IMLInvestment
Model Library

Statistical estimation / v1.0.0

Single-benchmark return beta

Calculate a descriptive raw-return sensitivity to one aligned benchmark series.

Synthetic educational references. Not a fitted investment strategy, forecast, provider model or client return. First publication: 2026-10-16. Model and engine version 1.0.0.

Calculation contract

beta = sample_cov(benchmark, asset) / sample_var(benchmark)
Version 1.0.0 input contract
InputAllowed valuesMeaning
asset3-250 decimal returnsChronological raw asset returns
benchmarkSame length, nonconstant decimal returnsAligned reference returns

Method and interpretation

The default asset series is each benchmark return plus 0.005. Its slope is exactly one and its period intercept is 0.005. The intercept is a property of this invented relationship, not a demonstrated strategy premium.

A beta label is incomplete without the benchmark, sample dates, frequency and return definition. This fixture contains no real calendar or instrument identity. A real study must preserve them outside the array and ensure that each pair describes the same interval.

Where the reference stops

No risk-free series is deducted. Do not describe this raw intercept as CAPM alpha or interpret in-sample R-squared as investment quality. Nonlinear exposure, stale prices and changing factor sensitivities require a broader specification.

Published synthetic inputs

{
  "asset": [
    0.015,
    -0.005,
    0.025,
    0.005
  ],
  "benchmark": [
    0.01,
    -0.01,
    0.02,
    0
  ]
}

Frozen calculation output

{
  "slope": 1,
  "intercept": 0.005,
  "r_squared": 1,
  "residual_sum_squares": 3.76158192263132e-36,
  "observations": 4
}

Descriptive same-period raw-return beta and intercept. No risk-free adjustment; intercept is not a causal alpha estimate.

Verification coverage

  • Slope reconciled with covariance/variance and a known affine series.
  • Zero benchmark variance and unequal lengths rejected.

Unit and independent-reference checks test arithmetic and rejection rules, not future investment performance.

Method references

Read the assumptions in context

Statistical estimation

Regression fit is not forecast evidence

Separate least-squares estimation, conditional predictions and genuinely unseen forecast evaluation, including what a high fitted R-squared cannot establish.

Statistical estimation

Beta depends on its window and benchmark

Interpret beta as an estimated slope with a specific return definition, benchmark and observation window, rather than a permanent label attached to an asset.