GAS Price Levels Technical Indicator

Overview

The GAS Price Levels indicator is a sophisticated multi-factor technical analysis tool that combines traditional technical indicators with advanced alpha factors to provide comprehensive price level analysis for natural gas trading. This indicator implements a dynamic weighting system based on Information Coefficients (IC) to adapt to changing market conditions.

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)

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)

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)

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):

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 5
• 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