PINE LIBRARY

LengthAdaptation

已更新

Collection of dynamic length adaptation algorithms. Mostly from various Adaptive Moving Averages (they are usually just EMA otherwise). Now you can combine Adaptations with any other Moving Averages or Oscillators (see my other libraries), to get something like Deviation Scaled RSI or Fractal Adaptive VWMA. This collection is not encyclopaedic. Suggestions are welcome.

chande(src, len, sdlen, smooth, power) Chande's Dynamic Length
Parameters:
src: Series to use
len: Reference lookback length
sdlen: Lookback length of Standard deviation
smooth: Smoothing length of Standard deviation
power: Exponent of the length adaptation (lower is smaller variation)
Returns: Calculated period
Taken from Chande's Dynamic Momentum Index (CDMI or DYMOI), which is dynamic RSI with this length
Original default power value is 1, but I use 0.5
A variant of this algorithm is also included, where volume is used instead of price

vidya(src, len, dynLow) Variable Index Dynamic Average Indicator (VIDYA)
Parameters:
src: Series to use
len: Reference lookback length
dynLow: Lower bound for the dynamic length
Returns: Calculated period
Standard VIDYA algorithm. The period oscillates from the Lower Bound up (slow)
I took the adaptation part, as it is just an EMA otherwise

vidyaRS(src, len, dynHigh) Relative Strength Dynamic Length - VIDYA RS
Parameters:
src: Series to use
len: Reference lookback length
dynHigh: Upper bound for the dynamic length
Returns: Calculated period
Based on Vitali Apirine's modification (Stocks and Commodities, January 2022) of VIDYA algorithm. The period oscillates from the Upper Bound down (fast)
I took the adaptation part, as it is just an EMA otherwise

kaufman(src, len, dynLow, dynHigh) Kaufman Efficiency Scaling
Parameters:
src: Series to use
len: Reference lookback length
dynLow: Lower bound for the dynamic length
dynHigh: Upper bound for the dynamic length
Returns: Calculated period
Based on Efficiency Ratio calculation orifinally used in Kaufman Adaptive Moving Average developed by Perry J. Kaufman
I took the adaptation part, as it is just an EMA otherwise

ds(src, len) Deviation Scaling
Parameters:
src: Series to use
len: Reference lookback length
Returns: Calculated period
Based on Derivation Scaled Super Smoother (DSSS) by John F. Ehlers
Originally used with Super Smoother
RMS originally has 50 bar lookback. Changed to 4x length for better flexibility. Could be wrong.

maa(src, len, threshold) Median Average Adaptation
Parameters:
src: Series to use
len: Reference lookback length
threshold: Adjustment threshold (lower is smaller length, default: 0.002, min: 0.0001)
Returns: Calculated period
Based on Median Average Adaptive Filter by John F. Ehlers
Discovered and implemented by cheatcountry:

Ehlers Median Average Adaptive Filter [CC]

I took the adaptation part, as it is just an EMA otherwise

fra(len, fc, sc) Fractal Adaptation
Parameters:
len: Reference lookback length
fc: Fast constant (default: 1)
sc: Slow constant (default: 200)
Returns: Calculated period
Based on FRAMA by John F. Ehlers
Modified to allow lower and upper bounds by an unknown author
I took the adaptation part, as it is just an EMA otherwise

mama(src, dynLow, dynHigh) MESA Adaptation - MAMA Alpha
Parameters:
src: Series to use
dynLow: Lower bound for the dynamic length
dynHigh: Upper bound for the dynamic length
Returns: Calculated period
Based on MESA Adaptive Moving Average by John F. Ehlers
Introduced in the September 2001 issue of Stocks and Commodities
Inspired by the everget implementation:

Ehlers MESA Adaptive Moving Averages (MAMA & FAMA)

I took the adaptation part, as it is just an EMA otherwise

doAdapt(type, src, len, dynLow, dynHigh, chandeSDLen, chandeSmooth, chandePower) Execute a particular Length Adaptation from the list
Parameters:
type: Length Adaptation type to use
src: Series to use
len: Reference lookback length
dynLow: Lower bound for the dynamic length
dynHigh: Upper bound for the dynamic length
chandeSDLen: Lookback length of Standard deviation for Chande's Dynamic Length
chandeSmooth: Smoothing length of Standard deviation for Chande's Dynamic Length
chandePower: Exponent of the length adaptation for Chande's Dynamic Length (lower is smaller variation)
Returns: Calculated period (float, not limited)

doMA(type, src, len) MA wrapper on wrapper: if DSSS is selected, calculate it here
Parameters:
type: MA type to use
src: Series to use
len: Filtering length
Returns: Filtered series
Demonstration of a combined indicator: Deviation Scaled Super Smoother

發行說明

v2 Correction for vidyaRS algorithm: Vitali Apirine used EMA for his calculations, but I used RMA by mistake

發行說明

v3 Updated vidyaRS to allow multiplier input in form of lower bound

發行說明

v4 New combined MA: Relative Strength Super Smoother based on Vitali Apirine's RS EMA, but with Super Smoother