Fidamen

Sharpe Ratio Calculator

This Sharpe ratio calculator computes an annualized Sharpe ratio from either periodic statistics or direct annual inputs. You can provide periodic mean and standard deviation and let the calculator annualize them, or supply already-annualized values.

The tool focuses on transparency and reproducibility: it exposes the intermediate annualized mean and annualized standard deviation, and documents assumptions and known limitations so you can evaluate model fit and data quality.

Updated Nov 28, 2025QA PASS — golden 25 / edge 120Run golden-edge-2026-01-23

Governance

Record 74634f12a4d4 • Reviewed by Fidamen Standards Committee

Use when you have periodic mean return and periodic standard deviation (e.g., daily mean and daily std). The tool annualizes both using the provided periods-per-year.

Inputs

Results

Updates as you type

Sharpe ratio (annualized)

0.7307

Annualized mean return

25.20%

Annualized standard deviation

31.75%

OutputValueUnit
Sharpe ratio (annualized)0.7307—
Annualized mean return25.20%—
Annualized standard deviation31.75%—
Primary result0.7307

Visualization

Methodology

The Sharpe ratio is defined as the expected excess return over the risk-free rate divided by the return standard deviation. This implementation supports three practical workflows: (1) periodic statistics converted to annualized measures, (2) direct annual inputs, and (3) periodic excess-return inputs.

Annualization follows standard financial practice: mean is multiplied by the number of periods per year; standard deviation is scaled by the square root of the number of periods per year. Users must ensure the risk-free rate and return inputs share the same periodic basis before annualizing.

Worked examples

Example 1: Daily mean return = 0.001 (0.1%), daily std = 0.02 (2%), periods_per_year = 252, risk-free = 0.02 (2%). Annualized mean = 0.252, annualized std = 0.02 × sqrt(252) ≈ 0.317, Sharpe ≈ (0.252 − 0.02) / 0.317 ≈ 0.73.

Example 2: If you already have annualized inputs: mean_annual = 0.10, std_annual = 0.15, risk-free = 0.02, Sharpe = (0.10 − 0.02)/0.15 = 0.533.

F.A.Q.

Do I need to annualize my inputs?

You can either provide periodic statistics plus the number of periods per year or provide annualized statistics directly. If you supply periodic numbers, set periods_per_year to match your data frequency (e.g., 252 for daily). Make sure the risk-free rate is on the same annual basis as the annualized returns.

What are common pitfalls and assumptions?

Sharpe ratio assumes stationarity and symmetric dispersion of returns; it is sensitive to sample size and outliers. For short return series or heavy-tailed return distributions, the ratio can be misleading. Use additional diagnostics such as skewness, kurtosis, and confidence intervals when possible.

How accurate is the result?

Numerical accuracy depends on the quality of inputs, the chosen periods_per_year, and whether returns are independent and identically distributed. Small samples increase estimation error. Treat the Sharpe ratio as a point estimate and consider its sampling variability before making decisions.

Are there regulatory or industry standards I should consider?

This calculator is intended for analysis and decision support; it is not a substitute for formal model validation. Follow applicable organizational and regulatory guidelines for model risk management and operational controls such as those from NIST, ISO, and industry best-practice frameworks. Maintain reproducible records of inputs and provenance.

Sources & citations

Further resources

Versioning & Change Control

Audit record (versions, QA runs, reviewer sign-off, and evidence).

Record ID: 74634f12a4d4

What changed (latest)

v1.0.0 • 2025-11-28 • MINOR

Initial publication and governance baseline.

Why: Published with reviewed formulas, unit definitions, and UX controls.

Public QA status

PASS — golden 25 + edge 120

Last run: 2026-01-23 • Run: golden-edge-2026-01-23

Engine

v1.0.0

Data

Baseline (no external datasets)

Content

v1.0.0

UI

v1.0.0

Governance

Last updated: Nov 28, 2025

Reviewed by: Fidamen Standards Committee (Review board)

Credentials: Internal QA

Risk level: low

Reviewer profile (entity)

Fidamen Standards Committee

Review board

Internal QA

Entity ID: https://fidamen.com/reviewers/fidamen-standards-committee#person

Semantic versioning

  • MAJOR: Calculation outputs can change for the same inputs (formula, rounding policy, assumptions).
  • MINOR: New features or fields that do not change existing outputs for the same inputs.
  • PATCH: Bug fixes, copy edits, or accessibility changes that do not change intended outputs except for previously incorrect cases.

Review protocol

  • Verify formulas and unit definitions against primary standards or datasets.
  • Run golden-case regression suite and edge-case suite.
  • Record reviewer sign-off with credentials and scope.
  • Document assumptions, limitations, and jurisdiction applicability.

Assumptions & limitations

  • Uses exact unit definitions from the Fidamen conversion library.
  • Internal calculations use double precision; display rounding follows the unit's configured decimal places.
  • Not a substitute for calibrated instruments in regulated contexts.
  • Jurisdiction-specific rules may require official guidance.

Change log

v1.0.0 • 2025-11-28 • MINOR

Initial publication and governance baseline.

Why: Published with reviewed formulas, unit definitions, and UX controls.

Areas: engine, content, ui • Reviewer: Fidamen Standards Committee • Entry ID: f3eaa0dd0d0e