A Bayesian Inference Approach to Testing Mean Reversion in the Swedish Stock Market

Abstract

In this paper we use a Bayesian approach to test for mean reversion in the Swedish stock market on monthly data 1918-1998. By simply account for the heteroscedasticity of the data with a two-state hidden Markov model of normal distributions and taking estimation bias into account via Gibbs sampling we cannot find support of mean reversion. This is a contradiction to previous result from Sweden. We find that a tranquil and a volatile regime can characterize the Swedish stock market and within the regimes the stock market is random. This finding of randomness is in line with recent evidence for the U.S stock market.

Keywords: Market efficiency, variance ratio, Gibbs sampling, hidden Markov chains, MCMC

JEL Classification: G10 C11 C15