Understanding the source of multifractality in financial markets
Abstract
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.Download Info
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Paper provided by arXiv.org in its series Papers with number 1201.1535.Length:
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
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Web page: http://arxiv.org/
Related research
Keywords:Other versions of this item:
- Barunik, Jozef & Aste, Tomaso & Di Matteo, T. & Liu, Ruipeng, 2012. "Understanding the source of multifractality in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4234-4251.
- NEP-ALL-2012-01-18 (All new papers)
- NEP-ETS-2012-01-18 (Econometric Time Series)
References
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- T. Di Matteo & T. Aste & Michel M. Dacorogna, 2005.
"Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development,"
Econometrics
0503004, EconWPA.
- Matteo, T. Di & Aste, T. & Dacorogna, Michel M., 2005. "Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 827-851, April.
- T. Di Matteo & T. Aste & M. M. Dacorogna, 2004. "Long term memories of developed and emerging markets: using the scaling analysis to characterize their stage of development," Papers cond-mat/0403681, arXiv.org.
- Benoit Mandelbrot & Adlai Fisher & Laurent Calvet, 1997.
"A Multifractal Model of Asset Returns,"
Cowles Foundation Discussion Papers
1164, Cowles Foundation for Research in Economics, Yale University.
- Laurent Calvet & Adlai Fisher & Benoit Mandelbrot, 1999. "A Multifractal Model of Assets Returns," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-072, New York University, Leonard N. Stern School of Business-.
- Liu, Ruipeng & Di Matteo, T. & Lux, Thomas, 2007.
"True and apparent scaling: The proximity of the Markov-switching multifractal model to long-range dependence,"
Physica A: Statistical Mechanics and its Applications,
Elsevier, vol. 383(1), pages 35-42.
- Liu, Ruipeng & Di Matteo, Tiziana & Lux, Thomas, 2007. "True and Apparent Scaling: The Proximity of the Markov- Switching Multifractal Model to Long-Range Dependence," Economics Working Papers 2007,06, Christian-Albrechts-University of Kiel, Department of Economics.
- Thomas Lux & Di Matteo & Liu Ruipeng, 2007. "True and Apparent Scaling: The Proximity of the Markov- Switching Multifractal Model to Long-Range Dependence," Working Papers wp07-12, Warwick Business School, Financial Econometrics Research Centre.
- 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.
- Kokoszka, Piotr S. & Taqqu, Murad S., 1996. "Infinite variance stable moving averages with long memory," Journal of Econometrics, Elsevier, vol. 73(1), pages 79-99, July.
- Laurent Calvet & Adlai Fisher, 2003.
"Regime-Switching and the Estimation of Multifractal Processes,"
Harvard Institute of Economic Research Working Papers
1999, Harvard - Institute of Economic Research.
- Laurent Calvet & Adlai Fisher, 2003. "Regime-Switching and the Estimation of Multifractal Processes," NBER Working Papers 9839, National Bureau of Economic Research, Inc.
- Laurent E. Calvet, 2004. "How to Forecast Long-Run Volatility: Regime Switching and the Estimation of Multifractal Processes," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 2(1), pages 49-83.
- Benoit Mandelbrot, 1963. "The Variation of Certain Speculative Prices," The Journal of Business, University of Chicago Press, vol. 36, pages 394.
- Barunik, Jozef & Kristoufek, Ladislav, 2010.
"On Hurst exponent estimation under heavy-tailed distributions,"
Physica A: Statistical Mechanics and its Applications,
Elsevier, vol. 389(18), pages 3844-3855.
- Jozef Barunik & Ladislav Kristoufek, 2012. "On Hurst exponent estimation under heavy-tailed distributions," Papers 1201.4786, arXiv.org.
- Barunik, Jozef & Vacha, Lukas, 2010.
"Monte Carlo-based tail exponent estimator,"
Physica A: Statistical Mechanics and its Applications,
Elsevier, vol. 389(21), pages 4863-4874.
- Jozef Barunik & Lukas Vacha, 2010. "Monte Carlo-Based Tail Exponent Estimator," Working Papers IES 2010/06, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Apr 2010.
- Jozef Barunik & Lukas Vacha, 2012. "Monte Carlo-based tail exponent estimator," Papers 1201.4781, arXiv.org.
- Laurent Calvet & Adlai Fisher, 2002. "Multifractality In Asset Returns: Theory And Evidence," The Review of Economics and Statistics, MIT Press, vol. 84(3), pages 381-406, August.
- Sergio Bianchi & Augusto Pianese, 2007. "Modelling stock price movements: multifractality or multifractionality?," Quantitative Finance, Taylor and Francis Journals, vol. 7(3), pages 301-319.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Ladislav Kristoufek & Miloslav Vosvrda, 2012.
"Measuring capital market efficiency: Global and local correlations structure,"
Papers
1208.1298, arXiv.org.
- Kristoufek, Ladislav & Vosvrda, Miloslav, 2013. "Measuring capital market efficiency: Global and local correlations structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(1), pages 184-193.
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