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True and Apparent Scaling: The Proximity of the Markov-Switching Multifractal Model to Long-Range Dependence

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  • Ruipeng Liu
  • T. Di Matteo
  • Thomas Lux

Abstract

In this paper, we consider daily financial data of a collection of different stock market indices, exchange rates, and interest rates, and we analyze their multi-scaling properties by estimating a simple specification of the Markov-switching multifractal model (MSM). In order to see how well the estimated models capture the temporal dependence of the data, we estimate and compare the scaling exponents $H(q)$ (for $q = 1, 2$) for both empirical data and simulated data of the estimated MSM models. In most cases the multifractal model appears to generate `apparent' long memory in agreement with the empirical scaling laws.

Suggested Citation

  • Ruipeng Liu & T. Di Matteo & Thomas Lux, 2007. "True and Apparent Scaling: The Proximity of the Markov-Switching Multifractal Model to Long-Range Dependence," Papers 0704.1338, arXiv.org.
    • Handle: RePEc:arx:papers:0704.1338
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    References listed on IDEAS

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    1. Calvet, Laurent & Fisher, Adlai, 2001. "Forecasting multifractal volatility," Journal of Econometrics, Elsevier, vol. 105(1), pages 27-58, November.
    2. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    3. Gençay, Ramazan & Dacorogna, Michel & Muller, Ulrich A. & Pictet, Olivier & Olsen, Richard, 2001. "An Introduction to High-Frequency Finance," Elsevier Monographs, Elsevier, edition 1, number 9780122796715.
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