Bayesian Analysis of a Regime Switching In-Mean Effect for the Polish Stock Market
AbstractThe study aims at a statistical verification of breaks in the risk-return relationship for shares of individual companies quoted at the Warsaw Stock Exchange. To this end a stochastic volatility model incorporating Markov switching in-mean effect (SV-MS-M) is employed. We argue that neglecting possible regime changes in the relation between expected return and volatility within an ordinary SV-M specification may lead to spurious insignificance of the risk premium parameter (as being 'averaged out' over the regimes). Therefore, we allow the volatility-in-mean effect to switch over different regimes according to a discrete homogeneous two- or three-state Markov chain. The model is handled within Bayesian framework, which allows to fully account for the uncertainty of model parameters, latent conditional variances and state variables. MCMC methods, including the Gibbs sampler, Metropolis-Hastings algorithm and the forward-filtering-backward-sampling scheme are suitably adopted to obtain posterior densities of interest as well as marginal data density. The latter allows for a formal model comparison in terms of the in-sample fit and, thereby, inference on the 'adequate' number of the risk premium regimes.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by CEJEME in its journal Central European Journal of Economic Modelling and Econometrics.
Volume (Year): 3 (2011)
Issue (Month): 4 (December)
Contact details of provider:
Web page: http://cejeme.org/
Markov switching; stochastic volatility; risk premium; in-mean effect; Bayesian analysis;
Find related papers by JEL classification:
- C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Hui Guo & Robert F. Whitelaw, 2003.
"Uncovering the Risk-Return Relation in the Stock Market,"
NBER Working Papers
9927, National Bureau of Economic Research, Inc.
- Hui Guo & Robert F. Whitelaw, 2006. "Uncovering the Risk-Return Relation in the Stock Market," Journal of Finance, American Finance Association, vol. 61(3), pages 1433-1463, 06.
- Hui Guo & Robert Whitelaw, 2005. "Uncovering the risk-return relation in the stock market," Working Papers 2001-001, Federal Reserve Bank of St. Louis.
- Hibbert, Ann Marie & Daigler, Robert T. & Dupoyet, Brice, 2008. "A behavioral explanation for the negative asymmetric return-volatility relation," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2254-2266, October.
- Paul Harrison & Harold H. Zhang, 1999. "An Investigation Of The Risk And Return Relation At Long Horizons," The Review of Economics and Statistics, MIT Press, vol. 81(3), pages 399-408, August.
- Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-31, February.
- Campbell, John, 1987.
"Stock Returns and the Term Structure,"
3207699, Harvard University Department of Economics.
- Guo, Hui & Neely, Christopher J., 2008.
"Investigating the intertemporal risk-return relation in international stock markets with the component GARCH model,"
Elsevier, vol. 99(2), pages 371-374, May.
- Hui Guo & Christopher J. Neely, 2006. "Investigating the intertemporal risk-return relation in international stock markets with the component GARCH model," Working Papers 2006-006, Federal Reserve Bank of St. Louis.
- Chib, Siddhartha, 1996. "Calculating posterior distributions and modal estimates in Markov mixture models," Journal of Econometrics, Elsevier, vol. 75(1), pages 79-97, November.
- Sei-Wan Kim & Bong-Soo Lee, 2008. "Stock Returns, Asymmetric Volatility, Risk Aversion, And Business Cycle: Some New Evidence," Economic Inquiry, Western Economic Association International, vol. 46(2), pages 131-148, 04.
- Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
- Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993.
" On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks,"
Journal of Finance,
American Finance Association, vol. 48(5), pages 1779-1801, December.
- Lawrence R. Glosten & Ravi Jagannathan & David E. Runkle, 1993. "On the relation between the expected value and the volatility of the nominal excess return on stocks," Staff Report 157, Federal Reserve Bank of Minneapolis.
- Siem Jan Koopman & Eugenie Hol Uspensky, 2002. "The stochastic volatility in mean model: empirical evidence from international stock markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(6), pages 667-689.
- French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
- Luc Bauwens & Michel Lubrano, 1998.
"Bayesian inference on GARCH models using the Gibbs sampler,"
Royal Economic Society, vol. 1(Conferenc), pages C23-C46.
- Bauwens, L. & Lubrano, M., . "Bayesian inference on GARCH models using the Gibbs sampler," CORE Discussion Papers RP -1307, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- BAUWENs, Luc & LUBRANO , Michel, 1996. "Bayesian Inference on GARCH Models using the Gibbs Sampler," CORE Discussion Papers 1996027, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Bauwens, L. & Lubrano, M., 1996. "Bayesian Inference on GARCH Models Using the Gibbs Sampler," G.R.E.Q.A.M. 96a21, Universite Aix-Marseille III.
- Ray Chou & Robert F. Engle & Alex Kane, 1991. "Measuring Risk Aversion From Excess Returns on a Stock Index," NBER Working Papers 3643, National Bureau of Economic Research, Inc.
- Harvey, Campbell R., 1989. "Time-varying conditional covariances in tests of asset pricing models," Journal of Financial Economics, Elsevier, vol. 24(2), pages 289-317.
- Bollerslev, Tim & Zhou, Hao, 2006. "Volatility puzzles: a simple framework for gauging return-volatility regressions," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 123-150.
- Backus, David K & Gregory, Allan W, 1993.
"Theoretical Relations between Risk Premiums and Conditional Variances,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 11(2), pages 177-85, April.
- David K. Backus & Allan W. Gregory, 1992. "Theoretical Relations Between Risk Premiums and Conditional Variances," Working Papers 92-18a, New York University, Leonard N. Stern School of Business, Department of Economics.
- Jacquier, Eric & Polson, Nicholas G. & Rossi, P.E.Peter E., 2004. "Bayesian analysis of stochastic volatility models with fat-tails and correlated errors," Journal of Econometrics, Elsevier, vol. 122(1), pages 185-212, September.
- Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
- Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-55, January.
- Gennotte, Gerard & Marsh, Terry A., 1993. "Variations in economic uncertainty and risk premiums on capital assets," European Economic Review, Elsevier, vol. 37(5), pages 1021-1041, June.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Krzysztof Osiewalski).
If references are entirely missing, you can add them using this form.