
Adjust the profit target (e.g., 5%) and stop-loss (e.g., 3%) to your preference.
Tweak ATR or MA lengths if BONK’s volatility shifts.
Trade:
Look for green triangle signals and confirm with market context (e.g., volume or news).
Enter trades manually or via TradingView’s broker tools if supported.
Exit when the profit target or stop-loss is hit.
Test:
Use TradingView’s Strategy Tester to backtest on historical data and refine settings.
Benefits of the 1-Hour Timeframe
Faster Opportunities: Captures shorter-term uptrends in BONK’s volatile price action.
Responsive: Adjusted indicators react quickly to hourly changes.
Conservative: Maintains the 3-7% profit goal with tight risk control.
Potential Challenges
Noise: The 1-hour chart has more false signals. The ATR and MA filters help, but caution is needed.
Fees: Frequent trading increases costs, so ensure each trade’s potential justifies the expense.
Volatility: BONK can move unpredictably—monitor broader market trends or Solana ecosystem news.
Final Thoughts
Switching to a 1-hour timeframe makes the strategy more active, targeting shorter volatility spikes while keeping profits conservative at 3-7%. The adjusted indicators and conditions balance responsiveness with reliability. Backtest it on TradingView to confirm it suits BONK’s behavior, and always use proper risk management, as meme coins are highly speculative.
Disclaimer: This is for educational purposes, not financial advice. Cryptocurrency trading, especially with assets like BONK, is risky. Test thoroughly and trade responsibly.
RSI VWAP POC [Uncle Sam Trading]Category: Oscillators, Volume, Market Profile
Timeframe: Suitable for all timeframes
Markets: Crypto, Forex, Stocks, Commodities
Overview
The RSI VWAP POC indicator is a powerful and innovative oscillator that combines the Relative Strength Index (RSI), Volume-Weighted Average Price (VWAP), and Point of Control (POC) from market profile analysis. Designed to provide traders with clear, high-probability trading signals, this indicator helps you identify key market levels, spot overbought/oversold conditions, and time your entries and exits with precision. Whether you’re a day trader, swing trader, or scalper, this free tool adds significant value to your trading strategy by offering a unique blend of momentum, volume, and market profile insights.
How It Works
This indicator integrates three core components to deliver actionable insights:
RSI (Relative Strength Index): Measures momentum to identify overbought (above 70) and oversold (below 30) conditions, helping you anticipate potential reversals.
VWAP (Volume-Weighted Average Price): Calculates a volume-weighted price benchmark, which is used to compute a more accurate, volume-sensitive RSI. This ensures the indicator reflects true market dynamics.
POC (Point of Control): Derived from market profile analysis, the POC represents the price level with the highest traded volume in a session, acting as a critical support or resistance level.
The indicator plots a smoothed RSI based on VWAP, overlaid with market profile data on a user-defined higher timeframe (default: 4H). The POC is displayed as a red line, with aqua bars indicating the value area where the majority of trading volume occurred. When the RSI crosses the POC, the indicator generates clear buy and sell signals:
Strong Buy (SBU): RSI crosses above the POC in an oversold zone.
Strong Sell (SBD): RSI crosses below the POC in an overbought zone.
Additional features include:
Background colors to highlight bullish (green) or bearish (red) trends.
Shaded zones for overbought (70/60) and oversold (30/40) levels.
Customizable settings to fit your trading style and timeframe.
How This Indicator Adds Value
The RSI VWAP POC indicator offers several key benefits that enhance your trading performance:
High-Probability Signals: By combining RSI, VWAP, and POC, this indicator identifies trades at key market levels where price is likely to react, increasing your win rate.
Improved Timing: Clear buy and sell signals, such as ‘SBU’ and ‘SBD’, help you enter and exit trades at optimal points, maximizing profitability.
Risk Management: Overbought/oversold zones and trend confirmation via background colors help you avoid false signals, protecting your capital.
Versatility: Suitable for all markets (crypto, forex, stocks) and timeframes, making it a valuable tool for traders of all experience levels.
Time Efficiency: The indicator does the heavy lifting by analyzing momentum, volume, and market profile data, allowing you to focus on executing trades.
Real-World Performance Example: On a 1-hour Bitcoin chart with a 4-hour higher timeframe, this indicator identified a strong sell signal on April 6th at 12:00 ($82,000), leading to a 9% drop to $74,600. A subsequent strong buy signal on April 7th at 04:00 ($76,200) captured a 6% rise to $81,200 – a potential 25% profit with 5x leverage if exited at 5%.
How to Use
Add the Indicator: Search for “RSI VWAP POC ” in TradingView’s indicator library and add it to your chart.
Set Your Timeframe: The indicator works on any timeframe but is optimized for a 1-hour chart with a 4-hour higher timeframe (set in the settings).
Interpret Signals:
Look for ‘SBU’ (strong buy) labels when the RSI crosses above the POC in an oversold zone, indicating a potential buying opportunity.
Look for ‘SBD’ (strong sell) labels when the RSI crosses below the POC in an overbought zone, signaling a potential selling opportunity.
Use the background colors (green for bullish, red for bearish) to confirm the trend.
Combine with Your Strategy: Use the indicator alongside your existing analysis (e.g., support/resistance, candlestick patterns) for best results.
Settings and Customization
The indicator is highly customizable to suit your trading needs:
RSI Length (Default: 14): Adjust the sensitivity of the RSI. Use a shorter length (e.g., 10) for scalping, or a longer length (e.g., 20) for smoother signals.
EMA Smoothing Length (Default: 3): Smooths the RSI line. Increase to 5 or 7 for less choppy signals in volatile markets.
Higher Timeframe (Default: 240 minutes): Set to 240 (4 hours) for a 1-hour chart. Adjust based on your chart’s timeframe (e.g., 60 minutes for a 15-minute chart).
Value Area Percentage (Default: 100%): Defines the size of the value area around the POC. Lower to 70% for a tighter focus on key levels.
Overbought/Oversold Thresholds (Defaults: 70/30): Adjust these levels to match market conditions (e.g., 80/20 for trending markets).
Show POC Line (Default: True): Toggle the red POC line on or off.
