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Detecting jumps and regime switches in international stock markets returns

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  • Julien Chevallier
  • St�phane Goutte

Abstract

This article explores seven international stock markets (DJIA, Euro STOXX 600, Russell 2000, Nikkei, NASDAQ, FTSE and 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 L�vy processes. The econometric procedure is detailed in a two-step fashion. The data set 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 & St�phane Goutte, 2015. "Detecting jumps and regime switches in international stock markets returns," Applied Economics Letters, Taylor & Francis Journals, vol. 22(13), pages 1011-1019, September.
  • Handle: RePEc:taf:apeclt:v:22:y:2015:i:13:p:1011-1019
    DOI: 10.1080/13504851.2014.995356
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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.
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    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.
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    Cited by:

    1. 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.
    2. Andrea Bucci & Vito Ciciretti, 2021. "Market Regime Detection via Realized Covariances: A Comparison between Unsupervised Learning and Nonlinear Models," Papers 2104.03667, arXiv.org.
    3. 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.
    4. 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.
    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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