Piecewise constant modeling and Kalman filter tracking of systematic market risk

In this paper, we present a new piecewise constant model to represent time-varying systematic risk, i.e., beta. We develop a new tracking algorithm for the new model based on modified Kalman filter that uses Bayes´ criteria. Empirical results show the superiority of our method over traditional random walk, mean reverting and moving window beta estimates.