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https://github.com/mihakralj/QuanTAlib.git
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Miha Kralj
86fe32a682
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com> Co-authored-by: aider (openrouter/anthropic/claude-sonnet-4) <aider@aider.chat> Co-authored-by: Warp <agent@warp.dev>
44 lines
2.3 KiB
Plaintext
44 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("Exponential Weighted MA Volatility", "EWMA Volty", overlay=false)
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//@function Calculates Exponential Weighted Moving Average (EWMA) Volatility.
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//@param src The source series for price data. Default is close.
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//@param length The period length for the EWMA calculation.
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//@param annualize Boolean to indicate if the volatility should be annualized. Default is true.
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//@param annualPeriods Number of periods in a year for annualization. Default is 252 for daily data.
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//@returns float The EWMA Volatility value.
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//@optimized for performance and dirty data
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ewmaVolty(series float src, simple int length, simple bool annualize = true, simple int annualPeriods = 252) =>
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if length <= 0
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runtime.error("Length must be greater than 0")
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if annualize and annualPeriods <= 0
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runtime.error("Annual periods must be greater than 0 if annualizing")
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float logReturn = nz(math.log(src / src[1]),0.0)
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float squaredReturn = logReturn * logReturn
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var float raw_rma_sq_ret = 0.0, var float e_rma = 1.0
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float rma_alpha = 1.0 / float(length)
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if not na(squaredReturn)
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raw_rma_sq_ret := na(raw_rma_sq_ret[1]) ? squaredReturn : (nz(raw_rma_sq_ret[1],squaredReturn) * (length - 1) + squaredReturn) / length
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e_rma := na(e_rma[1]) ? (1.0 - rma_alpha) : (1.0 - rma_alpha) * nz(e_rma[1],1.0)
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float EPSILON = 1e-10
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float corrected_rma_sq_ret = e_rma > EPSILON and not na(raw_rma_sq_ret) ? raw_rma_sq_ret / (1.0 - e_rma) : raw_rma_sq_ret
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float currentEwmaSqReturns = nz(corrected_rma_sq_ret, squaredReturn)
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float volatility = currentEwmaSqReturns < 0 ? na : math.sqrt(currentEwmaSqReturns)
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annualize and not na(volatility) ? volatility * math.sqrt(float(annualPeriods)) : volatility
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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_length = input.int(20, "Length", minval=1, tooltip="Period for EWMA calculation")
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i_annualize = input.bool(true, "Annualize Volatility", tooltip="Annualize the volatility output")
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i_annualPeriods = input.int(252, "Annual Periods", minval=1, tooltip="Number of periods in a year for annualization (e.g., 252 for daily, 52 for weekly)")
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// Calculation
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ewmaVolatilityValue = ewmaVolty(i_source, i_length, i_annualize, i_annualPeriods)
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// Plot
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plot(ewmaVolatilityValue, "EWMA Volty", color=color.yellow, linewidth=2)
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