Hands-On Machine Learning for Algorithmic Trading

Data-driven risk factors

In Chapter 7, Linear Models, we explored risk factor models used in quantitative finance to capture the main drivers of returns. These models explain differences in returns on assets based on their exposure to systematic risk factors and the rewards associated with these factors.

In particular, we explored the Fama-French approach, which specifies factors based on prior knowledge about the empirical behavior of average returns, treats these factors as observable, and then estimates risk model coefficients using linear regression. An alternative approach treats risk factors as latent variables and uses factor analytic techniques such as PCA to simultaneously estimate the factors and how they drive returns from historical ...