Machine Learning for Algorithmic Trading - Second Edition

9

Time-Series Models for Volatility Forecasts and Statistical Arbitrage

In Chapter 7, Linear Models – From Risk Factors to Asset Return Forecasts, we introduced linear models for inference and prediction, starting with static models for a contemporaneous relationship with cross-sectional inputs that have an immediate effect on the output. We presented the ordinary least squares (OLS) learning algorithm, and saw that it produces unbiased coefficients for a correctly specified model with residuals that are not correlated with the input variables. Adding the assumption that the residuals have constant variance guarantees that OLS produces the smallest mean squared prediction error among unbiased estimators.

We also encountered panel data that ...