# Sharpe Ratio

Excess return earned per unit of total volatility.

Source data: AMFI daily NAV (17,900+ schemes) + Nifty benchmark indices. Last updated: 2026-07-02. Interactive tool: https://mfpro.tigzig.com

## What is the Sharpe Ratio?



The Sharpe Ratio measures risk-adjusted return: how much return you earn above the
 risk-free rate per unit of total volatility. Higher is better. It was introduced by
 William Sharpe in 1966 and is the most widely used risk-adjusted metric.

 


## How We Compute It


 
 Daily excess = fund_daily_return − (6% / 252)

Sharpe = (Mean daily excess × 252) / (StdDev of fund daily returns × √252)
 

Risk-free rate: 6% annualized (approximate India T-bill rate), which gives
 ~0.0238% daily. We use sample std dev (DuckDB's STDDEV function, divides by n-1).

 


## Worked Example



Sharpe calculation


Mean daily fund return: 0.055% (~13.9% annualized)


Risk-free daily: 0.024% (6% / 252)


StdDev of daily returns: 0.95%


Sharpe = (0.055 − 0.024) × 252 / (0.95 × √252)
= 7.812 / 15.07 = **0.52**

 
 


## How to Interpret





- Sharpe ≥ 1.0: Excellent risk-adjusted returns (shown in green)

- Sharpe 0.5-1.0: Good

- Sharpe 0-0.5: Positive but the return barely compensates for volatility

- Sharpe < 0: The fund didn't even beat the risk-free rate (shown in red)


 


## Edge Cases & Differences





- **Risk-free rate choice:** We use 6% p.a. (India context). Using a different
 rate changes the Sharpe. Some providers use the 91-day T-bill rate which fluctuates.
 Our fixed 6% gives a stable, comparable baseline.

- **Penalizes all volatility equally:** Sharpe penalizes upside volatility
 just as much as downside. A fund that jumps 5% up one day gets the same penalty as one
 that drops 5%. If this bothers you, look at Sortino instead.

- **Annualization:** We annualize both numerator and denominator from daily
 data. Some providers compute from monthly returns (multiply by √12). The numbers won't
 match exactly due to the different return frequencies.

## Related metrics

More Risk Metrics methodology from the MFPRO analytics tool:

- [Beta and R-Squared](/mfpro/beta-and-r-squared)

- [Alpha and t-statistic](/mfpro/alpha-and-t-stat)

- [Sortino Ratio](/mfpro/sortino-ratio)

- [Tracking Error and Information Ratio](/mfpro/tracking-error-information-ratio)

- [Capture Ratios (Upside and Downside)](/mfpro/capture-ratio)

- [Win Rate](/mfpro/win-rate)

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Source: https://www.tigzig.com/mfpro/sharpe-ratio