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Trading frequency and volatility clustering

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  • Xue, Yi
  • Gençay, Ramazan

Abstract

Volatility clustering, with autocorrelations of the hyperbolic decay rate, is unquestionably one of the most important stylized facts of financial time series. This paper presents a market microstructure model that is able to generate volatility clustering with hyperbolically decaying autocorrelations via traders with multiple trading frequencies, using Bayesian information updates in an incomplete market. The model illustrates that signal extraction, which is induced by multiple trading frequencies, can increase the persistence of the volatility of returns. Furthermore, we show that the volatility of the underlying time series of returns varies greatly with the number of traders in the market.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Banking & Finance.

Volume (Year): 36 (2012)
Issue (Month): 3 ()
Pages: 760-773

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Handle: RePEc:eee:jbfina:v:36:y:2012:i:3:p:760-773

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Web page: http://www.elsevier.com/locate/jbf

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Keywords: Trading frequency; Volatility clustering; Signal extraction; Hyperbolic decay;

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Cited by:
  1. Yi Xue & Ramazan Gencay, 2009. "Hierarchical Information and the Rate of Information Diffusion," Working Paper Series, The Rimini Centre for Economic Analysis 29_09, The Rimini Centre for Economic Analysis, revised Jan 2009.
  2. Batten, Jonathan A. & Kinateder, Harald & Wagner, Niklas, 2014. "Multifractality and value-at-risk forecasting of exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 401(C), pages 71-81.

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