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Levels of complexity in financial markets

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Author Info

  • Bonanno, Giovanni
  • Lillo, Fabrizio
  • Mantegna, Rosario N.

Abstract

We consider different levels of complexity which are observed in the empirical investigation of financial time series. We discuss recent empirical and theoretical work showing that statistical properties of financial time series are rather complex under several ways. Specifically, they are complex with respect to their (i) temporal and (ii) ensemble properties. Moreover, the ensemble return properties show a behavior which is specific to the nature of the trading day reflecting if it is a normal or an extreme trading day.

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File URL: http://www.sciencedirect.com/science/article/pii/S0378437101002795
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Bibliographic Info

Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

Volume (Year): 299 (2001)
Issue (Month): 1 ()
Pages: 16-27

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Handle: RePEc:eee:phsmap:v:299:y:2001:i:1:p:16-27

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Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

Related research

Keywords: Econophysics; Stochastic processes; Correlation based clustering;

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Cited by:
  1. Miśkiewicz, Janusz, 2013. "Power law classification scheme of time series correlations. On the example of G20 group," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2150-2162.
  2. Wei, Yu & Chen, Wang & Lin, Yu, 2013. "Measuring daily Value-at-Risk of SSEC index: A new approach based on multifractal analysis and extreme value theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2163-2174.
  3. Gábor Dávid Kiss & Andreász Kosztopulosz, 2012. "The impact of the crisis on the monetary autonomy of Central and Eastern European countries," Public Finance Quarterly, State Audit Office of Hungary, vol. 57(1), pages 28-52.
  4. Tanya Ara\'{u}jo & Francisco Lou\c{c}\~{a}, 2004. "Complex Behavior of Stock Markets: Processes of Synchronization and Desynchronization during Crises," Papers cond-mat/0403333, arXiv.org, revised Mar 2004.
  5. Chen, Wang & Wei, Yu & Lang, Qiaoqi & Lin, Yu & Liu, Maojuan, 2014. "Financial market volatility and contagion effect: A copula–multifractal volatility approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 398(C), pages 289-300.
  6. Hokky Situngkir & Yohanes Surya, 2005. "On Stock Market Dynamics through Ultrametricity of Minimum Spanning Tree," Macroeconomics 0505010, EconWPA.
  7. Tanya Araujo & Francisco Louçã, 2005. "The Geometry of Crashes - A Measure of the Dynamics of Stock Market Crises," Working Papers Department of Economics 2005/15, ISEG - School of Economics and Management, Department of Economics, University of Lisbon.
  8. Bertrand M. Roehner, 2004. "Stock markets are not what we think they are: the key roles of cross-ownership and corporate treasury stock," Papers cond-mat/0406704, arXiv.org.
  9. Tanya Ara\'{u}jo & Francisco Lou\c{c}\~{a}, 2005. "The Geometry of Crashes - A Measure of the Dynamics of Stock Market Crises," Papers physics/0506137, arXiv.org, revised Jul 2005.
  10. Brida, Juan Gabriel & Risso, Wiston Adrián, 2008. "Multidimensional minimal spanning tree: The Dow Jones case," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5205-5210.
  11. Andreia Dionisio & Rui Menezes & Diana A. Mendes, 2003. "Mutual information: a dependence measure for nonlinear time series," Econometrics 0311003, EconWPA.
  12. Anna CZAPKIEWICZ & Pawel MAJDOSZ, 2014. "Grouping Stock Markets with Time-Varying Copula-GARCH Model," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(2), pages 144-159, March.
  13. Sandoval, Leonidas & Franca, Italo De Paula, 2012. "Correlation of financial markets in times of crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 187-208.
  14. Matesanz, David & Ortega, Guillermo J., 2008. "Network analysis of exchange data: Interdependence drives crisis contagion," MPRA Paper 7720, University Library of Munich, Germany.
  15. Goswami, B. & Ambika, G. & Marwan, N. & Kurths, J., 2012. "On interrelations of recurrences and connectivity trends between stock indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(18), pages 4364-4376.

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