The Sharpe Ratio measures risk-adjusted return by calculating excess return per unit of volatility. The formula is: (Portfolio Return − Risk-Free Rate) / Portfolio Standard Deviation. A Sharpe of 1.0 means one unit of excess return for each unit of risk taken. Above 1.0 is generally considered good; above 2.0 is excellent; sustained Sharpe above 3.0 is extremely rare outside of high-frequency strategies.
The ratio has important limitations: it assumes returns are normally distributed (they are not — fat tails are common), it penalizes upside volatility equally to downside volatility, and it uses standard deviation as the sole risk measure (ignoring drawdown depth and duration). Despite these limitations, the Sharpe Ratio remains the most widely used risk-adjusted performance metric because it enables direct comparison across strategies, asset classes, and time periods. In Closelook's portfolio framework, Sharpe is reported alongside maximum drawdown and Sortino ratio (which only penalizes downside deviation) for a more complete risk picture.
Raw returns are meaningless without context. A 20% return with 40% volatility (Sharpe 0.5) is inferior to a 12% return with 8% volatility (Sharpe 1.5). The Sharpe Ratio forces this comparison by measuring how much return you earn per unit of risk taken. Institutional investors typically target Sharpe ratios above 1.0, and the best hedge funds sustain ratios above 2.0 over multi-year periods.
Closelook's three-engine architecture is designed to maximize portfolio-level Sharpe Ratio through diversification across uncorrelated return streams. The Volatility Harvesting engine (options premium) has naturally low correlation with the Structural Narrative engine (long-duration equity). Combining them produces a composite Sharpe higher than either engine alone — the mathematical benefit of genuine diversification rather than just holding more stocks.
Sharpe Ratio is reported for every Reference Portfolio, connects to Maximum Drawdown as a complementary risk measure, and benefits from Kelly Criterion position sizing.
