OPEN-SOURCE SCRIPT
Hybrid Moving Average - Market Trend
Hybrid Moving Average Market Trend System - , designed to visualize market trends using a combination of three moving averages: FRAMA (Fractal Adaptive Moving Average), VIDYA (Variable Index Dynamic Average), and a Hamming windowed Volume-Weighted Moving Average (VWMA).
Key Features:
FRAMA Calculation:
FRAMA adapts to market volatility by dynamically adjusting its smoothing factor based on the fractal dimension of price movement. This allows it to be more responsive during trending periods while filtering out noise in sideways markets. The FRAMA is calculated for both short and long periods
VIDYA with CMO:
The VIDYA (Variable Index Dynamic Average) is based on a Chande Momentum Oscillator (CMO), which adjusts the smoothing factor dynamically depending on the momentum of the market. Higher momentum periods result in more responsive averages, while low momentum periods lead to smoother averages. Like FRAMA, VIDYA is calculated for both short and long periods.
Hamming Windowed VWMA:
This VWMA variation applies a Hamming window to smooth the weighting of volume across the calculation period. This method emphasizes central data points and reduces noise, making the VWMA more adaptive to volume fluctuations. The Hamming VWMA is calculated for short and long periods, offering another layer of adaptability to the hybrid moving average.
Hybrid Moving Averages:
Dynamic Coloring and Filling:
The script uses dynamic color transitions to visually distinguish between bullish and bearish conditions:
Key Features:
FRAMA Calculation:
FRAMA adapts to market volatility by dynamically adjusting its smoothing factor based on the fractal dimension of price movement. This allows it to be more responsive during trending periods while filtering out noise in sideways markets. The FRAMA is calculated for both short and long periods
VIDYA with CMO:
The VIDYA (Variable Index Dynamic Average) is based on a Chande Momentum Oscillator (CMO), which adjusts the smoothing factor dynamically depending on the momentum of the market. Higher momentum periods result in more responsive averages, while low momentum periods lead to smoother averages. Like FRAMA, VIDYA is calculated for both short and long periods.
Hamming Windowed VWMA:
This VWMA variation applies a Hamming window to smooth the weighting of volume across the calculation period. This method emphasizes central data points and reduces noise, making the VWMA more adaptive to volume fluctuations. The Hamming VWMA is calculated for short and long periods, offering another layer of adaptability to the hybrid moving average.
Hybrid Moving Averages:
Dynamic Coloring and Filling:
The script uses dynamic color transitions to visually distinguish between bullish and bearish conditions:
Script de código aberto
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