Show Buy/Sell Signals: Enable ‘Show Strong Breakup Signals’ and ‘Show Strong Breakdown Signals’ to focus on high-probability trades.
Why Choose This Indicator?
The RSI VWAP POC indicator stands out by offering a unique combination of momentum, volume, and market profile analysis in a single, easy-to-use tool. It’s designed to help traders of all levels make informed decisions, reduce risk, and increase profitability. Whether you’re trading Bitcoin, forex pairs, or stocks, this indicator provides the clarity and precision you need to succeed.
Institutional Quantum Momentum Impulse [BullByte]## Overview
The Institutional Quantum Momentum Impulse (IQMI) is a sophisticated momentum oscillator designed to detect institutional-level trend strength, volatility conditions, and market regime shifts. It combines multiple advanced technical concepts, including:
- Quantum Momentum Engine (Hilbert Transform + MACD Divergence + Stochastic Energy)
- Fractal Volatility Scoring (GARCH + Keltner-based volatility)
- Dynamic Adaptive Bands (Self-adjusting thresholds based on efficiency)
- Market Phase Detection (Volume + Momentum alignment)
- Liquidity & Cumulative Delta Analysis
The indicator provides a Z-score normalized momentum reading, making it ideal for mean-reversion and trend-following strategies.
---
## Key Features
### 1. Quantum Momentum Core
- Combines Hilbert Transform, MACD divergence, and Stochastic Energy into a single composite momentum score.
- Normalized using a Z-score for statistical significance.
- Smoothed with EMA/WMA/HMA for cleaner signals.
### 2. Dynamic Adaptive Bands
- Upper/Lower bands adjust based on volatility and efficiency ratio .
- Acts as overbought/oversold zones when momentum reaches extremes.
### 3. Market Phase Detection
- Identifies bullish , bearish , or neutral phases using:
- Volume-Weighted MA alignment
- Fractal momentum extremes
### 4. Volatility & Liquidity Filters
- Fractal Volatility Score (0-100 scale) shows market instability.
- Liquidity Check ensures trades are taken in favorable spread conditions.
### 5. Dashboard & Visuals
- Real-time dashboard with key metrics:
- Momentum strength, volatility, efficiency, cumulative delta, and market regime.
- Gradient coloring for intuitive momentum visualization .
---
## Best Trade Setups
### 1. Trend-Following Entries
- Signal :
- QM crosses above zero + Market Phase = Bullish + ADX > 25
- Cumulative Delta rising (buying pressure)
- Confirmation :
- Efficiency > 0.5 (strong momentum quality)
- Liquidity = High (tight spreads)
### 2. Mean-Reversion Entries
- Signal :
- QM touches upper band + Volatility expanding
- Market Regime = Ranging (ADX < 25)
- Confirmation :
- Efficiency < 0.3 (weak momentum follow-through)
- Cumulative Delta divergence (price high but delta declining)
### 3. Breakout Confirmation
- Signal :
- QM holds above zero after a pullback
- Market Phase shifts to Bullish/Bearish
- Confirmation :
- Volatility rising (expansion phase)
- Liquidity remains high
---
## Recommended Timeframes
- Intraday (5M - 1H): Works well for scalping & swing trades.
- Swing Trading (4H - Daily): Best for trend-following setups.
- Position Trading (Weekly+): Useful for macro trend confirmation.
---
## Input Customization
- Resonance Factor (1.0 - 3.618 ): Adjusts MACD divergence sensitivity.
- Entropy Filter (0.382/0.50/0.618) : Controls stochastic damping.
- Smoothing Type (EMA/WMA/HMA) : Changes momentum responsiveness.
- Normalization Period : Adjusts Z-score lookback.
---
The IQMI is a professional-grade momentum indicator that combines institutional-level concepts into a single, easy-to-read oscillator. It works across all markets (stocks, forex, crypto) and is ideal for traders who want:
✅ Early trend detection
✅ Volatility-adjusted signals
✅ Institutional liquidity insights
✅ Clear dashboard for quick analysis
Try it on TradingView and enhance your trading edge! 🚀
Happy Trading!
- BullByte
Deadzone Pro @DaviddTechDeadzone Pro by @DaviddTech – Adaptive Multi-Strategy NNFX Trading System
Deadzone Pro by @DaviddTech is a meticulously engineered trading indicator that strictly adheres to the No-Nonsense Forex (NNFX) methodology. It integrates adaptive trend detection, dual confirmation indicators, advanced volatility filtering, and dynamic risk management into one powerful, visually intuitive system. Ideal for traders seeking precision and clarity, this indicator consistently delivers high-probability trade setups across all market conditions.
🔥 Key Features:
The Setup:
Adaptive Hull Moving Average Baseline: Clearly identifies trend direction using an advanced, gradient-colored Hull MA that intensifies based on trend strength, providing immediate visual clarity.
Dual Confirmation Indicators: Combines Waddah Attar Explosion (momentum detector) and Bull/Bear Power (strength gauge) for robust validation, significantly reducing false entries.
Volatility Filter (ADX): Ensures entries are only made during strong trending markets, filtering out weak, range-bound scenarios for enhanced trade accuracy.
Dynamic Trailing Stop Loss: Implements a SuperTrend-based trailing stop using adaptive ATR calculations, managing risk effectively while optimizing exits.
Dashboard:
💎 Gradient Visualization & User Interface:
Dynamic gradient colors enhance readability, clearly indicating bullish/bearish strength.
Comprehensive dashboard summarizes component statuses, real-time market sentiment, and entry conditions at a glance.
Distinct and clear buy/sell entry and exit signals, with adaptive stop-loss levels visually plotted.
Candlestick coloring based on momentum signals (Waddah Attar) for intuitive market reading.
📈 How to Interpret Signals:
Bullish Signal: Enter when Hull MA baseline trends upward, both confirmation indicators align bullish, ADX indicates strong trend (>25), and price breaks above the previous trailing stop.
Bearish Signal: Enter short or exit long when Hull MA baseline trends downward, confirmations indicate bearish momentum, ADX confirms trend strength, and price breaks below previous trailing stop.
📊 Recommended Usage:
Timeframes: Ideal on 1H, 4H, and Daily charts for swing trading; effective on shorter (5M, 15M) charts for day trading.
