Bayesian panel data analysis for exploring the impact of subprime financial crisis on the US stock market

Abstract

The effects of recent subprime financial crisis on the US stock market are analyzed. To investigate this problem, a Bayesian panel data analysis to identify common factors that explain the movement of stock returns when the dimension is high is developed. For high-dimensional panel data, it is known that previously proposed approaches cannot estimate accurately the variance-covariance matrix. An advantage of the proposed method is that it considers parameter uncertainty in variance-covariance estimation and factor selection. Two new criteria for determining the number of factors in the data are developed and the consistency of the selection criteria as both the number of observations and the..