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Asset returns and volatility clustering in financial time series

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  • Jie-Jun Tseng
  • Sai-Ping Li
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    Abstract

    An analysis of the stylized facts in financial time series is carried out. We find that, instead of the heavy tails in asset return distributions, the slow decay behaviour in autocorrelation functions of absolute returns is actually directly related to the degree of clustering of large fluctuations within the financial time series. We also introduce an index to quantitatively measure the clustering behaviour of fluctuations in these time series and show that big losses in financial markets usually lump more severely than big gains. We further give examples to demonstrate that comparing to conventional methods, our index enables one to extract more information from the financial time series.

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    File URL: http://arxiv.org/pdf/1002.0284
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    Bibliographic Info

    Paper provided by arXiv.org in its series Papers with number 1002.0284.

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    Date of creation: Feb 2010
    Date of revision: Apr 2011
    Publication status: Published in Physica A 390, 1300 - 1314 (2011)
    Handle: RePEc:arx:papers:1002.0284

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    Web page: http://arxiv.org/

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    1. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frederic Abergel, 2009. "Econophysics: Empirical facts and agent-based models," Papers 0909.1974, arXiv.org, revised Jun 2010.
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    Cited by:
    1. Chunxia, Yang & Bingying, Xia & Sen, Hu & Rui, Wang, 2012. "A study of the interplay between the structure variation and fluctuations of the Shanghai stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3198-3205.
    2. Yang, ChunXia & Hu, Sen & Xia, BingYing, 2012. "The endogenous dynamics of financial markets: Interaction and information dissemination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(12), pages 3513-3525.
    3. Ross, Gordon J., 2013. "Modelling financial volatility in the presence of abrupt changes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(2), pages 350-360.
    4. D’Urso, Pierpaolo & Cappelli, Carmela & Di Lallo, Dario & Massari, Riccardo, 2013. "Clustering of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2114-2129.

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