Markets: Compatible with Forex, Crypto, Indices, Stocks, and Commodities.
The Entry & Exit:
🎯 Trading Styles:
Choose from three distinct trading modes:
Conservative: Requires full alignment of all indicators for maximum accuracy.
Balanced (Default): Optimized balance between signal frequency and reliability.
Aggressive: Fewer confirmations needed for more frequent trading signals.
📝 Credits & Originality:
Deadzone Pro incorporates advanced concepts inspired by:
Hull Moving Average by @Julien_Eche
Waddah Attar Explosion by @LazyBear
Bull Bear Power by @Pinecoders
ADX methodology by @BeikabuOyaji
This system has been significantly refactored and enhanced by @DaviddTech to maximize synergy, clarity, and usability, standing apart distinctly from its original components.
Deadzone Pro exemplifies precision and discipline, aligning fully with NNFX principles to provide traders with a comprehensive yet intuitive trading advantage.
EMA Crossover (Short Focus with Trailing Stop)This strategy utilizes a combination of Exponential Moving Averages (EMA) and Simple Moving Averages (SMA) to generate entry and exit signals for both long and short positions. The core of the strategy is based on the 13-period EMA (short EMA) crossing the 33-period EMA (long EMA) for entering long trades, while a 13-period EMA crossing the 25-period EMA (mid EMA) generates short trade signals. The 100-period SMA and 200-period SMA serve as additional trend indicators to provide context for the market conditions. The strategy aims to capitalize on trend reversals and momentum shifts in the market.
The strategy is designed to execute trades swiftly with an emphasis on entering positions when conditions align in real time. For long entries, the strategy initiates a buy when the 13 EMA is greater than the 33 EMA, indicating a bullish trend. For short entries, the 13 EMA crossing below the 33 EMA signals a bearish trend, prompting a short position. Importantly, the code includes built-in exit conditions for both long and short positions. Long positions are exited when the 13 EMA falls below the 33 EMA, while short positions are closed when the 13 EMA crosses above the 25 EMA.
A key feature of the strategy is the use of trailing stops for both long and short positions. This dynamic exit method adjusts the stop level as the market moves in favor of the trade, locking in profits while reducing the risk of losses. The trailing stop for long positions is based on the high price of the current bar, while the trailing stop for short positions is set using the low price, providing more flexibility in managing risk. This trailing stop mechanism helps to capture profits from favorable market moves while ensuring that positions are exited if the market moves against them.
This strategy works best on the daily timeframe and is optimized for major cryptocurrency pairs. The daily chart allows for the EMAs to provide more reliable signals, as the strategy is designed to capture broader trends rather than short-term market fluctuations. Using it on major crypto pairs increases its effectiveness as these assets tend to have strong and sustained trends, providing better opportunities for the strategy to perform well.
Customizable RSI/StochRSI Double ConfirmationBelow are the key adjustable parameters in the script and their usage:
RSI Parameters
RSI Length: The number of periods used to calculate the RSI, with a default value of 7. Adjusting this parameter changes the sensitivity of the RSI—shorter periods make it more sensitive, while longer periods make it smoother.
RSI Source: The price source used for RSI calculation, defaulting to the closing price (close). This can be changed to the opening price or other price types as needed.
StochRSI Parameters
StochRSI Length: The number of periods used to calculate the StochRSI, with a default value of 5. This affects how quickly the StochRSI reacts to changes in the RSI.
StochRSI Smooth K: The smoothing period for the StochRSI %K line, with a default value of 3. This is used to reduce noise.
StochRSI Smooth D: The smoothing period for the StochRSI %D line, with a default value of 3. It works in conjunction with %K to provide more stable signals.
Signal Thresholds
RSI Buy Threshold: A buy signal is triggered when the RSI crosses above this value (default 20).
RSI Sell Threshold: A sell signal is triggered when the RSI crosses below this value (default 80).
StochRSI Buy Threshold: A buy signal is triggered when the StochRSI %K crosses above this value (default 20).
StochRSI Sell Threshold: A sell signal is triggered when the StochRSI %K crosses below this value (default 80).
Signals
RSI Buy/Sell Signals: When the RSI crosses the buy/sell threshold, a green "RSI Buy" or red "RSI Sell" is displayed on the chart.
StochRSI Buy/Sell Signals: When the StochRSI %K crosses the buy/sell threshold, a yellow "StochRSI Buy" or purple "StochRSI Sell" is displayed.
Double Buy/Sell Signals: When both RSI and StochRSI simultaneously trigger buy/sell signals, a green "Double Buy" or red "Double Sell" is displayed, indicating a stronger trading opportunity.
The volatility of different cryptocurrencies varies, and different parameters may be suitable for each. Users need to experiment and select the most appropriate parameters themselves.
Disclaimer: This script is for informational purposes only and should not be considered financial advice; use it at your own risk.
Portfolio Monitor - DolphinTradeBot1️⃣ Overview
▪️This indicator unifies the value of all your investments—whether stocks, currencies, or cryptocurrencies—in your chosen currency. This tool not only provides a clear snapshot of your overall portfolio performance but also highlights the individual growth of each asset with intuitive visualizations and an easy-to-understand performance report.
2️⃣ What sets this indicator apart
▪️is its ability to convert values from various currency pairs into any currency you choose. This means you can monitor your portfolio's performance against any currency pair you prefer, offering a flexible and comprehensive view of your investments.
3️⃣ How Is It Work ?
🔍The indicator can be analyzed under two main categories: visual representations and tables.
1- Visual representations ;
The indicator includes three different types of lines:
1. 1 - Reference Line → This represents the cost of all assets we hold, based on the selected date.
1. 2 - Total Assets Line → Displays the real-time value of all assets in our possession, including cash value, in the selected trading pair.
The area between the reference line is filled with green and red. The section above the reference line is represented in green, while the section below is shown in red.
1. 3 - Performance Lines → These visualize the performance of the assets, starting from the reference line and taking into account their weights in the portfolio. (Note: The lines are scaled for visualization purposes, so their absolute values should not be considered.)
"The names of the lines are shown in the image below."⤵️
2- Tables
The indicator includes three different types of tables:
2. 1 - Analysis Table : It provides a superficial overview of wallet statistics and values.
