factor-research

To evaluate cross-sectional factor predictive power, you need a factor-value CSV and a forward-return CSV to compute IC/IR metrics and run quantile backtests. This process outputs IC series, IC summaries, and group equity results to assess factor validity.

Running IC and quantile backtests for factor screening requires a structured factor-value CSV and a forward-return CSV as inputs. You compute cross-sectional factor values across instruments and dates, then execute the factor analysis tool to generate equity results.

IC/IR analysis for multi-factor combination works by evaluating the predictive power of individual cross-sectional financial factors across different industries or regimes. You compare IC series and group equity results to build robust multi-factor strategies.

Yes, you can test single-factor validity across different holding periods and instruments by feeding cross-sectional factor values and forward returns into the factor analysis tool. It outputs IC summaries and quantile backtest performance for systematic evaluation.

The best way to visualize quantile backtest performance is by running the factor analysis tool with your factor-value and forward-return CSVs. The tool generates group equity results, allowing you to assess predictive power and guide factor selection.