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Components of Bull and Bear Markets: Bull Corrections and Bear Rallies

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  • John M. Maheu
  • Thomas H. McCurdy
  • Yong Song

Abstract

Existing methods of partitioning the market index into bull and bear regimes do not identify market corrections or bear market rallies. In contrast, our probabilistic model of the return distribution allows for rich and heterogeneous intraregime dynamics. We focus on the characteristics and dynamics of bear market rallies and bull market corrections, including, for example, the probability of transition from a bear market rally into a bull market versus back to the primary bear state. A Bayesian estimation approach accounts for parameter and regime uncertainty and provides probability statements regarding future regimes and returns. We show how to compute the predictive density of long-horizon returns and discuss the improvements our model provides over benchmarks. This article has online supplementary materials.

Suggested Citation

  • John M. Maheu & Thomas H. McCurdy & Yong Song, 2012. "Components of Bull and Bear Markets: Bull Corrections and Bear Rallies," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 391-403, February.
  • Handle: RePEc:taf:jnlbes:v:30:y:2012:i:3:p:391-403
    DOI: 10.1080/07350015.2012.680412
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    2. Mathieu Gatumel & Florian Ielpo, 2014. "The Number Of Regimes Across Asset Returns: Identification And Economic Value," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 17(06), pages 1-25.
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    5. Gupta, Priyanshi & Sehgal, Sanjay & Deisting, Florent, 2015. "Time-Varying Bond Market Integration in EMU," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 30(4), pages 708-760.
    6. Li, Ziran & Sun, Jiajing & Wang, Shouyang, 2013. "Amplitude-Duration-Persistence Trade-off Relationship for Long Term Bear Stock Markets," MPRA Paper 54177, University Library of Munich, Germany.
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    8. Zeng, Songlin & Bec, Frédérique, 2015. "Do stock returns rebound after bear markets? An empirical analysis from five OECD countries," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 50-61.
    9. Aliyu, Shehu Usman Rano & Aminu, Abubakar Wambai, 2018. "Economic regimes and stock market performance in Nigeria: Evidence from regime switching model," MPRA Paper 91430, University Library of Munich, Germany, revised 03 Oct 2018.
    10. Kuang-Liang Chang & Nan-Kuang Chen & Charles Ka Yui Leung, 2016. "Losing Track of the Asset Markets: the Case of Housing and Stock," International Real Estate Review, Asian Real Estate Society, vol. 19(4), pages 435-492.
    11. repec:wly:japmet:v:33:y:2018:i:3:p:297-318 is not listed on IDEAS
    12. Bejaoui, Azza & Karaa, Adel, 2016. "Revisiting the bull and bear markets notions in the Tunisian stock market: New evidence from multi-state duration-dependence Markov-switching models," Economic Modelling, Elsevier, vol. 59(C), pages 529-545.
    13. Sehgal, Sanjay & Gupta, Priyanshi & Deisting, Florent, 2014. "Assessing Time-Varying Stock Market Integration in EMU for Normal and Crisis Periods," MPRA Paper 64078, University Library of Munich, Germany.
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    15. Yong Song, 2014. "Modelling Regime Switching And Structural Breaks With An Infinite Hidden Markov Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 825-842, August.
    16. Jia Liu & John M. Maheu, 2018. "Improving Markov switching models using realized variance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(3), pages 297-318, April.
    17. Chang, Kuang-Liang, 2016. "Does the return-state-varying relationship between risk and return matter in modeling the time series process of stock return?," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 72-87.
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    19. Nicolau, João, 2016. "Structural change test in duration of bull and bear markets," Economics Letters, Elsevier, vol. 146(C), pages 64-67.
    20. Erik Kole & Dick Dijk, 2017. "How to Identify and Forecast Bull and Bear Markets?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 120-139, January.
    21. Jeff Fleming & Chris Kirby, 2013. "Component-Driven Regime-Switching Volatility," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 11(2), pages 263-301, March.
    22. Ntantamis, Christos & Zhou, Jun, 2015. "Bull and bear markets in commodity prices and commodity stocks: Is there a relation?," Resources Policy, Elsevier, vol. 43(C), pages 61-81.
    23. Julien Chevallier & Mathieu Gatumel & Florian Ielpo, 2013. "Understanding momentum in commodity markets," Applied Economics Letters, Taylor & Francis Journals, vol. 20(15), pages 1383-1402, October.
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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G1 - Financial Economics - - General Financial Markets

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