Smooth transition quantile capital asset pricing models with heteroscedasticity

Cathy W. S. CHEN, Simon LIN, Leung Ho Philip YU

Research output: Contribution to journalArticles

12 Citations (Scopus)

Abstract

Capital asset pricing model (CAPM) has become a fundamental tool in finance for assessing the cost of capital, risk management, portfolio diversification and other financial assets. It is generally believed that the market risks of the assets, often denoted by a beta coefficient, should change over time. In this paper, we model timevarying market betas in CAPM by a smooth transition regime switching CAPM with heteroscedasticity, which provides flexible nonlinear representation of market betas as well as flexible asymmetry and clustering in volatility. We also employ the quantile regression to investigate the nonlinear behavior in the market betas and volatility under various market conditions represented by different quantile levels. Parameter estimation is done by a Bayesian approach. Finally, we analyze some Dow Jones Industrial stocks to demonstrate our proposed models. The model selection method shows that the proposed smooth transition quantile CAPM–GARCH model is strongly preferred over a sharp threshold transition and a symmetric CAPM–GARCH model. Copyright © 2011 Springer Science+Business Media, LLC.
Original languageEnglish
Pages (from-to)19-48
JournalComputational Economics
Volume40
Issue number1
Early online dateApr 2011
DOIs
Publication statusPublished - Jun 2012

Citation

Chen, C. W. S., Lin, S., & Yu, P. L. H. (2012). Smooth transition quantile capital asset pricing models with heteroscedasticity. Computational Economics, 40(1), 19-48. doi: 10.1007/s10614-011-9266-y

Keywords

  • Bayesian inference
  • CAPM
  • GARCH
  • Quantile regression
  • Skewed-Laplace distribution
  • Smooth transition

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