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How to Identify and Forecast Bull and Bear Markets?

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  • Erik Kole
  • Dick Dijk

Abstract

The state of the equity market, often referred to as a bull or a bear market, is of key importance for financial decisions and economic analyses. Its latent nature has led to several methods to identify past and current states of the market and forecast future states. These methods encompass semi-parametric rule-based methods and parametric regime-switching models. We compare these methods by new statistical and economic measures that take into account the latent nature of the market state. The statistical measure is based directly on the predictions, while the economic mea- sure is based on the utility that results when a risk-averse agent uses the predictions in an investment decision. Our application of this framework to the S&P500 shows that rule-based methods are preferable for (in-sample) identification of the market state, but regime-switching models for (out-of-sample) forecasting. In-sample only the direction of the market matters, but for forecasting both means and volatilities of returns are important. Both the statistical and the economic measures indicate that these differences are significant.
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Suggested Citation

  • 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.
  • Handle: RePEc:wly:japmet:v:32:y:2017:i:1:p:120-139
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    Cited by:

    1. Jia Liu & John M. Maheu & Yong Song, 2024. "Identification and forecasting of bull and bear markets using multivariate returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 723-745, August.
    2. Haase, Felix & Neuenkirch, Matthias, 2023. "Predictability of bull and bear markets: A new look at forecasting stock market regimes (and returns) in the US," International Journal of Forecasting, Elsevier, vol. 39(2), pages 587-605.
    3. Linh Nguyen & Vilém Novák & Soheyla Mirshahi, 2020. "Trend‐cycle Estimation Using Fuzzy Transform and Its Application for Identifying Bull and Bear Phases in Markets," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 27(3), pages 111-124, July.
    4. Kirby, Chris, 2023. "A closer look at the regime-switching evidence of bull and bear markets," Finance Research Letters, Elsevier, vol. 52(C).
    5. Nicholas Apergis & Vasilios Plakandaras & Ioannis Pragidis, 2022. "Industry momentum and reversals in stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3093-3138, July.
    6. Asif, Raheel & Frömmel, Michael & Mende, Alexander, 2022. "The crisis alpha of managed futures: Myth or reality?," International Review of Financial Analysis, Elsevier, vol. 80(C).
    7. Fernando Henrique De Paula E Silva Mendes & Guilherme Valle Mour, 2014. "Evidências De Bull E Bear Market No Índice Bovespa: Uma Aplicação De Modelos De Regime Markoviano E Duration Dependence," Anais do XLI Encontro Nacional de Economia [Proceedings of the 41st Brazilian Economics Meeting] 138, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    8. João Cruz & João Nicolau & Paulo M. M. Rodrigues, 2021. "Structural Changes in the Duration of Bull Markets and Business Cycle Dynamics," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(3), pages 333-352, September.
    9. Kole, Erik & van Dijk, Dick, 2023. "Moments, shocks and spillovers in Markov-switching VAR models," Journal of Econometrics, Elsevier, vol. 236(2).
    10. Mahadeo, Scott M.R. & Heinlein, Reinhold & Legrenzi, Gabriella D., 2019. "Energy contagion analysis: A new perspective with application to a small petroleum economy," Energy Economics, Elsevier, vol. 80(C), pages 890-903.
    11. 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.
    12. Stephen Thiele, 2020. "Modeling the conditional distribution of financial returns with asymmetric tails," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 46-60, January.
    13. Zegadło, Piotr, 2022. "Identifying bull and bear market regimes with a robust rule-based method," Research in International Business and Finance, Elsevier, vol. 60(C).
    14. Yu, Xing & Shen, Xilin & Li, Yanyan & Gong, Xue, 2023. "Selective hedging strategies for crude oil futures based on market state expectations," Global Finance Journal, Elsevier, vol. 57(C).
    15. Mendes, Fernando Henrique de Paula e Silva & Caldeira, João Frois & Moura, Guilherme Valle, 2018. "Evidence of Bull and Bear Markets in the Bovespa index: An application of Markovian regime-switching Models with Duration Dependence," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 38(1), May.
    16. Mahadeo, Scott M.R. & Heinlein, Reinhold & Legrenzi, Gabriella D., 2022. "Contagion testing in frontier markets under alternative stressful S&P 500 market scenarios," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    17. Damir Tokic & Dave Jackson, 2023. "When a correction turns into a bear market: What explains the depth of the stock market drawdown? A discretionary global macro approach," Journal of Asset Management, Palgrave Macmillan, vol. 24(3), pages 184-197, May.
    18. Lee, Wei-Ming & Wu, Shue-Jen, 2025. "Do oil price changes contain useful predictive information about the U.S. bear stock market?," The North American Journal of Economics and Finance, Elsevier, vol. 80(C).
    19. Milad Goodarzi & Christoph Meinerding, 2025. "Asset allocation with recursive parameter updating and macroeconomic regime identifiers," The European Journal of Finance, Taylor & Francis Journals, vol. 31(9), pages 1141-1167, June.
    20. Borjigin, Sumuya & Yang, Yating & Yang, Xiaoguang & Sun, Leilei, 2018. "Econometric testing on linear and nonlinear dynamic relation between stock prices and macroeconomy in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 107-115.
    21. Hanna, Alan J., 2018. "A top-down approach to identifying bull and bear market states," International Review of Financial Analysis, Elsevier, vol. 55(C), pages 93-110.

    More about this item

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G3 - Financial Economics - - Corporate Finance and Governance
    • M00 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - General - - - General

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