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https://github.com/mihakralj/QuanTAlib.git
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Miha Kralj
56 lines
1.9 KiB
Plaintext
56 lines
1.9 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("Covariance (COVARIANCE)", "COVARIANCE", overlay=false)
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//@function Calculates covariance using single pass with circular buffer
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//@param src1 series float First series to analyze
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//@param src2 series float Second series to analyze
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//@param len simple int Lookback period for calculation
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//@returns float Covariance between src1 and src2
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//@optimized for performance using circular buffer
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covariance(series float src1, series float src2, simple int len) =>
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if len <= 0
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runtime.error("Period must be greater than 0")
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var int p = math.max(1, len)
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var array<float> buffer1 = array.new_float(p, na)
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var array<float> buffer2 = array.new_float(p, na)
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var int head = 0, var int count = 0
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var float sum1 = 0.0, var float sum2 = 0.0
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var float sumProd = 0.0
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float oldest1 = array.get(buffer1, head)
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float oldest2 = array.get(buffer2, head)
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if not na(oldest1) and not na(oldest2)
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sum1 -= oldest1
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sum2 -= oldest2
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sumProd -= oldest1 * oldest2
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count -= 1
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if not na(src1) and not na(src2)
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sum1 += src1
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sum2 += src2
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sumProd += src1 * src2
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count += 1
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array.set(buffer1, head, src1)
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array.set(buffer2, head, src2)
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else
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array.set(buffer1, head, na)
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array.set(buffer2, head, na)
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head := (head + 1) % p
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count > 1 ? (sumProd / count) - (sum1 / count) * (sum2 / count) : na
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// ---------- Main loop ----------
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// Inputs
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i_source1 = input.source(close, "Source 1")
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i_source2_ticker = input.symbol("SPY", "Source 2 Ticker (e.g., SPY, AAPL)")
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i_period = input.int(20, "Period", minval=2)
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i_source2 = request.security(i_source2_ticker, timeframe.period, close, lookahead=barmerge.lookahead_off)
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// Calculation
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variance_value = covariance(i_source1, i_source2, i_period)
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// Plot
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plot(variance_value, "Covariance", color=color.yellow, linewidth=2)
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