---
title: "Choose how a method estimates risk"
description: "Pick the covariance or correlation estimate an allocation method reads, set its decay or shrinkage, and know when an estimator has no effect or stops a run."
canonical_url: "https://fincanva.com/docs/strategies/choose-how-a-method-estimates-risk"
last_updated: "2026-10-06"
md_url: "https://fincanva.com/docs/strategies/choose-how-a-method-estimates-risk.md"
---

# Choose how a method estimates risk

Methods built on volatilities and correlations read them through an estimate you choose on the method, in the [strategy](/glossary/strategy)'s **Allocation** card: the **Covariance matrix**, or the **Correlation matrix** on [Min correlation](/glossary/min-correlation).

## Steps

1. Open the **Allocation** card on a method that reads one — see [which methods use the covariance matrix](/glossary/covariance-matrix#which-methods-use-the-covariance-matrix).
2. Press **Change** beside **Covariance matrix** (or **Correlation matrix**) and pick an estimate; the covariance list marks Ledoit-Wolf · constant correlation **Recommended**. What each one does is on [covariance matrix](/glossary/covariance-matrix).
3. For **EWMA**, set the **Decay factor**; for **Manual shrinkage**, enter the **Shrinkage intensity**, which is required.
4. Check the [in-sample period](/glossary/calculation-window) is long enough for the estimator you chose — the card warns when it is not.
5. On a split strategy, repeat for the other profile: [Risk-On and Risk-Off](/glossary/risk-on-and-risk-off) keep their own estimate.
6. On Min correlation, a chip under the method names any choice other than Sample: "Correlation: Pearson", "Correlation: Spearman", "Correlation: Kendall", "Correlation: EWMA" or "Correlation: Marchenko-Pastur".

**Done.** The method reads its volatilities and correlations through the estimate you chose, from the next [backtest](/glossary/backtest) on.

## Why does an estimator have no effect with a short history?

**Two advanced estimators need enough history, and quietly fall back to Sample without it.** Regime-conditional (HMM) needs about 126 trading days — an in-sample period of at least 6 months — and also falls back when calm and turbulent periods cannot be told apart. Nonlinear Ledoit-Wolf needs about 30 trading days, so at least 2 months. When the window is too short the app warns: "With this history the estimate has no effect", with an action to lengthen the in-sample period.

## Why does a flat-priced instrument stop the backtest?

**An instrument whose price stayed flat for the whole window has no measured risk, and most estimates leave it that way.** With Sample, Ledoit-Wolf · constant correlation, EWMA, Manual shrinkage, Marchenko-Pastur or Regime-conditional (HMM), such an [instrument](/glossary/instrument) stops the backtest when the method is [Hierarchical risk parity](/glossary/hierarchical-risk-parity), [Hierarchical equal risk contribution](/glossary/hierarchical-equal-risk-contribution), [Nested clustered optimization](/glossary/nested-clustered-optimization) or [Max diversification](/glossary/max-diversification). Ledoit-Wolf · identity and Nonlinear Ledoit-Wolf give it a small positive risk instead, so the backtest runs — Nonlinear Ledoit-Wolf only once the window holds about 30 trading days, below which it behaves as Sample.

Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3)