IMLInvestment
Model Library

Statistical estimation / v1.0.0

Zero-mean EWMA variance

Track an explicit initial variance through a zero-mean exponentially weighted update.

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

v_(t+1) = lambda*v_t + (1 - lambda)*r_t^2
Version 1.0.0 input contract
InputAllowed valuesMeaning
returns2-250 decimals, -1 to 10Chronological equal-frequency observations
initial_varianceSquared decimal, 0 to 100Variance before the first supplied return
lambdaDecimal, 0 to 1Decay parameter, not fitted here

Method and interpretation

Each supplied return updates the variance for the next period. The output path therefore begins after the first observation, not at the initial variance. This convention avoids attaching an updated estimate to a decision made before the return was observed.

With initial variance 0.0001 and decay 0.94, the first 1% return leaves variance unchanged. The following -2% return raises it to 0.000118. A 1.5% third return then produces 0.00012442. The path and terminal value are both available for reconciliation.

Where the reference stops

A zero conditional mean is assumed. Lambda=1 freezes the initial value; lambda=0 uses only the latest squared return. No parameter fitting, expected return adjustment, missing-period decay or empirical forecast score is provided.

Published synthetic inputs

{
  "returns": [
    0.01,
    -0.02,
    0.015
  ],
  "initial_variance": 0.0001,
  "lambda": 0.94
}

Frozen calculation output

{
  "variance_path": [
    0.0001,
    0.00011800000000000002,
    0.00012442000000000003
  ],
  "next_period_variance": 0.00012442000000000003,
  "next_period_volatility": 0.01115437134042076
}

Zero conditional mean assumption; each observation updates variance for the following period. No fitted decay parameter or forecast validation.

Verification coverage

  • Recursion independently replayed, including decay endpoints.
  • Initial condition, ordering and negative variance validation covered.

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

Method references

Read the assumptions in context

Statistical estimation

EWMA Variance Needs a Seed and an Information Clock

The decay parameter alone does not define an EWMA variance series. Initialization, mean treatment, normalization and observation timing determine its early and subsequent values.

Risk measurement

Covariance Units and Frequency Must Travel With the Matrix

Decimal versus percentage returns and daily versus annual horizons change covariance scales. Correct matrix multiplication cannot repair mismatched units or unsupported time aggregation.