▪️TOTAL ASSETS → The current equivalent of all assets in the target currency
▪️CASH VALUE → The current value of the amount "Cash Value", in the target currency.
▪️PORTFOLIO VALUE → The total value of assets excluding Cash, in the target currency.
▪️POSTFOLIO COST → The cost of assets excluding Cash, in the target currency.
▪️PORTFOLIO ABSOLUTE RETURN → It shows the profit or loss relative to the cost of assets
▪️PORTFOLIO RETURN % →It shows the profit or loss relative to the cost of assets on a percentage basis
2. 2 - Performance Table : It displays the names of assets excluding Cash and their profit amounts, sorted from highest to lowest profit. If "Show as Percentage" is selected in the settings, it shows the percentage profit or loss relative to the cost. Profits are represented in green, while losses are represented in red.
"You can see the visual showing the tables below"⤵️
4️⃣How to Use ?
1- Choose the date on which the visualization will begin (📌The start date only affects the exchange rate used for calculating the reference line in the target currency.)
2- If you have cash holdings, enter the amount and specify the currency.
3- Select the currency in which your portfolio value will be displayed.(Default value is USD)
4- To set up your portfolio;
SYMBOLS - QUANTITY - PURCHASE PRICE
Enter the symbols of your assets - the number of units you hold - and their cost levels.
5- If you have cash, be sure to include your cash balance. If you also hold other currencies, enter them as separate assets with their corresponding quantities and purchase prices.
6- If you want to see the percentage returns of the assets in the performance table relative to their cost, select the "Show as Percent" option.
7- If you want to see the performance visuals of the assets, click on the "Show Asset Performance" option.
You can find an image of the settings section where the numbers above are used as references below.⤵️
📌 NOTE → By default, a few assets and their values have been pre-added in the initial settings. This is to ensure that you don’t see an empty screen when adding the indicator to the chart. Please remember to enter your own assets and values. The default settings are only provided as an example.
Stop Loss / Take Profit Table// (\_/)
// ( •.•)
// (")_(")
📈 Introducing the Stop Loss / Take Profit Table Indicator! 📈
Enhance your trading strategy with our powerful Stop Loss / Take Profit Table indicator, designed for traders in the Crypto, Stock, and Forex markets. This easy-to-use tool helps you manage risk and maximize profits by clearly displaying your Stop Loss and Take Profit levels based on your trading position.
Key Features:
Custom Asset Types: Choose between Crypto, Stock, or Forex to tailor the indicator to your specific trading style.
Dynamic Stop Loss & Take Profit Calculation: Set your desired Stop Loss percentage, and the indicator will automatically calculate your Stop Loss and two Take Profit levels based on different timeframes (1 min to 240 min).
Position Type Flexibility: Whether you're trading Long or Short, the indicator adjusts the calculations accordingly, providing you with precise price levels for effective risk management.
Visual Representation: Stop Loss and Take Profit levels are marked directly on the chart with distinctive horizontal lines in vibrant colors for easy reference.
Informative Table Display: A dedicated table displayed on the chart shows your asset type, position type, and calculated prices for Stop Loss and Take Profit levels, ensuring you have all critical data at a glance.
Alert Notifications: Stay informed with optional alerts that signal when your Stop Loss or Take Profit levels are hit, allowing you to react swiftly in fast-moving markets.
Why Use This Indicator?
Managing your trades is critical for success in the financial markets. With our Stop Loss / Take Profit Table, you can easily set your parameters and visually track your risk and reward levels, making it a practical addition to any trader's toolkit.
Get started today and take control of your trading strategy! ✨
Happy trading! 📊🚀
Strategy Stats [presentTrading]Hello! it's another weekend. This tool is a strategy performance analysis tool. Looking at the TradingView community, it seems few creators focus on this aspect. I've intentionally created a shared version. Welcome to share your idea or question on this.
█ Introduction and How it is Different
Strategy Stats is a comprehensive performance analytics framework designed specifically for trading strategies. Unlike standard strategy backtesting tools that simply show cumulative profits, this analytics suite provides real-time, multi-timeframe statistical analysis of your trading performance.
Multi-timeframe analysis: Automatically tracks performance metrics across the most recent time periods (last 7 days, 30 days, 90 days, 1 year, and 4 years)
Advanced statistical measures: Goes beyond basic metrics to include Information Coefficient (IC) and Sortino Ratio
Real-time feedback: Updates performance statistics with each new trade
Visual analytics: Color-coded performance table provides instant visual feedback on strategy health
Integrated risk management: Implements sophisticated take profit mechanisms with 3-step ATR and percentage-based exits
BTCUSD Performance
The table in the upper right corner is a comprehensive performance dashboard showing trading strategy statistics.
Note: While this presentation uses Vegas SuperTrend as the underlying strategy, this is merely an example. The Stats framework can be applied to any trading strategy. The Vegas SuperTrend implementation is included solely to demonstrate how the analytics module integrates with a trading strategy.
⚠️ Timeframe Limitations
Important: TradingView's backtesting engine has a maximum storage limit of 10,000 bars. When using this strategy stats framework on smaller timeframes such as 1-hour or 2-hour charts, you may encounter errors if your backtesting period is too long.
Recommended Timeframe Usage:
Ideal for: 4H, 6H, 8H, Daily charts and above
May cause errors on: 1H, 2H charts spanning multiple years
Not recommended for: Timeframes below 1H with long history
█ Strategy, How it Works: Detailed Explanation
The Strategy Stats framework consists of three primary components: statistical data collection, performance analysis, and visualization.
🔶 Statistical Data Collection
The system maintains several critical data arrays:
equityHistory: Tracks equity curve over time
tradeHistory: Records profit/loss of each trade
predictionSignals: Stores trade direction signals (1 for long, -1 for short)
actualReturns: Records corresponding actual returns from each trade
For each closed trade, the system captures:
float tradePnL = strategy.closedtrades.profit(tradeIndex)
float tradeReturn = strategy.closedtrades.profit_percent(tradeIndex)
int tradeType = entryPrice < exitPrice ? 1 : -1 // Direction
🔶 Performance Metrics Calculation
The framework calculates several key performance metrics:
Information Coefficient (IC):
The correlation between prediction signals and actual returns, measuring forecast skill.
