Understand that the strategy is using 4H data but why the simple_tear_sheet is using 1D data? What’s the difference between sharpe ratio 0.63 and rolling sharpe ratio (6-month)?
Course Name: Financial Time Series Analysis for Trading, Section No: 26, Unit No: 6, Unit type: Notebook
Hello,
In the capstone solution you are referring to, the create_simple_tear_sheet function is part of the Pyfolio library. It is typically designed to work with daily returns data, as Pyfolio’s annualized calculations assume daily data. If you provide 4-hour (4H) returns, annualized statistics will be miscalculated unless you resample them daily. If you pass 4H data without resampling, Pyfolio will still generate a tear sheet, but it will miscalculate metrics such as the Sharpe ratio, drawdowns, and other annualized statistics. Hence the returns data was resampled to daily in the solution.
The Sharpe ratio of 0.63 indicates how well the strategy has performed overall, considering both returns and risk. However, the rolling 6-month Sharpe ratio (~2) evaluates performance in smaller 6-month intervals (rolling), showing how it fluctuates over time. Since the rolling Sharpe is significantly higher than the overall Sharpe, it suggests that the strategy has performed well in recent 6-month periods compared to the entire analysis period.
Hope this solves your queries. Let us know if you have any additional queries on these.