Orthogonalizing independent variables
SUMMARY
INTRODUCTION
Although artificial intelligence and machine learning have advanced rapidly in finance, most portfolio risk and return analysis still relies on traditional linear regression. The underlying math has not changed much, but the frameworks and factor sets have evolved significantly.
For instance, MSCI’s risk attribution model separates contributions from currency, market timing, and residuals. Within residuals, it further distinguishes between specific and common factors such as industry, country, global, and risk indices – allowing for quite granular analysis.