IC = Correlation(predictionSignals, actualReturns)
Where Correlation is the Pearson correlation coefficient:
Correlation(X,Y) = (nΣXY - ΣXY) / √
Sortino Ratio:
Measures risk-adjusted return focusing only on downside risk:
Sortino = (Avg_Return - Risk_Free_Rate) / Downside_Deviation
Where Downside Deviation is:
Downside_Deviation = √
R_i represents individual returns, T is the target return (typically the risk-free rate), and n is the number of observations.
Maximum Drawdown:
Tracks the largest percentage drop from peak to trough:
DD = (Peak_Equity - Trough_Equity) / Peak_Equity * 100
🔶 Time Period Calculation
The system automatically determines the appropriate number of bars to analyze for each timeframe based on the current chart timeframe:
bars_7d = math.max(1, math.round(7 * barsPerDay))
bars_30d = math.max(1, math.round(30 * barsPerDay))
bars_90d = math.max(1, math.round(90 * barsPerDay))
bars_365d = math.max(1, math.round(365 * barsPerDay))
bars_4y = math.max(1, math.round(365 * 4 * barsPerDay))
Where barsPerDay is calculated based on the chart timeframe:
barsPerDay = timeframe.isintraday ?
24 * 60 / math.max(1, (timeframe.in_seconds() / 60)) :
timeframe.isdaily ? 1 :
timeframe.isweekly ? 1/7 :
timeframe.ismonthly ? 1/30 : 0.01
🔶 Visual Representation
The system presents performance data in a color-coded table with intuitive visual indicators:
Green: Excellent performance
Lime: Good performance
Gray: Neutral performance
Orange: Mediocre performance
Red: Poor performance
█ Trade Direction
The Strategy Stats framework supports three trading directions:
Long Only: Only takes long positions when entry conditions are met
Short Only: Only takes short positions when entry conditions are met
Both: Takes both long and short positions depending on market conditions
█ Usage
To effectively use the Strategy Stats framework:
Apply to existing strategies: Add the performance tracking code to any strategy to gain advanced analytics
Monitor multiple timeframes: Use the multi-timeframe analysis to identify performance trends
Evaluate strategy health: Review IC and Sortino ratios to assess predictive power and risk-adjusted returns
Optimize parameters: Use performance data to refine strategy parameters
Compare strategies: Apply the framework to multiple strategies to identify the most effective approach
For best results, allow the strategy to generate sufficient trade history for meaningful statistical analysis (at least 20-30 trades).
█ Default Settings
The default settings have been carefully calibrated for cryptocurrency markets:
Performance Tracking:
Time periods: 7D, 30D, 90D, 1Y, 4Y
Statistical measures: Return, Win%, MaxDD, IC, Sortino Ratio
IC color thresholds: >0.3 (green), >0.1 (lime), <-0.1 (orange), <-0.3 (red)
Sortino color thresholds: >1.0 (green), >0.5 (lime), <0 (red)
Multi-Step Take Profit:
ATR multipliers: 2.618, 5.0, 10.0
Percentage levels: 3%, 8%, 17%
Short multiplier: 1.5x (makes short take profits more aggressive)
Stop loss: 20%
Supply & Demand Zones + Order Block (Pro Fusion) SuroLevel up your trading edge with this all-in-one Supply and Demand Zones + Order Block TradingView indicator, built for precision traders who focus on price action and smart money concepts.
🔍 Key Features:
Automatic detection of Supply & Demand Zones based on refined swing highs and lows
Dynamic Order Block recognition with customizable thresholds
Highlights Breakout signals with volume confirmation and trend filters
Built-in EMA 50 trend detection
Take Profit (TP1, TP2, TP3) projection levels
Clean visual labels for Demand, Supply, and OB zones
Uses smart box plotting with long extended zones for better zone visibility
🔥 Ideal for:
Traders who follow Smart Money Concepts (SMC)
Supply & Demand strategy practitioners
Breakout & Retest pattern traders
Scalpers, swing, and intraday traders using Order Flow logic
📈 Works on all markets: Forex, Crypto, Stocks, Indices
📊 Recommended timeframes: M15, H1, H4, Daily
✅ Enhance your trading strategy using this powerful zone-based script — bringing structure, clarity, and automation to your chart.
#SupplyAndDemand #OrderBlock #TradingViewScript #SmartMoney #BreakoutStrategy #TPProjection #ForexIndicator #SMC
EMA 10/55/200 - LONG ONLY MTF (4h with 1D & 1W confirmation)Title: EMA 10/55/200 - Long Only Multi-Timeframe Strategy (4h with 1D & 1W confirmation)
Description:
This strategy is designed for trend-following long entries using a combination of exponential moving averages (EMAs) on the 4-hour chart, confirmed by higher timeframe trends from the daily (1D) and weekly (1W) charts.
🔍 How It Works
🔹 Entry Conditions (4h chart):
EMA 10 crosses above EMA 55 and price is above EMA 55
OR
EMA 55 crosses above EMA 200
OR
EMA 10 crosses above EMA 500
These entries indicate short-term momentum aligning with medium/long-term trend strength.
🔹 Confirmation (multi-timeframe alignment):
Daily (1D): EMA 55 is above EMA 200
Weekly (1W): EMA 55 is above EMA 200
This ensures that we only enter long trades when the higher timeframes support an uptrend, reducing false signals during sideways or bearish markets.
🛑 Exit Conditions
Bearish crossover of EMA 10 below EMA 200 or EMA 500
Stop Loss: 5% below entry price
⚙️ Backtest Settings
Capital allocation per trade: 10% of equity
Commission: 0.1%
Slippage: 2 ticks
These are realistic conditions for crypto, forex, and stocks.
📈 Best Used On
Timeframe: 4h
Instruments: Trending markets like BTC/ETH, FX majors, or growth stocks
Works best in volatile or trending environments
⚠️ Disclaimer
This is a backtest tool and educational resource. Always validate on demo accounts before applying to real capital. Do your own due diligence.
