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https://github.com/mihakralj/QuanTAlib.git
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Miha Kralj
24e86d762a
- Updated BBWN, BBWP, CCV, CV, CVI, EWMA, GKV, HLV, HV, Jvolty, JVOLTYN, MASSI, NATR, RSV, RV, RVI, TR, UI, VOV, VR, YZV indicators with documentation links. - Added documentation links for Aberration, Acceleration Bands, Andrews' Pitchfork, Adaptive Price Zone, ATR Bands, Bollinger Bands, Center of Gravity, Donchian Channels, Decay Min-Max Channel, Detrended Synthetic Price, EACP, EBSW, HOMOD, Jurik Volatility Bands, Keltner Channel, MA Envelope, Min-Max Channel, Price Channel, Regression Channels, Standard Deviation Channel, Stoller Average Range Channel, Super Trend Bands, Ultimate Bands, Ultimate Channel, VWAP Bands, and VWAP with Standard Deviation Bands.
59 lines
2.3 KiB
Plaintext
59 lines
2.3 KiB
Plaintext
// The MIT License (MIT)
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// © mihakralj
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//@version=6
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indicator("Deviation-Scaled Moving Average (DSMA)", "DSMA", overlay=true)
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//@function Calculates DSMA using standard deviation to scale the averaging factor
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//@param source Series to calculate DSMA from
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//@param period Length of the lookback period for both average and deviation calculation
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//@param scaleFactor Combined scaling/smoothing factor (0.01-0.9)
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//@returns DSMA value that adapts to market volatility through deviation scaling
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//@optimized Uses circular buffer for RMS calculation and adaptive alpha for O(1) complexity
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dsma(series float source, simple int period, simple float scaleFactor=0.5) =>
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float a1 = math.exp(-1.414 * math.pi / (period * 0.5))
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float b1 = 2.0 * a1 * math.cos(1.414 * math.pi / (period * 0.5))
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float c1 = 1.0 - b1 + (a1 * a1)
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float c1Half = c1 * 0.5
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float periodRecip = 1.0 / period
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float scaleAdjustment = scaleFactor * 5.0 * periodRecip
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var float result = na
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var float filt = 0.0
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var float filt1 = 0.0
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var float filt2 = 0.0
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var float zeros1 = 0.0
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var float sumSquared = 0.0
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var array<float> filtSquared = array.new_float(period, 0.0)
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var int bufferIndex = 0
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if na(source)
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result
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else
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if na(result)
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result := source
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else
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float zeros = source - result
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filt := c1Half * (zeros + zeros1) + b1 * filt1 - (a1 * a1) * filt2
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float filtSq = filt * filt
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sumSquared := sumSquared + filtSq - array.get(filtSquared, bufferIndex)
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array.set(filtSquared, bufferIndex, filtSq)
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bufferIndex := (bufferIndex + 1) % period
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float rms = math.sqrt(math.max(sumSquared * periodRecip, 1e-10))
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float alpha = math.min(scaleAdjustment * math.abs(filt / rms), 1.0)
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result := alpha * source + (1 - alpha) * result
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zeros1 := zeros
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filt2 := filt1
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filt1 := filt
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result
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// ---------- Main loop ----------
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// Inputs
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i_source = input.source(close, "Source")
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i_period = input.int(25, "Period", minval=2)
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i_scale = input.float(0.9, "Scale Factor", minval=0.01, maxval=0.9, step=0.01)
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// Calculation
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dsma_value = dsma(i_source, i_period, i_scale)
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// Plot
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plot(dsma_value, "DSMA", color=color.yellow, linewidth=2)
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