Stock Return Predictability by Bayesian Model Averaging: Evidence from Stock Exchange of Thailand
Kmonwan Chairakwattana and
Sarayut Nathaphan
International Journal of Economic Sciences, 2014, vol. 2014, issue 1, 47-63
Abstract:
This research paper examines the predictability power on future stock returns by employing the concept of Bayesian Model Averaging (BMA). The sample focuses on Stock Exchange of Thailand (SET) over 2001-2011. Predictors for return predictability contain financial information which are dividend yield, Book-to-Market, Earning yield, Default risk premium, Monthly rate of three-month Treasury bill, Term premium, Monthly inflation rate and Term spread. This paper also explores the predictability power over financial crisis, sub-period over 2008-2009. In addition, this paper compares expected returns from two models between BMA and traditional regression (Fama and Macbeth two steps procedure). Results indicated that BMA approach outperforms the traditional regression model.
Keywords: Stock Return; Investment Decision; Bayesian Model Averaging; Portfolio; Asset Pricing; Model Uncertainty (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.vse.cz/ijes/7 (text/html)
free of charge
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:prg:jnljes:v:2014:y:2014:i:1:id:7:p:47-63
Ordering information: This journal article can be ordered from
IISES, Kamerunska 607/1, Prague, Czech Republic
http://www.vse.cz/ijes/
Access Statistics for this article
International Journal of Economic Sciences is currently edited by Klara Cermakova
More articles in International Journal of Economic Sciences from Prague University of Economics and Business Contact information at EDIRC.
Bibliographic data for series maintained by Stanislav Vojir ().