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QuanTAlib/lib/trends_IIR/vidya/vidya.pine
T
86fe32a682 SIMD Refactor: Merge simd-dev into dev (#55)
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>
2026-01-18 19:02:03 -08:00

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// The MIT License (MIT)
// © mihakralj
//@version=6
indicator("Variable Index Dynamic Average (VIDYA)", "VIDYA", overlay=true)
//@function Calculates VIDYA using adaptive smoothing based on market volatility
//@param source Series to calculate VIDYA from
//@param period Length of the smoothing period
//@param std_period Length of the standard deviation period, defaults to same as period
//@returns VIDYA value that adapts to market volatility
//@optimized Uses volatility index calculation with O(n) complexity per bar due to lookback loops
vidya(series float source, simple int period, simple int std_period=0) =>
if period <= 0
runtime.error("Period must be greater than 0")
float alpha = 2.0 / (period + 1.0)
var float vidya = na
if not na(source)
int p = std_period > 0 ? std_period : period
float sum_p = 0.0
float sumSq_p = 0.0
float count_p = 0.0
float sum_5 = 0.0
float sumSq_5 = 0.0
float count_5 = 0.0
for i = 0 to math.max(p, 5) - 1
if not na(source[i])
float val = source[i]
if i < p
sum_p += val
sumSq_p += val * val
count_p += 1
if i < 5
sum_5 += val
sumSq_5 += val * val
count_5 += 1
float std = count_p > 0 ? math.sqrt(math.max((sumSq_p / count_p) - (sum_p / count_p) * (sum_p / count_p), 0.0)) : 0.0
float std_5 = count_5 > 0 ? math.sqrt(math.max((sumSq_5 / count_5) - (sum_5 / count_5) * (sum_5 / count_5), 0.0)) : 0.0
float vol_idx = std > 0 ? std_5 / std : 1.0
vol_idx := math.min(math.max(vol_idx, 0.0), 1.0)
float sc = alpha * vol_idx
vidya := na(vidya) ? source : source * sc + vidya * (1.0 - sc)
vidya
// ---------- Main loop ----------
// Inputs
i_period = input.int(10, "Period", minval=1)
i_std_period = input.int(0, "Std Dev Period (0=use Period)", minval=0)
i_source = input.source(close, "Source")
// Calculation
vidya_value = vidya(i_source, i_period, i_std_period)
// Plot
plot(vidya_value, "VIDYA", color=color.yellow, linewidth=2)