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Modelling financial time series using multifractal random walks

Author

Listed:
  • Bacry, E.
  • Delour, J.
  • Muzy, J.F.

Abstract

Multifractal random walks (MRW) correspond to simple solvable “stochastic volatility” processes. Moreover, they provide a simple interpretation of multifractal scaling laws and multiplicative cascade process paradigms in terms of volatility correlations. We show that they are able to reproduce most of the recent empirical findings concerning financial time series: no correlation between price variations, long-range volatility correlations and multifractal statistics.

Suggested Citation

  • Bacry, E. & Delour, J. & Muzy, J.F., 2001. "Modelling financial time series using multifractal random walks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 84-92.
    • Handle: RePEc:eee:phsmap:v:299:y:2001:i:1:p:84-92
    DOI: 10.1016/S0378-4371(01)00284-9
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    References listed on IDEAS

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    1. Marc-Etienne Brachet & Erik Taflin & Jean Marcel Tcheou, 1999. "Scaling transformation and probability distributions for financial time series," Papers cond-mat/9905169, arXiv.org.
    2. E. Bacry & J. Delour & J. F. Muzy, 2000. "A multivariate multifractal model for return fluctuations," Papers cond-mat/0009260, arXiv.org.
    3. Marc-Etienne BRACHET & Erik TAFLIN & Jean Marcel TCHEOU, 1999. "Scaling transformation and probability distributions for financial time series," GE, Growth, Math methods 9901003, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

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