The article discusses how linear regression models are used in investment management to understand relationships between variables. By assuming a linear connection between variables, researchers can estimate relationships and make predictions. Different assumptions and computational methods can be used to improve the model's flexibility. For multivariate regression, prior distributions for coefficients and covariance are needed for estimation.