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LEARNAIMARKETS · AI-POWERED TRADING

Guide · Metrics

What is the Sharpe Ratio and how to interpret it

The Sharpe Ratio is the most widely used metric in portfolio management to measure risk-adjusted returns. It is not enough that a strategy makes money — what matters is how much risk it took to get there. The Sharpe compresses both variables into a single number and is the standard benchmark for comparing any investment strategy.

The formula: return divided by volatility

The Sharpe Ratio subtracts the risk-free rate from the strategy's return and divides the result by the annualised standard deviation of those returns:
Formula

Sharpe = (Rp − Rf) / σp

Rp = portfolio return · Rf = risk-free rate (short-term Treasury bills) · σp = annualised standard deviation

If a strategy returns 20% annualised with 10% standard deviation and the risk-free rate is 3%, the Sharpe is (20% − 3%) / 10% ≈ 1.70. The higher the Sharpe, the more return per unit of risk. The figures are an example, not a LearnAImarkets result.

What values are good, mediocre or excellent

There is no universal 'perfect' Sharpe, but there are widely accepted ranges in professional management:

The S&P 500 historically has a Sharpe of 0.5–0.8. A reference hedge fund typically targets 1.0–1.5. Very high figures (>3) over short periods deserve scepticism.

  • Poor

    < 1Returns do not compensate for the risk taken. Many active funds fall in this range.

  • Good

    1 – 2Benchmark for competent active strategies. The long-term S&P 500 Sharpe is around 0.5–0.8.

  • Excellent

    > 2Hard to sustain long-term. Often signals genuine statistical edge or measurement-period bias.

How the LearnAImarkets model uses it

The model publishes a live Sharpe Ratio on the walk-forward OOS backtest (OOS history from 2021). Each unit of risk taken translates into units of return net of the risk-free rate — on data the model never saw during training. Exact figures change with each training cycle; live metrics below.
  • The Sharpe is calculated on OOS (out-of-sample) data: the model never used it for training.
  • It includes NEUTRAL and high-cash periods — not just the best BULL moments.
  • The comparative benchmark is the equal-weighted S&P 500 without guardrails (Sharpe ~0.6).

Current model figures (out of sample)

Updated:

Sharpe1.14
CAGR17.8%
Max Drawdown-22.7%
Alpha3.1%

Current model metrics

You can see the updated historical Sharpe in the Performance section.

The limitations nobody usually explains

  • Assumes normal distribution

    The Sharpe penalises all volatility equally, including positive (strong up-moves). It does not detect fat tails or extreme events.

  • Sensitive to measurement period

    A Sharpe calculated over a bull market can look spectacular without the system having proved anything. Long and representative periods are required.

  • Does not distinguish up from down volatility

    The Sortino Ratio corrects this by penalising only downside volatility. For asymmetric strategies, Sortino is a better complement to Sharpe.

Frequently asked questions

Is a higher Sharpe always better?

Generally yes, but with caveats. A very high Sharpe over a short period may reflect luck or a favourable market regime. What matters is the stability of the Sharpe across different regimes: bull, bear and transition.

What Sharpe does the S&P 500 have?

The S&P 500 historically has a Sharpe of 0.5 to 0.8 depending on the measurement period. In the last decade, with low rates and a strong market, it may have reached 1.0–1.2. It is the standard passive benchmark.

Is the model's Sharpe good compared to the market?

On the OOS walk-forward backtest the model typically publishes a Sharpe clearly above the S&P 500 (~0.6) over the same period. The exact figure updates with each training cycle and can be consulted in the Backtest section. It indicates more return per unit of risk than passive exposure, though past performance does not guarantee future results.

What is the difference between Sharpe and Sortino?

Sortino only penalises downside volatility (negative returns), not upside. It better reflects strategies with strong gains and few drawdowns. For systems with low drawdowns, Sortino is typically higher than Sharpe.

Can I compare the Sharpe of two different strategies?

Yes, but make sure they are calculated over the same period and with the same risk-free rate reference. A Sharpe calculated over 3 years is not directly comparable to one calculated over 10.

View the model's full backtest

The model publishes the Sharpe Ratio, maximum drawdown, CAGR and Alpha vs benchmark in the Backtest section — updated after each training cycle.
View Backtest How the model works

External references

LearnAIMarkets is an educational platform. The information provided does not constitute financial, investment, legal or tax advice. Backtest metrics are historical and do not guarantee future returns. Investing carries risk of capital loss. Consult a financial advisor before making investment decisions.

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