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Long term vs. short term comovements in stock markets: the use of Markov-switching multifractal models

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Author Info
Idier, J.
Abstract

Empirical techniques to assess market comovements are numerous from cointegration to dynamic conditional correlations. This paper uses the fractal properties of asset returns and presents estimations of Markov switching multifractal models [as MSM] to give new insights about short and long run dependencies in stock returns. The main advantage of the model is to allow for the derivation of several indicators of comovements on heterogenous lasting horizons. Empirical applications are performed for four stock indices (CAC DAX FTSE NYSE) at daily frequency between 1996 and 2008.

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Publisher Info
Paper provided by Banque de France in its series Documents de Travail with number 218.

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Length: 39 pages
Date of creation: 2008
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Handle: RePEc:bfr:banfra:218

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Related research
Keywords: Multivariate volatility models ; Markov switching multifractal model transmission; comovements.;

Find related papers by JEL classification:
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
F36 - International Economics - - International Finance - - - Financial Aspects of Economic Integration
G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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  1. Masih, Rumi & Masih, Abul M. M., 2001. "Long and short term dynamic causal transmission amongst international stock markets," Journal of International Money and Finance, Elsevier, vol. 20(4), pages 563-587, August. [Downloadable!] (restricted)
  2. Calvet, Laurent E. & Fisher, Adlai J. & Thompson, Samuel B., 2006. "Volatility comovement: a multifrequency approach," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 179-215. [Downloadable!] (restricted)
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  3. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109. [Downloadable!]
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  4. Calvet, Laurent & Fisher, Adlai, 2001. "Forecasting multifractal volatility," Journal of Econometrics, Elsevier, vol. 105(1), pages 27-58, November. [Downloadable!] (restricted)
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  5. Kristin J. Forbes & Roberto Rigobon, 2002. "No Contagion, Only Interdependence: Measuring Stock Market Comovements," Journal of Finance, American Finance Association, vol. 57(5), pages 2223-2261, October. [Downloadable!] (restricted)
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  6. Benoit Mandelbrot, 1963. "The Variation of Certain Speculative Prices," Journal of Business, University of Chicago Press, vol. 36, pages 394. [Downloadable!]
  7. Jérôme Fillol, 2003. "Multifractality: Theory and Evidence an Application to the French Stock Market," Economics Bulletin, Economics Bulletin, vol. 3(31), pages 1-12. [Downloadable!]
  8. Kanas, Angelos, 1998. "Linkages between the US and European Equity Markets: Further Evidence from Cointegration Tests," Applied Financial Economics, Taylor and Francis Journals, vol. 8(6), pages 607-14, December. [Downloadable!] (restricted)
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  9. Lux, Thomas & Kaizoji, Taisei, 2006. "Forecasting volatility and volume in the Tokyo stock market : long memory, fractality and regime switching," Economics Working Papers 2006,13, Christian-Albrechts-University of Kiel, Department of Economics. [Downloadable!]
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  10. Colm Kearney & Valerio Poti, 2005. "Correlation Dynamics in European Equity Markets," Finance 0507008, EconWPA. [Downloadable!]
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  11. Jerome Fillol, 2005. "Modelisation multifractale du taux de change dollar/euro," Economie Internationale, CEPII research center, issue 4Q, pages 135-150. [Downloadable!]
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