Comparing Fund Performance with Rolling Correlations and Risk Metrics
Summary
This tutorial describes a Python workflow for comparing two subfunds with the China Securities 1000 Index using weekly net asset values. It calculates rolling correlations over a 20-day window and plots how those relationships change, then compares period return, maximum drawdown, Sharpe ratio, volatility, Calmar ratio, and Sortino ratio. The document reports that one fund outperformed over the stated five-month period with lower drawdown, while the other lagged the index; it also notes that rolling correlations varied over time and may help assess market beta exposure.
These are reported results from a short historical period, not evidence that the funds will continue to perform similarly. The source does not give the underlying observations, calculation conventions, or enough detail to assess statistical reliability. In particular, its annualized return and risk-adjusted figures should be interpreted in light of the brief sample and the market's upward trend during the comparison.
Key ideas
- Compare fund net values with a market benchmark using rolling correlations.
- Assess performance with returns, drawdown, volatility, and risk-adjusted ratios.
- The tutorial reports different return and drawdown profiles for the two funds.
- Rolling correlation can help indicate whether performance is associated with market beta.
- Short historical results do not establish future performance.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.