mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-07-28 01:37:43 +00:00
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"
69 lines
2.5 KiB
Plaintext
69 lines
2.5 KiB
Plaintext
// Licensed under the Apache License, Version 2.0
|
|
// © mihakralj
|
|
//@version=6
|
|
indicator("Pearson's Correlation (CORREL)", "CORREL", overlay=false)
|
|
|
|
//@function Calculates Pearson correlation coefficient using single pass with circular buffer
|
|
//@param src1 series float First series to analyze
|
|
//@param src2 series float Second series to analyze
|
|
//@param len simple int Lookback period for calculation
|
|
//@returns float Pearson correlation coefficient between -1 and 1
|
|
//@optimized for performance using combined covariance and variance calculation
|
|
correlation(series float src1, series float src2, simple int len) =>
|
|
if len <= 0
|
|
runtime.error("Period must be greater than 0")
|
|
var int p = math.max(1, len)
|
|
var array<float> buffer1 = array.new_float(p, na)
|
|
var array<float> buffer2 = array.new_float(p, na)
|
|
var int head = 0, var int count = 0
|
|
var float sum1 = 0.0, var float sum2 = 0.0
|
|
var float sumSq1 = 0.0, var float sumSq2 = 0.0
|
|
var float sumProd = 0.0
|
|
float oldest1 = array.get(buffer1, head)
|
|
float oldest2 = array.get(buffer2, head)
|
|
if not na(oldest1) and not na(oldest2)
|
|
sum1 -= oldest1, sum2 -= oldest2
|
|
sumSq1 -= oldest1 * oldest1, sumSq2 -= oldest2 * oldest2
|
|
sumProd -= oldest1 * oldest2
|
|
count -= 1
|
|
if not na(src1) and not na(src2)
|
|
sum1 += src1, sum2 += src2
|
|
sumSq1 += src1 * src1, sumSq2 += src2 * src2
|
|
sumProd += src1 * src2
|
|
count += 1
|
|
array.set(buffer1, head, src1)
|
|
array.set(buffer2, head, src2)
|
|
else
|
|
array.set(buffer1, head, na)
|
|
array.set(buffer2, head, na)
|
|
head := (head + 1) % p
|
|
if count > 1
|
|
mean1 = sum1 / count, mean2 = sum2 / count
|
|
cov = (sumProd / count) - mean1 * mean2
|
|
var1 = (sumSq1 / count) - mean1 * mean1
|
|
var2 = (sumSq2 / count) - mean2 * mean2
|
|
stddev1 = math.sqrt(math.max(0.0, var1))
|
|
stddev2 = math.sqrt(math.max(0.0, var2))
|
|
denominator = stddev1 * stddev2
|
|
if denominator != 0
|
|
cov / denominator
|
|
else
|
|
na
|
|
else
|
|
na
|
|
|
|
// ---------- Main loop ----------
|
|
|
|
// Inputs
|
|
i_source1 = input.source(close, "Source 1")
|
|
i_source2_ticker = input.symbol("SPY", "Source 2 Ticker (e.g., SPY, AAPL)")
|
|
i_period = input.int(20, "Period", minval=2)
|
|
|
|
i_source2 = request.security(i_source2_ticker, timeframe.period, close, lookahead=barmerge.lookahead_off)
|
|
|
|
// Calculation
|
|
correlation_value = correlation(i_source1, i_source2, i_period)
|
|
|
|
// Plot
|
|
plot(correlation_value, "Correlation", color=color.yellow, linewidth=2)
|