Evidence of Stock Returns and Abnormal Trading Volume: A Quantile Regression Approach
33 Pages Posted: 28 Jan 2015
Date Written: November 8, 2014
Abstract
This paper presents a CAPM-based threshold quantile regression model with GARCH specification to examine relations between stock excess returns and “abnormal trading volume.” By employing the Bayesian MCMC method with asymmetric Laplace distribution to six daily Dow Jones Industrial stocks, the proposed model captures asymmetric risk through market beta and volume coefficient that change discretely between regimes that are driven by market information and various quantile levels. This study finds significantly negative effects of abnormal volume on stock excess return under low quantile levels, nevertheless there are significantly positive effects under high quantile levels. The evidence indicates that each market beta varies with different quantile levels, capturing different states of market conditions.
Keywords: Quantile regression; Volume Asymmetric; GARCH; HP-filter; Market beta; MCMC
JEL Classification: C11; C22; C51; C52
Suggested Citation: Suggested Citation