Asset returns and volatility clustering in financial time series
AbstractAn 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by arXiv.org in its series Papers with number 1002.0284.
Date of creation: Feb 2010
Date of revision: Apr 2011
Publication status: Published in Physica A 390, 1300 - 1314 (2011)
Contact details of provider:
Web page: http://arxiv.org/
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-02-13 (All new papers)
- NEP-ECM-2010-02-13 (Econometrics)
- NEP-FMK-2010-02-13 (Financial Markets)
- NEP-MST-2010-02-13 (Market Microstructure)
- NEP-RMG-2010-02-13 (Risk Management)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- 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.
- 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.
- 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.
- 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.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (arXiv administrators).
If references are entirely missing, you can add them using this form.