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Detecting jumps and regime-switches in international stock markets returns

Author

Listed:
  • Julien Chevallier

    (EconomiX - EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

  • Stéphane Goutte

    (BF - Banque-Finance - LED - Laboratoire d'Economie Dionysien - UP8 - Université Paris 8 Vincennes-Saint-Denis)

Abstract

This paper explores seven international stock markets (DJIA, Euro STOXX 600, Russell 2000, Nikkei, NASDAQ, FTSE, Global Dow) in the quest for jumps and regime-switches. The methodological framework borrows from the Markov-switching approach and the stochastic modelling literature based on Lévy processes. The econometric procedure is detailed in a two-step fashion. The dataset covers the period from June 2004 to July 2014. The main results uncover changing market dynamics according to economic and/or financial phenomena (e.g., economic crises/growth, news events) with the occurrence of several episodes characterized by a high jump intensity. We advocate the use of such a jump-robust model modulated by a Markov chain to further study the dependence structure of financial time series.

Suggested Citation

  • Julien Chevallier & Stéphane Goutte, 2014. "Detecting jumps and regime-switches in international stock markets returns," Working Papers hal-01090833, HAL.
    • Handle: RePEc:hal:wpaper:hal-01090833
    Note: View the original document on HAL open archive server: https://hal.science/hal-01090833
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    References listed on IDEAS

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    1. Stéphane Goutte & Benteng Zou, 2012. "Continuous time regime switching model applied to foreign exchange rate," Working Papers hal-00643900, HAL.
    2. Ang, Andrew & Bekaert, Geert, 2002. "Regime Switches in Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 163-182, April.
    3. 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 357-384, March.
    4. Goutte, Stéphane, 2014. "Conditional Markov regime switching model applied to economic modelling," Economic Modelling, Elsevier, vol. 38(C), pages 258-269.
    5. Chernov, Mikhail & Ronald Gallant, A. & Ghysels, Eric & Tauchen, George, 2003. "Alternative models for stock price dynamics," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 225-257.
    6. Bjørn Eraker, 2004. "Do Stock Prices and Volatility Jump? Reconciling Evidence from Spot and Option Prices," Journal of Finance, American Finance Association, vol. 59(3), pages 1367-1404, June.
    7. James D. Hamilton & Baldev Raj, 2002. "New directions in business cycle research and financial analysis," Empirical Economics, Springer, vol. 27(2), pages 149-162.
    8. Julien Chevallier & Florian Ielpo, 2014. "Twenty years of jumps in commodity markets," International Review of Applied Economics, Taylor & Francis Journals, vol. 28(1), pages 64-82, January.
    9. Torben G. Andersen & Luca Benzoni & Jesper Lund, 2002. "An Empirical Investigation of Continuous‐Time Equity Return Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1239-1284, June.
    10. Bjørn Eraker & Michael Johannes & Nicholas Polson, 2003. "The Impact of Jumps in Volatility and Returns," Journal of Finance, American Finance Association, vol. 58(3), pages 1269-1300, June.
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    Cited by:

    1. Asante Gyamerah, Samuel & Ngare, Philip & Ikpe, Dennis, 2018. "A Levy Regime-Switching Temperature Dynamics Model for Weather Derivatives," MPRA Paper 89680, University Library of Munich, Germany, revised 10 Jul 2018.
    2. Donatien Hainaut & Franck Moraux, 2019. "A switching self-exciting jump diffusion process for stock prices," Annals of Finance, Springer, vol. 15(2), pages 267-306, June.
    3. Samuel Asante Gyamerah & Philip Ngare & Dennis Ikpe, 2018. "Regime-Switching Temperature Dynamics Model for Weather Derivatives," International Journal of Stochastic Analysis, Hindawi, vol. 2018, pages 1-15, July.
    4. Andrea Bucci & Vito Ciciretti, 2021. "Market Regime Detection via Realized Covariances: A Comparison between Unsupervised Learning and Nonlinear Models," Papers 2104.03667, arXiv.org.
    5. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019. "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, vol. 213(2), pages 493-515.

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