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Understanding the source of multifractality in financial markets

  • Jozef Barunik
  • Tomaso Aste
  • Tiziana Di Matteo
  • Ruipeng Liu

In this paper, we use the generalized Hurst exponent approach to study the multi- scaling behavior of different financial time series. We show that this approach is robust and powerful in detecting different types of multiscaling. We observe a puzzling phenomenon where an apparent increase in multifractality is measured in time series generated from shuffled returns, where all time-correlations are destroyed, while the return distributions are conserved. This effect is robust and it is reproduced in several real financial data including stock market indices, exchange rates and interest rates. In order to understand the origin of this effect we investigate different simulated time series by means of the Markov switching multifractal (MSM) model, autoregressive fractionally integrated moving average (ARFIMA) processes with stable innovations, fractional Brownian motion and Levy flights. Overall we conclude that the multifractality observed in financial time series is mainly a consequence of the characteristic fat-tailed distribution of the returns and time-correlations have the effect to decrease the measured multifractality.

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File URL: http://arxiv.org/pdf/1201.1535
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Paper provided by arXiv.org in its series Papers with number 1201.1535.

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Date of creation: Jan 2012
Date of revision: Jan 2012
Publication status: Published in Physica A, 391 (17), pp. 4234-4251 (2012)
Handle: RePEc:arx:papers:1201.1535
Contact details of provider: Web page: http://arxiv.org/

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