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The Number of Regimes Across Asset Returns: Identification and Economic Value

Author

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  • Mathieu Gatumel

    (CERAG - Centre d'études et de recherches appliquées à la gestion - UPMF - Université Pierre Mendès France - Grenoble 2 - CNRS - Centre National de la Recherche Scientifique)

  • Florian Ielpo

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, Pictet Asset Management - Pictet Asset Management)

Abstract

A shared belief in the financial industry is that markets are driven by two types of regimes. Bull markets would be characterized by high returns and low volatility whereas bear markets would display low returns coupled with high volatility. Modeling the dynam- ics of different asset classes (stocks, bonds, commodities and currencies) with a Markov- Switching model and using a density-based test, we reject the hypothesis that two regimes are enough to capture asset returns' evolutions for many of the investigated assets. Once the accuracy of our test methodology has been assessed through Monte Carlo experi- ments, our empirical results point out that between two and five regimes are required to capture the features of each asset's distribution. Moreover, we show that only a part of the underlying number of regimes is explained by the distributional characteristics of the returns such as kurtosis. A thorough out-of-sample analysis provides additional evidence that there are more than just bulls and bears in financial markets. Finally, we high- light that taking into account the real number of regimes allows both improved portfolio returns and density forecasts.

Suggested Citation

  • Mathieu Gatumel & Florian Ielpo, 2011. "The Number of Regimes Across Asset Returns: Identification and Economic Value," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00658540, HAL.
  • Handle: RePEc:hal:cesptp:halshs-00658540
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00658540
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    3. Donatien Hainaut & Yan Shen & Yan Zeng, 2016. "How do capital structure and economic regime affect fair prices of bank's equity and liabilities?," Post-Print hal-01394133, HAL.
    4. Collet, Jerome & Ielpo, Florian, 2018. "Sector spillovers in credit markets," Journal of Banking & Finance, Elsevier, vol. 94(C), pages 267-278.
    5. Hainaut, Donatien & Goutte, Stephane, 2018. "A switching microstructure model for stock prices," LIDAM Discussion Papers ISBA 2018014, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. 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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