Asia-Pacific Financial Markets

, Volume 18, Issue 2, pp 167–189 | Cite as

The Regime Switching Portfolios

  • Hiroshi IshijimaEmail author
  • Masaki Uchida


In this paper we develop a portfolio selection theory under regime switching means and volatilities. We use log mean-variance as the portfolio selection criteria and, as a result, the theory is made substantially easier to implement than other existing theories. Moreover, the estimated regimes are easy to interpret as one of the regimes corresponds to the business cycle turning points. Finally, we conduct an asset allocation simulation and obtain reasonable results by introducing an idea of switching volatility targets.


Markov switching model Continuous-and discrete-time regime switching Log mean-variance Portfolio selection EM algorithm 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Ang A., Bekaert G. (2002) International asset allocation with regime shifts. Review of Financial Studies 15: 1137–1187CrossRefGoogle Scholar
  2. Breiman, L. (1961). Optimal gambling systems for favorable games. In Proceedings of the 4th Berkeley symposium on mathematical statistics and probability (Vol. I, pp. 65–78).Google Scholar
  3. Campbell J. Y., Viceira L. M. (2002) Strategic asset allocation: Portfolio choice for long-term investors. Oxford University Press, OxfordGoogle Scholar
  4. Cover T. M., Thomas J. A. (1991) Elements of information theory. Wiley, New YorkCrossRefGoogle Scholar
  5. Cox J. C., Ingersoll J. E., Ross S. A. (1985) A theory of the term structure of interest rates. Econometrica 53: 385–408CrossRefGoogle Scholar
  6. Dempster A. P., Laird N. M., Rubin D. B. (1977) Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society Series B 39: 1–38Google Scholar
  7. Diebold F. X., Lee J., Weinbach G. C. (1994) Regime switching with time-varying transition probabilities. In: Hargreaves C. (eds) Nonstationary time series analysis and cointegration. Oxford University Press, Oxford, pp 283–302Google Scholar
  8. Elliott R. J. (1994) Exact adaptive filters for Markov chains observed in Gaussian noise. Automatica 30: 1399–1408CrossRefGoogle Scholar
  9. Elliott R. J., Aggoun L., Moore J. B. (1995) Hidden Markov models: Estimation and control. Springer, New YorkGoogle Scholar
  10. Elliott R. J., van der Hoek J. (1997) An application of hidden Markov models to asset allocation problems. Finance and Stochastics 1: 229–238CrossRefGoogle Scholar
  11. Filardo A. J. (1994) Business-cycle phases and their transitional dynamics. Journal of Business and Economic Statistics 12: 299–308CrossRefGoogle Scholar
  12. Hamilton J. D. (1989) A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica 57: 357–384CrossRefGoogle Scholar
  13. Hamilton J. D. (1990) Analysis of time series subject to changes in regime. Journal of Econometrics 45: 39–70CrossRefGoogle Scholar
  14. Hamilton J. D. (1994) Time series analysis. Princeton University Press, PrincetonGoogle Scholar
  15. Kelly J. L. (1956) A new interpretation of information rate. Bell System Technical Journal 35: 917–926Google Scholar
  16. Kim C.-J. (1993) Dynamic linear models with Markov-switching. Journal of Econometrics 60: 1–22CrossRefGoogle Scholar
  17. Konno H., Pliska S., Suzuki K. (1993) Optimal portfolio with asymptotic criteria. Annals of Operations Research 45: 187–204CrossRefGoogle Scholar
  18. Krolzig, H. (1997). Markov-switching vector autoregressions: Modelling, statistical inference, and application to business cycle analysis. Lecture Notes in Economics and Mathematical Systems (Vol. 454). Berlin: Springer.Google Scholar
  19. Layton A. P., Katsuura M. (2001) Comparison of regime switching, probit and logit models in dating and forecasting US business cycles. International Journal of Forecasting 17: 403–417CrossRefGoogle Scholar
  20. Luenberger D. G. (1993) A preference foundation for log mean-variance criteria in portfolio choice problems. Journal of Economic Dynamics and Control 17: 887–906CrossRefGoogle Scholar
  21. Maheu J. M., McCurdy T. H. (2000) Indentifying bull and bear markets in stock returns. Journal of Business and Economic Statistics 18: 100–112CrossRefGoogle Scholar
  22. Merton R. C. (1969) Lifetime portfolio selection under uncertainty: The continuous-time case. Review of Economics and Statistics 51: 247–257CrossRefGoogle Scholar
  23. Merton R. C. (1971) Optimum consumption and portfolio rules in a continuous-time model. Journal of Economic Theory 3: 373–413CrossRefGoogle Scholar
  24. Mizrach B., Watkins J. (1999) A Markov switching cookbook. In: Rothman P. (eds) Nonlinear time series analysis of economic and financial data. Kluwer, BostonGoogle Scholar
  25. Perez-Quiros G., Timmermann A. (1998) Variations in the mean and volatility of stock returns around turning points of the business cycle. In: Knight J., Satchell S. (eds) Forecasting volatility in the financial markets. Butterworth-Heinemann, OxfordGoogle Scholar
  26. Psaradakis Z., Sola M. (1998) Finite-sample properties of the maximum likelihood estimator in autoregressive models with Markov switching. Journal of Econometrics 86: 369–386CrossRefGoogle Scholar
  27. Schaller H., van Norden S. (1997) Regime switching in stock market returns. Applied Financial Economics 7: 177–191CrossRefGoogle Scholar
  28. Thorp, E. O. (1971). Portfolio choice and the Kelly criterion. In Proceedings of the 1971 Business and Economics Section of the American Statistical Association (pp. 215–224).Google Scholar
  29. Timmermann A. (2000) Moments of Markov switching models. Journal of Econometrics 96: 75–111CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC. 2010

Authors and Affiliations

  1. 1.Graduate School of International AccountingChuo UniversityTokyoJapan
  2. 2.JPMorgan Asset Management (Japan) Ltd.TokyoJapan

Personalised recommendations