Fuzzy SMA with DCTI Confirmation[FibonacciFlux]FibonacciFlux: Advanced Fuzzy Logic System with Donchian Trend Confirmation
Institutional-grade trend analysis combining adaptive Fuzzy Logic with Donchian Channel Trend Intensity for superior signal quality
Conceptual Framework & Research Foundation
FibonacciFlux represents a significant advancement in quantitative technical analysis, merging two powerful analytical methodologies: normalized fuzzy logic systems and Donchian Channel Trend Intensity (DCTI). This sophisticated indicator addresses a fundamental challenge in market analysis – the inherent imprecision of trend identification in dynamic, multi-dimensional market environments.
While traditional indicators often produce simplistic binary signals, markets exist in states of continuous, graduated transition. FibonacciFlux embraces this complexity through its implementation of fuzzy set theory, enhanced by DCTI's structural trend confirmation capabilities. The result is an indicator that provides nuanced, probabilistic trend assessment with institutional-grade signal quality.
Core Technological Components
1. Advanced Fuzzy Logic System with Percentile Normalization
At the foundation of FibonacciFlux lies a comprehensive fuzzy logic system that transforms conventional technical metrics into degrees of membership in linguistic variables:
// Fuzzy triangular membership function with robust error handling
fuzzy_triangle(val, left, center, right) =>
if na(val)
0.0
float denominator1 = math.max(1e-10, center - left)
float denominator2 = math.max(1e-10, right - center)
math.max(0.0, math.min(left == center ? val <= center ? 1.0 : 0.0 : (val - left) / denominator1,
center == right ? val >= center ? 1.0 : 0.0 : (right - val) / denominator2))
The system employs percentile-based normalization for SMA deviation – a critical innovation that enables self-calibration across different assets and market regimes:
// Percentile-based normalization for adaptive calibration
raw_diff = price_src - sma_val
diff_abs_percentile = ta.percentile_linear_interpolation(math.abs(raw_diff), normLookback, percRank) + 1e-10
normalized_diff_raw = raw_diff / diff_abs_percentile
normalized_diff = useClamping ? math.max(-clampValue, math.min(clampValue, normalized_diff_raw)) : normalized_diff_raw
This normalization approach represents a significant advancement over fixed-threshold systems, allowing the indicator to automatically adapt to varying volatility environments and maintain consistent signal quality across diverse market conditions.
2. Donchian Channel Trend Intensity (DCTI) Integration
FibonacciFlux significantly enhances fuzzy logic analysis through the integration of Donchian Channel Trend Intensity (DCTI) – a sophisticated measure of trend strength based on the relationship between short-term and long-term price extremes:
// DCTI calculation for structural trend confirmation
f_dcti(src, majorPer, minorPer, sigPer) =>
H = ta.highest(high, majorPer) // Major period high
L = ta.lowest(low, majorPer) // Major period low
h = ta.highest(high, minorPer) // Minor period high
l = ta.lowest(low, minorPer) // Minor period low
float pdiv = not na(L) ? l - L : 0 // Positive divergence (low vs major low)
float ndiv = not na(H) ? H - h : 0 // Negative divergence (major high vs high)
float divisor = pdiv + ndiv
dctiValue = divisor == 0 ? 0 : 100 * ((pdiv - ndiv) / divisor) // Normalized to -100 to +100 range
sigValue = ta.ema(dctiValue, sigPer)
DCTI provides a complementary structural perspective on market trends by quantifying the relationship between short-term and long-term price extremes. This creates a multi-dimensional analysis framework that combines adaptive deviation measurement (fuzzy SMA) with channel-based trend intensity confirmation (DCTI).
Multi-Dimensional Fuzzy Input Variables
FibonacciFlux processes four distinct technical dimensions through its fuzzy system:
Normalized SMA Deviation: Measures price displacement relative to historical volatility context
Rate of Change (ROC): Captures price momentum over configurable timeframes
Relative Strength Index (RSI): Evaluates cyclical overbought/oversold conditions
Donchian Channel Trend Intensity (DCTI): Provides structural trend confirmation through channel analysis
Each dimension is processed through comprehensive fuzzy sets that transform crisp numerical values into linguistic variables:
// Normalized SMA Deviation - Self-calibrating to volatility regimes
ndiff_LP := fuzzy_triangle(normalized_diff, norm_scale * 0.3, norm_scale * 0.7, norm_scale * 1.1)
ndiff_SP := fuzzy_triangle(normalized_diff, norm_scale * 0.05, norm_scale * 0.25, norm_scale * 0.5)
ndiff_NZ := fuzzy_triangle(normalized_diff, -norm_scale * 0.1, 0.0, norm_scale * 0.1)
ndiff_SN := fuzzy_triangle(normalized_diff, -norm_scale * 0.5, -norm_scale * 0.25, -norm_scale * 0.05)
ndiff_LN := fuzzy_triangle(normalized_diff, -norm_scale * 1.1, -norm_scale * 0.7, -norm_scale * 0.3)
// DCTI - Structural trend measurement
dcti_SP := fuzzy_triangle(dcti_val, 60.0, 85.0, 101.0) // Strong Positive Trend (> ~85)
dcti_WP := fuzzy_triangle(dcti_val, 20.0, 45.0, 70.0) // Weak Positive Trend (~30-60)
dcti_Z := fuzzy_triangle(dcti_val, -30.0, 0.0, 30.0) // Near Zero / Trendless (~+/- 20)
dcti_WN := fuzzy_triangle(dcti_val, -70.0, -45.0, -20.0) // Weak Negative Trend (~-30 - -60)
dcti_SN := fuzzy_triangle(dcti_val, -101.0, -85.0, -60.0) // Strong Negative Trend (< ~-85)
Advanced Fuzzy Rule System with DCTI Confirmation
The core intelligence of FibonacciFlux lies in its sophisticated fuzzy rule system – a structured knowledge representation that encodes expert understanding of market dynamics:
// Base Trend Rules with DCTI Confirmation
cond1 = math.min(ndiff_LP, roc_HP, rsi_M)
strength_SB := math.max(strength_SB, cond1 * (dcti_SP > 0.5 ? 1.2 : dcti_Z > 0.1 ? 0.5 : 1.0))
// DCTI Override Rules - Structural trend confirmation with momentum alignment
cond14 = math.min(ndiff_NZ, roc_HP, dcti_SP)
strength_SB := math.max(strength_SB, cond14 * 0.5)
The rule system implements 15 distinct fuzzy rules that evaluate various market conditions including:
Established Trends: Strong deviations with confirming momentum and DCTI alignment
Emerging Trends: Early deviation patterns with initial momentum and DCTI confirmation
Weakening Trends: Divergent signals between deviation, momentum, and DCTI
Reversal Conditions: Counter-trend signals with DCTI confirmation
Neutral Consolidations: Minimal deviation with low momentum and neutral DCTI
A key innovation is the weighted influence of DCTI on rule activation. When strong DCTI readings align with other indicators, rule strength is amplified (up to 1.2x). Conversely, when DCTI contradicts other indicators, rule impact is reduced (as low as 0.5x). This creates a dynamic, self-adjusting system that prioritizes high-conviction signals.
