Journal article
Evidence of Stock Returns and Abnormal Trading Volume: A Threshold Quantile Regression Approach
Japanese economic review (Oxford, England), v 67(1), pp 96-124
01 Mar 2016
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
This paper presents a capital asset pricing model-based threshold quantile regression model with a generalized autoregressive conditional heteroscedastic specification to examine relations between excess stock returns and abnormal trading volume. We employ an adaptive Bayesian Markov chain Monte Carlo method with asymmetric Laplace distribution to study six daily Dow Jones Industrial stocks. The proposed model captures asymmetric risk through market beta and volume coefficients, which change discretely between regimes. Moreover, they are driven by market information and various quantile levels. This study finds that abnormal volume has significantly negative effects on excess stock returns under low quantile levels; however, 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.
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Details
- Title
- Evidence of Stock Returns and Abnormal Trading Volume: A Threshold Quantile Regression Approach
- Creators
- Cathy W. S. Chen - Feng Chia UniversityMike K. P. So - Hong Kong University of Science and TechnologyThomas C. Chiang - Drexel University
- Publication Details
- Japanese economic review (Oxford, England), v 67(1), pp 96-124
- Publisher
- Springer Nature
- Number of pages
- 29
- Grant note
- Marshall M. Austin Fund Le Bow College of Business, Drexel University MOST 103-2118-M-035-002-MY2 / Ministry of Science and Technology, Taiwan
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- [Retired Faculty]
- Web of Science ID
- WOS:000371673100005
- Scopus ID
- 2-s2.0-84958680610
- Other Identifier
- 991019167528204721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Economics