performance-metrics

Risk-adjusted returns are calculated using industry-standard ratios like Sharpe, Sortino, and Calmar to compare fund performance relative to volatility. This skill evaluates investment performance by computing these ratios and capture analysis to show which fund delivers better returns per unit of risk.

The Sharpe ratio measures risk-adjusted returns using total volatility, while the Sortino ratio isolates downside risk. This skill calculates both ratios, allowing users to assess investment performance based on overall fluctuation versus harmful downside deviations separately.

Yes, this skill depends on numpy to compute financial ratios including Treynor and Information Ratio. Users can process fund return arrays and benchmark data to evaluate investment performance on a risk-adjusted basis using these standard calculations.

Measuring investment performance against a benchmark involves calculating M-squared and Information Ratio for direct comparison. This skill provides benchmark-relative metrics, including upside and downside capture ratios, to assess whether a strategy outperforms or underperforms its market benchmark.

Evaluating downside risk requires the Sortino ratio, Omega ratio, and downside capture ratio. This skill computes these specific metrics to analyze the return distribution and assess how well an investment strategy handles negative market movements.

Yes, this skill calculates both the Calmar ratio and the Omega ratio. It evaluates investment performance comprehensively by computing these distribution analysis metrics alongside standard risk-adjusted ratios to provide a complete view of returns per unit of risk.