Defuzzification & Signal Generation
The final step transforms fuzzy outputs into a precise trend score through center-of-gravity defuzzification:
// Defuzzification with precise floating-point handling
denominator = strength_SB + strength_WB + strength_N + strength_WBe + strength_SBe
if denominator > 1e-10
fuzzyTrendScore := (strength_SB * STRONG_BULL + strength_WB * WEAK_BULL +
strength_N * NEUTRAL + strength_WBe * WEAK_BEAR +
strength_SBe * STRONG_BEAR) / denominator
The resulting FuzzyTrendScore ranges from -1.0 (Strong Bear) to +1.0 (Strong Bull), with critical threshold zones at ±0.3 (Weak trend) and ±0.7 (Strong trend). The histogram visualization employs intuitive color-coding for immediate trend assessment.
Strategic Applications for Institutional Trading
FibonacciFlux provides substantial advantages for sophisticated trading operations:
Multi-Timeframe Signal Confirmation: Institutional-grade signal validation across multiple technical dimensions
Trend Strength Quantification: Precise measurement of trend conviction with noise filtration
Early Trend Identification: Detection of emerging trends before traditional indicators through fuzzy pattern recognition
Adaptive Market Regime Analysis: Self-calibrating analysis across varying volatility environments
Algorithmic Strategy Integration: Well-defined numerical output suitable for systematic trading frameworks
Risk Management Enhancement: Superior signal fidelity for risk exposure optimization
Customization Parameters
FibonacciFlux offers extensive customization to align with specific trading mandates and market conditions:
Fuzzy SMA Settings: Configure baseline trend identification parameters including SMA, ROC, and RSI lengths
Normalization Settings: Fine-tune the self-calibration mechanism with adjustable lookback period, percentile rank, and optional clamping
DCTI Parameters: Optimize trend structure confirmation with adjustable major/minor periods and signal smoothing
Visualization Controls: Customize display transparency for optimal chart integration
These parameters enable precise calibration for different asset classes, timeframes, and market regimes while maintaining the core analytical framework.
Implementation Notes
For optimal implementation, consider the following guidance:
Higher timeframes (4H+) benefit from increased normalization lookback (800+) for stability
Volatile assets may require adjusted clamping values (2.5-4.0) for optimal signal sensitivity
DCTI parameters should be aligned with chart timeframe (higher timeframes require increased major/minor periods)
The indicator performs exceptionally well as a trend filter for systematic trading strategies
Acknowledgments
FibonacciFlux builds upon the pioneering work of Donovan Wall in Donchian Channel Trend Intensity analysis. The normalization approach draws inspiration from percentile-based statistical techniques in quantitative finance. This indicator is shared for educational and analytical purposes under Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license.
Past performance does not guarantee future results. All trading involves risk. This indicator should be used as one component of a comprehensive analysis framework.
Shout out @DonovanWall
Fuzzy SMA Trend Analyzer (experimental)[FibonacciFlux]Fuzzy SMA Trend Analyzer (Normalized): Advanced Market Trend Detection Using Fuzzy Logic Theory
Elevate your technical analysis with institutional-grade fuzzy logic implementation
Research Genesis & Conceptual Framework
This indicator represents the culmination of extensive research into applying fuzzy logic theory to financial markets. While traditional technical indicators often produce binary outcomes, market conditions exist on a continuous spectrum. The Fuzzy SMA Trend Analyzer addresses this limitation by implementing a sophisticated fuzzy logic system that captures the nuanced, multi-dimensional nature of market trends.
Core Fuzzy Logic Principles
At the heart of this indicator lies fuzzy logic theory - a mathematical framework designed to handle imprecision and uncertainty:
// Improved fuzzy_triangle function with guard clauses for NA and invalid parameters.
fuzzy_triangle(val, left, center, right) =>
if na(val) or na(left) or na(center) or na(right) or left > center or center > right // Guard checks
0.0
else if left == center and center == right // Crisp set (single point)
val == center ? 1.0 : 0.0
else if left == center // Left-shoulder shape (ramp down from 1 at center to 0 at right)
val >= right ? 0.0 : val <= center ? 1.0 : (right - val) / (right - center)
else if center == right // Right-shoulder shape (ramp up from 0 at left to 1 at center)
val <= left ? 0.0 : val >= center ? 1.0 : (val - left) / (center - left)
else // Standard triangle
math.max(0.0, math.min((val - left) / (center - left), (right - val) / (right - center)))
This implementation of triangular membership functions enables the indicator to transform crisp numerical values into degrees of membership in linguistic variables like "Large Positive" or "Small Negative," creating a more nuanced representation of market conditions.
Dynamic Percentile Normalization
A critical innovation in this indicator is the implementation of percentile-based normalization for SMA deviation:
// ----- Deviation Scale Estimation using Percentile -----
// Calculate the percentile rank of the *absolute* deviation over the lookback period.
// This gives an estimate of the 'typical maximum' deviation magnitude recently.
diff_abs_percentile = ta.percentile_linear_interpolation(math.abs(raw_diff), normLookback, percRank) + 1e-10
// ----- Normalize the Raw Deviation -----
// Divide the raw deviation by the estimated 'typical max' magnitude.
normalized_diff = raw_diff / diff_abs_percentile
// ----- Clamp the Normalized Deviation -----
normalized_diff_clamped = math.max(-3.0, math.min(3.0, normalized_diff))
This percentile normalization approach creates a self-adapting system that automatically calibrates to different assets and market regimes. Rather than using fixed thresholds, the indicator dynamically adjusts based on recent volatility patterns, significantly enhancing signal quality across diverse market environments.
