factor-models

To build a multi-factor risk model, define your asset universe, construct and standardize factor exposures like MKT, SMB, and HML, then run historical backtests to generate performance diagnostics and risk decomposition insights.

Factor risk decomposition attributes portfolio returns to specific factor exposures and alpha, using metrics like Information Coefficient (IC) and Information Ratio (IR) to evaluate how well your factors explain performance.

Yes, you can backtest factor strategies across US and global equities, bonds, and multi-asset universes, running historical simulations that include turnover and capacity analyses for each asset class.

You construct long-short portfolios by first creating and normalizing factor exposures for your selected factors, then applying neutralization techniques to isolate the factor premium from market and other risk exposures.

Evaluate factor premia by running historical backtests with performance diagnostics, measuring Information Coefficient and Information Ratio metrics, and analyzing turnover and capacity to assess the factor's viability.

Neutralizing factor exposures is a recommended step in the factor construction workflow, ensuring that your backtest results reflect the targeted factor premia rather than unintended risk exposures across your asset universe.