[SM-021] Gaussian Trend System [Optimized]This script is a comprehensive trend-following strategy centered around a Gaussian Channel. It is designed to capture significant market movements while filtering out noise during consolidation phases. This version (v2) introduces code optimizations using Pine Script v6 Arrays and a new Intraday Time Control feature.
1. Core Methodology & Math
The foundation of this strategy is the Gaussian Filter, originally conceptualized by @DonovanWall.
Gaussian Poles: Unlike standard moving averages (SMA/EMA), this filter uses "poles" (referencing signal processing logic) to reduce lag while maintaining smoothness.
Array Optimization: In this specific iteration, the f_pole function has been refactored to utilize Pine Script Arrays. This improves calculation efficiency and rendering speed compared to recursive variable calls, especially when calculating deep historical data.
Channel Logic: The strategy calculates a "Filtered True Range" to create High and Low bands around the main Gaussian line.
Long Entry: Price closes above the High Band.
Short Entry: Price closes below the Low Band.
2. Signal Filtering (Confluence)
To reduce false signals common in trend-following systems, the strategy employs a "confluence" approach using three additional layers:
Baseline Filter: A 200-period (customizable) EMA or SMA acts as a regime filter. Longs are only taken above the baseline; Shorts only below.
ADX Filter (Volatility): The Average Directional Index (ADX) is used to measure trend strength. If the ADX is below a user-defined threshold (default: 20), the market is considered "choppy," and new entries are blocked.
Momentum Check: A Stochastic RSI check ensures that momentum aligns with the breakout direction.
3. NEW: Intraday Session Filter
Per user requests, a time-based filter has been added to restrict trading activity to specific market sessions (e.g., the New York Open).
How it works: Users can toggle a checkbox to enable/disable the filter.
Configuration: You can define a specific time range (Default: 09:30 - 16:00) and a specific Timezone (Default: New York).
Logic: The strategy longCondition and shortCondition now check if the current bar's timestamp falls within this window. If outside the window, no new entries are generated, though existing trades are managed normally.
4. Risk Management
The strategy relies on volatility-based exits rather than fixed percentage stops:
ATR Stop Loss: A multiple of the Average True Range (ATR) is calculated at the moment of entry to set a dynamic Stop Loss.
ATR Take Profit: An optional Reward-to-Risk (RR) ratio can be set to place a Take Profit target relative to the Stop Loss distance.
Band Exit: If the trend reverses and price crosses the opposite band, the trade is closed immediately to prevent large drawdowns.
Credits & Attribution
Original Gaussian Logic: Developed by @DonovanWalll. This script utilizes his mathematical formula for the pole filters.
Strategy Wrapper & Array Refactor: Developed by @sebamarghella.
Community Request: The Intraday Session Filter was added to assist traders focusing on specific liquidity windows.
Disclaimer: This strategy is for educational purposes. Past performance is not indicative of future results. Please use the settings menu to adjust the Session Time and Risk parameters to fit your specific asset class.
Gaussianchannel
Truly Iterative Gaussian ChannelOVERVIEW
The Truly Iterative Gaussian Channel is a robust channeling system that integrates a Gaussian smoothing kernel with a rolling standard deviation to create dynamically adaptive upper and lower boundaries around price. This indicator provides a smooth, yet responsive representation of price movements while minimizing lag and dynamically adjusting channel width to reflect real-time market volatility. Its versatility makes it effective across various timeframes and trading styles, offering significant potential for experimentation and integration into advanced trading systems.
TRADING USES
The Gaussian indicator can be used for multiple trading strategies. Trend following relies on the middle Gaussian line to gauge trend direction: prices above this line indicate bullish momentum, while prices below signal bearish momentum. The upper and lower boundaries act as dynamic support and resistance levels, offering breakout or pullback entry opportunities. Mean reversion focuses on identifying reversal setups when price approaches or breaches the outer boundaries, aiming for a return to the Gaussian centerline. Volatility filtering helps assess market conditions, with narrow channels indicating low volatility or consolidation and suggesting fewer trading opportunities or an impending breakout. Adaptive risk management uses channel width to adjust for market volatility, with wider channels signaling higher risk and tighter channels indicating lower volatility and potentially safer entry points.
THEORY
Gaussian kernel smoothing, derived from the Gaussian normal distribution, is a cornerstone of probability and statistics, valued for its ability to reduce noise while preserving critical signal features. In this indicator, it ensures price movements are smoothed with precision, minimizing distortion while maintaining responsiveness to market dynamics.
The rolling standard deviation complements this by dynamically measuring price dispersion from the mean, enabling the channel to adapt in real time to changing market conditions. This combination leverages the mathematical correctness of both tools to balance smoothness and adaptability.
An iterative framework processes data efficiently, bar by bar, without recalculating historical value to ensure reliability and preventing repainting to create a mathematically grounded channel system suitable for a wide range of market environments.
The Gaussian channel excels at filtering noise while remaining responsive to price action, providing traders with a dependable tool for identifying trends, reversals, and volatility shifts with consistency and precision.
CALIBRATION
Calibration of the Gaussian channel involves adjusting its length to modify sensitivity and adaptability based on trading style. Shorter lengths (e.g., 50-100) are ideal for intraday traders seeking quick responses to price fluctuations. Medium lengths (e.g., 150-200) cater to swing traders aiming to capture broader market trends. Longer lengths (e.g., 250-400+) are better suited for positional traders focusing on long-term price movements and stability.
MARKET USAGE
Stock, Forex, Crypto, Commodities, and Indices.
