evaluate-time-series

To evaluate time-series factors for robust trading signals, calculate predictive performance metrics like hit rate, profit/loss ratio, and decay curves across 1, 5, and 20 day forward return horizons, then generate a standardized tearsheet for validation.

Factor evaluation in quant research uses standardized performance metrics including hit rate, profit/loss ratio, decay curves, cash period counts, and full tearsheets to quantify predictive power across multiple forward return horizons like 1, 5, and 20 day periods.

Test timing and rotation signals by evaluating time-series factors across 1, 5, and 20 day forward return periods. This multi-horizon performance testing produces standardized tearsheets to quantify the predictive performance and trading viability of your signals.

You need to generate a tearsheet for factor validation when you have developed a factor predicting individual stock or small basket price direction and want to validate its predictive power across multiple time horizons to determine if it is suitable for a live trading strategy.

Yes, you can use a decay curve to assess the trading viability of a time-series factor. The decay curve is one of the standardized performance metrics calculated across 1, 5, and 20 day forward return periods to quantify predictive performance and signal decay.

Evaluating time-series factors eliminates tedious, error-prone manual work by automating the calculation of hit rate, profit/loss ratio, and decay curves across 1, 5, and 20 day forward returns, ensuring consistent and reliable assessments for timing and rotation trading signals.