Bayesian Linear Regression Model

This chapter discusses the univariate and multivariate linear regression models. Regression analysis is one of the most common econometric tools employed in the area of investment management. The univariate linear regression model attempts to explain the variability in one variable with the help of one or more other variables by asserting a linear relationship between them. In a normal setting and under conjugate priors, the posterior and predictive results are standard. Increased flexibility can be achieved by employing alternative distributional assumptions. Model estimation then is aided by numerical computational methods. A full Bayesian informative prior approach to estimation of the multivariate linear regression model would require one to specify proper prior distributions for the regression coefficients and the covariance matrix.