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https://github.com/mihakralj/QuanTAlib.git
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Miha Kralj
6f0a339c9b
- Sar.Quantower.Tests.cs: add missing opening quote on string literal (line 48) - Exports.cs: rename Correlation.Batch → Correl.Batch (CS0103) - Ad.Validation.Tests.cs: fix Ooples OutputValues key "Ad" → "Adl"
127 lines
4.9 KiB
Plaintext
127 lines
4.9 KiB
Plaintext
// Licensed under the Apache License, Version 2.0
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// © mihakralj
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//@version=6
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indicator("Dynamic Momentum Index (DYMI)", "DYMI", overlay=false)
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//@description Dynamic Momentum Index by Tushar Chande and Stanley Kroll (1994).
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// A three-stage pipeline that produces a volatility-adaptive RSI:
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// Stage 1: Dual circular-buffer StdDev → volatility ratio V = σ_short / σ_long
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// Stage 2: dynamic_period = clamp(round(basePeriod / V), minPeriod, maxPeriod)
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// Stage 3: Wilder RMA RSI with adaptive alpha = 1 / dynamic_period
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// When price volatility is high V > 1, the period shortens → faster response.
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// When volatility is low V < 1, the period lengthens → smoother output.
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//@function Calculates StdDev over a circular buffer of given period
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//@param source Price series
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//@param period Window size
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//@returns Population standard deviation of the window
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stddev_circ(series float source, simple int period) =>
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var array<float> buf = array.new_float(period, na)
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var int head = 0
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var int count = 0
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var float sumV = 0.0
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var float sumSq = 0.0
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float oldest = array.get(buf, head)
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if not na(oldest)
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sumV -= oldest
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sumSq -= oldest * oldest
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float val = na(source) ? 0.0 : source
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array.set(buf, head, val)
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sumV += val
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sumSq += val * val
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head := (head + 1) % period
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if count < period
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count += 1
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float mean = sumV / count
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float variance = sumSq / count - mean * mean
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float sd = variance > 0.0 ? math.sqrt(variance) : 0.0
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sd
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//@function Calculates Wilder's RMA RSI with warmup compensation and adaptive alpha
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//@param source Close price series
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//@param dynPeriod Dynamic period (integer, already clamped)
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//@returns RSI value in [0, 100]
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rsi_wilder(series float source, series int dynPeriod) =>
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var float prevVal = na
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var float avgGain = 0.0
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var float avgLoss = 0.0
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var float e = 1.0
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var bool warmup = true
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float result = 50.0
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if not na(source)
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if na(prevVal)
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prevVal := source
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else
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float alpha = 1.0 / dynPeriod
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float beta = 1.0 - alpha
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float change = source - prevVal
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float gain = change > 0.0 ? change : 0.0
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float loss = change < 0.0 ? -change : 0.0
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prevVal := source
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avgGain := alpha * gain + beta * avgGain
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avgLoss := alpha * loss + beta * avgLoss
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if warmup
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e *= beta
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float c = e > 1e-10 ? 1.0 / (1.0 - e) : 1.0
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float aG = avgGain * c
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float aL = avgLoss * c
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float total = aG + aL
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result := total != 0.0 ? 100.0 * aG / total : 50.0
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if e <= 1e-10
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warmup := false
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else
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float total = avgGain + avgLoss
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result := total != 0.0 ? 100.0 * avgGain / total : 50.0
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result
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//@function Calculates Dynamic Momentum Index
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//@param source Close price series
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//@param basePeriod Base RSI period (default 14)
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//@param shortPeriod Short StdDev window (default 5)
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//@param longPeriod Long StdDev window (default 10)
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//@param minPeriod Minimum dynamic period (default 3)
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//@param maxPeriod Maximum dynamic period (default 30)
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//@returns DYMI value in [0, 100]
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//@optimized Uses circular buffers for O(1) StdDev; adaptive Wilder RMA for RSI
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dymi(series float source, simple int basePeriod, simple int shortPeriod, simple int longPeriod, simple int minPeriod, simple int maxPeriod) =>
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if basePeriod < 2 or shortPeriod < 2 or longPeriod <= shortPeriod or minPeriod < 2 or maxPeriod < minPeriod
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runtime.error("Invalid DYMI parameters")
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// Stage 1: dual StdDev volatility ratio
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float sdShort = stddev_circ(source, shortPeriod)
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float sdLong = stddev_circ(source, longPeriod)
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float v = sdLong > 1e-10 ? sdShort / sdLong : 1.0
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// Stage 2: dynamic period
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int rawPeriod = v > 1e-10 ? math.round(basePeriod / v) : maxPeriod
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int dynPeriod = math.max(minPeriod, math.min(maxPeriod, rawPeriod))
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// Stage 3: adaptive Wilder RSI
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float result = rsi_wilder(source, dynPeriod)
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math.max(0.0, math.min(100.0, result))
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// ---------- Main loop ----------
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i_basePeriod = input.int(14, "Base RSI Period", minval=2, maxval=500)
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i_shortPeriod = input.int(5, "Short StdDev Period", minval=2, maxval=500)
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i_longPeriod = input.int(10, "Long StdDev Period", minval=2, maxval=500)
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i_minPeriod = input.int(3, "Min Period", minval=2, maxval=500)
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i_maxPeriod = input.int(30, "Max Period", minval=2, maxval=500)
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i_source = input.source(close, "Source")
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dymi_val = dymi(i_source, i_basePeriod, i_shortPeriod, i_longPeriod, i_minPeriod, i_maxPeriod)
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plot(dymi_val, "DYMI", color=color.yellow, linewidth=2)
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hline(70, "Overbought", color=color.gray, linestyle=hline.style_dotted)
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hline(50, "Midline", color=color.gray, linestyle=hline.style_dotted)
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hline(30, "Oversold", color=color.gray, linestyle=hline.style_dotted)
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