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Risk-adjusted return metrics allow investors to compare strategies on a level playing field by normalizing performance for the amount of risk taken. A strategy that returns 15% with 30% volatility is less efficient than one returning 10% with 10% volatility, but this only becomes apparent when risk is explicitly accounted for. These metrics are essential for portfolio allocation decisions, manager evaluation, and strategy comparison.
The Sharpe ratio remains the most widely used risk-adjusted return metric. It divides excess return (return above the risk-free rate) by total volatility. While intuitive and easy to compute, the Sharpe ratio has known limitations. It penalizes upside volatility equally with downside volatility, assumes returns are normally distributed (which they are not), and can be gamed by strategies that suppress reported volatility through infrequent pricing or option-selling strategies that generate steady small gains with occasional large losses.
The Sortino ratio improves upon the Sharpe ratio by using only downside deviation (returns below a minimum acceptable return) in the denominator. This is more aligned with how investors actually experience risk: they care about losses, not about positive surprises. A strategy with many large positive returns and few negative returns will have a much higher Sortino ratio than Sharpe ratio, correctly reflecting its favorable risk characteristics. The Sortino ratio is particularly useful for evaluating strategies with asymmetric return distributions.
The Calmar ratio divides annualized return by maximum drawdown. It directly measures what matters most to many investors: how much you can expect to make relative to the worst loss you might endure. A Calmar ratio above 1.0 means the strategy's annualized return exceeds its worst drawdown. This metric is especially popular among commodity trading advisors and hedge fund allocators. The main limitation is that maximum drawdown is a single point estimate and is path-dependent: it depends on when the strategy started.
Information ratio measures a manager's excess return over a benchmark relative to the tracking error (standard deviation of excess returns). It is the benchmark-relative analog of the Sharpe ratio and is the preferred metric for evaluating active managers. An information ratio above 0.5 is generally considered good, and above 1.0 is exceptional. Unlike the Sharpe ratio, the information ratio rewards consistency: a manager who modestly outperforms every year will have a higher information ratio than one who dramatically outperforms some years and underperforms others.