Backtesting Metrics That Matter

The Foundation of Algorithmic Validation

Backtesting is the process of applying a trading strategy to historical data to determine its viability. At IndusRisk Analytics, we view backtesting not as a guarantee of success, but as a filter for failure. By simulating trades over years of market data, we uncover how a model behaves under various conditions—from bull markets to flash crashes.

Sharpe Ratio: Risk-Adjusted Efficiency

Why is risk-adjusted return king? Because a 20% return achieved through extreme volatility is rarely sustainable. The Sharpe Ratio measures the excess return per unit of deviation.

Definition

The average return earned in excess of the risk-free rate per unit of volatility.

Benchmark

A Sharpe Ratio above 1.0 is considered good; institutional desks often target 2.0 or higher.

Maximum Drawdown (MDD)

Understanding worst-case scenarios is vital for survival. MDD represents the maximum observed loss from a peak to a trough of a portfolio, before a new peak is attained.

Significance

It defines the 'Pain Threshold' for an investor or fund.

Mitigation

Strategies with MDD exceeding 20% often require refined stop-loss logic or position sizing.

Metrics aren't just numbers; they are the stress tests of your capital's endurance. At IndusRisk, we utilize asymmetric layout analysis to compare MDD against recovery time—the duration it takes to return to the previous peak.

Win/Loss Ratios vs. Profit Factor

Many novice traders obsess over Win Rate. However, a 90% win rate is useless if the 10% of losses wipe out all gains. The Profit Factor (Gross Profit / Gross Loss) provides a more holistic view of profitability.