Sharpe Ratio Optimizer

Sharpe = (Your Return - Risk-Free Rate) / Your Volatility. Example: 12% return, 4% risk-free, 16% volatility → (12-4)/16 = 0.5. Annualize both return and volatility before calculating.

Use the Bank of Canada overnight rate or 3-month T-bill rate. Currently around 4-5%. This is your hurdle rate - what you could earn without taking risk.

Generally yes, but context matters. A Sharpe of 3+ over a short period is likely luck or measurement error. Sustainable Sharpe above 1.0 is genuinely excellent. Compare to benchmark and peers.

At least 2 years for a reasonably reliable estimate. Shorter periods have very high estimation error. A 6-month Sharpe could easily be very different from the 'true' long-term Sharpe.

Yes. Negative Sharpe means your returns are below the risk-free rate - you're losing money compared to just holding cash. This indicates serious problems with the strategy.

Two paths: 1) Increase returns (better strategy, timing, reduced costs). 2) Decrease volatility (diversification, position sizing, hedging). Often easier to reduce volatility than increase returns.

Maintaining constant portfolio volatility by adjusting exposure. When current vol exceeds target, reduce positions. When it's below, increase. Formula: Adjustment = Target Vol / Current Vol.

Adding uncorrelated assets reduces portfolio volatility without reducing expected return proportionally. If two assets have 0 correlation, 50/50 portfolio has ~30% lower vol than average. Same return, lower vol = higher Sharpe.

Monthly to quarterly is typical. More frequent = closer to optimal but higher costs. Less frequent = lower costs but drift from optimal. Sweet spot depends on your transaction costs and volatility.

Sharpe is more common and comparable across strategies. Sortino is better if you have asymmetric returns (more upside than downside). Use both: Sharpe for comparison, Sortino for understanding downside risk.

1) Estimate expected returns (hard - use shrinkage or equilibrium). 2) Calculate covariance matrix (use Ledoit-Wolf shrinkage). 3) Solve optimization with constraints. 4) Use robust methods to avoid extreme weights.

Black-Litterman combines market equilibrium returns with your views using Bayesian framework. Use it when: 1) You have views on some assets. 2) You want more stable weights than MVO. 3) You want to avoid extreme positions.

Use Jobson-Korkie test or bootstrap. Given high estimation error of Sharpe, you need either: large difference (>0.3-0.4 for same period) OR long history to detect real differences. Most apparent differences aren't significant.

Ideally, Sharpe unchanged (both return and vol scale). But leverage has costs (margin interest) that reduce net Sharpe. Leverage improves results only if asset Sharpe > borrowing cost. Also increases drawdown risk.

Treat strategies as assets. Estimate each strategy's return, volatility, and correlations with other strategies. Use mean-variance optimization on strategies. Key is finding strategies with low correlation to each other.