Multi-Factor Fuzzy Rule System
The indicator implements a comprehensive fuzzy rule system that evaluates multiple technical factors:
SMA Deviation (Normalized): Measures price displacement from the Simple Moving Average
Rate of Change (ROC): Captures price momentum over a specified period
Relative Strength Index (RSI): Assesses overbought/oversold conditions
These factors are processed through a sophisticated fuzzy inference system with linguistic variables:
// ----- 3.1 Fuzzy Sets for Normalized Deviation -----
diffN_LP := fuzzy_triangle(normalized_diff_clamped, 0.7, 1.5, 3.0) // Large Positive (around/above percentile)
diffN_SP := fuzzy_triangle(normalized_diff_clamped, 0.1, 0.5, 0.9) // Small Positive
diffN_NZ := fuzzy_triangle(normalized_diff_clamped, -0.2, 0.0, 0.2) // Near Zero
diffN_SN := fuzzy_triangle(normalized_diff_clamped, -0.9, -0.5, -0.1) // Small Negative
diffN_LN := fuzzy_triangle(normalized_diff_clamped, -3.0, -1.5, -0.7) // Large Negative (around/below percentile)
// ----- 3.2 Fuzzy Sets for ROC -----
roc_HN := fuzzy_triangle(roc_val, -8.0, -5.0, -2.0)
roc_WN := fuzzy_triangle(roc_val, -3.0, -1.0, -0.1)
roc_NZ := fuzzy_triangle(roc_val, -0.3, 0.0, 0.3)
roc_WP := fuzzy_triangle(roc_val, 0.1, 1.0, 3.0)
roc_HP := fuzzy_triangle(roc_val, 2.0, 5.0, 8.0)
// ----- 3.3 Fuzzy Sets for RSI -----
rsi_L := fuzzy_triangle(rsi_val, 0.0, 25.0, 40.0)
rsi_M := fuzzy_triangle(rsi_val, 35.0, 50.0, 65.0)
rsi_H := fuzzy_triangle(rsi_val, 60.0, 75.0, 100.0)
Advanced Fuzzy Inference Rules
The indicator employs a comprehensive set of fuzzy rules that encode expert knowledge about market behavior:
// --- Fuzzy Rules using Normalized Deviation (diffN_*) ---
cond1 = math.min(diffN_LP, roc_HP, math.max(rsi_M, rsi_H)) // Strong Bullish: Large pos dev, strong pos roc, rsi ok
strength_SB := math.max(strength_SB, cond1)
cond2 = math.min(diffN_SP, roc_WP, rsi_M) // Weak Bullish: Small pos dev, weak pos roc, rsi mid
strength_WB := math.max(strength_WB, cond2)
cond3 = math.min(diffN_SP, roc_NZ, rsi_H) // Weakening Bullish: Small pos dev, flat roc, rsi high
strength_N := math.max(strength_N, cond3 * 0.6) // More neutral
strength_WB := math.max(strength_WB, cond3 * 0.2) // Less weak bullish
This rule system evaluates multiple conditions simultaneously, weighting them by their degree of membership to produce a comprehensive trend assessment. The rules are designed to identify various market conditions including strong trends, weakening trends, potential reversals, and neutral consolidations.
Defuzzification Process
The final step transforms the fuzzy result back into a crisp numerical value representing the overall trend strength:
// --- Step 6: Defuzzification ---
denominator = strength_SB + strength_WB + strength_N + strength_WBe + strength_SBe
if denominator > 1e-10 // Use small epsilon instead of != 0.0 for float comparison
fuzzyTrendScore := (strength_SB * STRONG_BULL +
strength_WB * WEAK_BULL +
strength_N * NEUTRAL +
strength_WBe * WEAK_BEAR +
strength_SBe * STRONG_BEAR) / denominator
The resulting FuzzyTrendScore ranges from -1 (strong bearish) to +1 (strong bullish), providing a smooth, continuous evaluation of market conditions that avoids the abrupt signal changes common in traditional indicators.
Advanced Visualization with Rainbow Gradient
The indicator incorporates sophisticated visualization using a rainbow gradient coloring system:
// Normalize score to for gradient function
normalizedScore = na(fuzzyTrendScore) ? 0.5 : math.max(0.0, math.min(1.0, (fuzzyTrendScore + 1) / 2))
// Get the color based on gradient setting and normalized score
final_color = get_gradient(normalizedScore, gradient_type)
This color-coding system provides intuitive visual feedback, with color intensity reflecting trend strength and direction. The gradient can be customized between Red-to-Green or Red-to-Blue configurations based on user preference.
Practical Applications
The Fuzzy SMA Trend Analyzer excels in several key applications:
Trend Identification: Precisely identifies market trend direction and strength with nuanced gradation
Market Regime Detection: Distinguishes between trending markets and consolidation phases
Divergence Analysis: Highlights potential reversals when price action and fuzzy trend score diverge
Filter for Trading Systems: Provides high-quality trend filtering for other trading strategies
Risk Management: Offers early warning of potential trend weakening or reversal
Parameter Customization
The indicator offers extensive customization options:
SMA Length: Adjusts the baseline moving average period
ROC Length: Controls momentum sensitivity
RSI Length: Configures overbought/oversold sensitivity
Normalization Lookback: Determines the adaptive calculation window for percentile normalization
Percentile Rank: Sets the statistical threshold for deviation normalization
Gradient Type: Selects the preferred color scheme for visualization
These parameters enable fine-tuning to specific market conditions, trading styles, and timeframes.
Acknowledgments
The rainbow gradient visualization component draws inspiration from LuxAlgo's "Rainbow Adaptive RSI" (used under CC BY-NC-SA 4.0 license). This implementation of fuzzy logic in technical analysis builds upon Fermi estimation principles to overcome the inherent limitations of crisp binary indicators.
This indicator is shared under Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license.
Remember that past performance does not guarantee future results. Always conduct thorough testing before implementing any technical indicator in live trading.
