ml_portfolio Signal diversification & redundancy audit

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Turns “I have 180 indicators” into “which of them actually add anything.” Convert each signal to its own return STREAM, correlate the streams, and grade how redundant vs complementary a set is — so you weight the diversifiers and prune the duplicates.

Design (host-fed): pairwise correlation needs two full series with history, so the host computes each pair’s rollingCorr and collects them into an array; this library standardizes the return-stream construction, the pair test, and the set-level diversification grade. Pure functions of what you pass; nothing repaints.

Concept credit: return-stream correlation and diversification grading are standard portfolio-construction ideas — original, dependency-free Pine v6 packaging. Educational; not financial advice.

Library "ml_portfolio"

signalReturn(longSig, shortSig, ret)
  Parameters:
    longSig (bool)
    shortSig (bool)
    ret (float)

rollingCorr(a, b, len)
  Parameters:
    a (float)
    b (float)
    len (simple int)

redundantPair(a, b, len, thr)
  Parameters:
    a (float)
    b (float)
    len (simple int)
    thr (simple float)

avgAbsCorr(corrs)
  Parameters:
    corrs (array<float>)

diversificationScore(corrs)
  Parameters:
    corrs (array<float>)

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