https://github.com/zelosleone/gas-price-levels
Advanced GAS Price Level Indicator combines machine learning-inspired alpha factors with traditional technical analysis, providing adaptive, correlation-weighted signals for high-probability trading opportunities.
https://github.com/zelosleone/gas-price-levels
algoritmic-trading alpha-factors atr bollinger-bands cci commodities commodity-trading financial-indicators kama macd machine-learning market-analysis pinescript quantitative-finance quantitative-trading rsi technical-analysis trading-indicators volatility-analysis
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Advanced GAS Price Level Indicator combines machine learning-inspired alpha factors with traditional technical analysis, providing adaptive, correlation-weighted signals for high-probability trading opportunities.
- Host: GitHub
- URL: https://github.com/zelosleone/gas-price-levels
- Owner: zelosleone
- License: mit
- Created: 2024-11-11T07:21:51.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-11-26T09:32:18.000Z (11 months ago)
- Last Synced: 2025-01-17T07:25:15.684Z (9 months ago)
- Topics: algoritmic-trading, alpha-factors, atr, bollinger-bands, cci, commodities, commodity-trading, financial-indicators, kama, macd, machine-learning, market-analysis, pinescript, quantitative-finance, quantitative-trading, rsi, technical-analysis, trading-indicators, volatility-analysis
- Homepage:
- Size: 13.7 KB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# GAS Price Levels Technical Indicator
## Overview
The GAS Price Levels Technical Indicator is a **sophisticated multi-factor technical analysis tool** designed for **natural gas trading**. It combines traditional technical indicators with advanced alpha factors, utilizing a **dynamic weighting system** based on **Information Coefficients (IC)** to adapt to **volatile market conditions**. This indicator provides comprehensive **price level analysis**, enabling traders to identify **support and resistance zones** with high precision.
## Features
- **Advanced Technical Indicators**: Integrates Bollinger Bands, KAMA, RSI, CCI, ATR, Williams %R, and MACD for robust price analysis.
- **Dynamic Weighting System**: Automatically adjusts indicator weights based on recent **predictive power** using Information Coefficients.
- **Mathematical Foundations**: Employs **cumulative log returns**, **rate of change (ROC)**, and **correlation calculations** to enhance analysis accuracy.
- **Performance Optimized**: Utilizes efficient `ta.*` functions to ensure minimal computational overhead and prevent repainting.
- **Risk Management Tools**: Incorporates multiple timeframe analysis and volatility-based risk adjustments for effective position sizing.
## Technical Components
### Core Technical Indicators
1. **Bollinger Bands (BB)**
- Length: 20 periods (customizable)
- Standard Deviation: 2.0 (customizable)
- Implementation: `ta.bb(close, bbandsLength, bbandsStdDev)`
- Provides dynamic support/resistance levels based on **volatility**
2. **Kaufman's Adaptive Moving Average (KAMA)**
- Length: 10 periods
- Implementation: `ta.ema(close, 10)`
- Adapts to market volatility for more responsive **trend following**
3. **Additional Supporting Indicators**
- RSI (Relative Strength Index): 14-period default
- CCI (Commodity Channel Index): 20-period default
- ATR (Average True Range): 10-period default
- Williams %R: 14-period default
- MACD: (12, 26, 9) standard parameters
### Advanced Alpha Factors
#### Alpha238 (40-day Minimum LogReturn)
```pine
cumLogReturn40d = ta.cum(math.log(close / close[1]))
alpha238 = ta.lowestbars(cumLogReturn40d, 40)
```
Mathematical foundation:
- Calculates **cumulative log returns** over 40 days
- Identifies historical price patterns through **minimum return periods**
- Effective for **mean reversion strategies**
#### Alpha51 (Price ROC Interaction)
```pine
alpha51 = ta.roc(close, 30) * ta.roc(close, 5)
```
Properties:
- Combines **long-term (30-period)** and **short-term (5-period)** price momentum
- Identifies **momentum divergences** and **convergences**
- Multiplication effect amplifies significant **price moves**
#### Alpha262 (CCI Complex)
```pine
alpha262 = ta.change(ta.sma(math.pow(cci, 2), cciLength))
```
Characteristics:
- Squares CCI values to emphasize **extreme movements**
- Applies **smoothing** through SMA
- Tracks **rate of change** in volatility
### Dynamic Weighting System
The indicator implements a sophisticated **dynamic weighting system** based on **Information Coefficients (IC)**:
```pine
float ic_238 = ta.correlation(alpha238, ta.change(close), 20)
float ic_51 = ta.correlation(alpha51, ta.change(close), 20)
float ic_262 = ta.correlation(alpha262, ta.change(close), 20)
float total_ic = math.abs(ic_238) + math.abs(ic_51) + math.abs(ic_262)
float w238 = math.abs(ic_238) / total_ic
```
#### Weight Calculation Method
1. Calculates **20-period correlation** between each alpha and **price changes**
2. Takes **absolute values** to focus on **strength** rather than direction
3. **Normalizes weights** by dividing by **total IC**
4. Automatically adjusts **factor importance** based on recent **predictive power**
## Usage Parameters
| Parameter | Default | Description |
|---------------|---------|--------------------------------------|
| emaPeriods | 9 | EMA calculation length |
| atrLength | 10 | ATR calculation period |
| bbandsLength | 20 | Bollinger Bands period |
| bbandsStdDev | 2.0 | BB standard deviation multiplier |
| rsiLength | 14 | RSI calculation period |
| cciLength | 20 | CCI calculation period |
## Visual Components
The indicator displays several **overlay elements** on the price chart:
- **Bollinger Bands** (Upper, Middle, Lower) in blue/white with 80% transparency
- **KAMA line** in orange with 80% transparency
## Implementation Notes
1. **Performance Considerations**
- Uses efficient `ta.*` built-in functions for optimal performance
- Implements look-back periods carefully to minimize **repainting**
- Calculations are streamlined to reduce **computational overhead**
2. **Risk Management**
- Multiple timeframe analysis recommended (**indicator works on any timeframe**)
- Use in conjunction with **position sizing** based on ATR values
- Consider BB width for **volatility-based risk adjustment**
## Requirements
- TradingView Pine Script version 6
- Real-time or delayed data feed for natural gas prices
## Installation
1. Open TradingView Chart
2. Go to Pine Editor
3. Create New Indicator
4. Copy and paste the provided code
5. Add to Chart
## License
MIT License
## Author
Denizhan Dakılır