Trading Frequency and Volatility Clustering

61 Pages Posted: 20 Mar 2009

See all articles by Yi Xue

Yi Xue

Department of Economics, Simon Fraser University

Ramazan Gencay

Simon Fraser University

Date Written: December 20, 2008

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 hyperbolic autocorrelations through traders with multiple trading frequencies using Bayesian information updating in an incomplete market. The model illustrates that signal extraction, which is induced by multiple trading frequency, can increase the persistence of the volatility of returns. Furthermore, we show that the local temporal memory of the underlying time series of returns and their volatility varies greatly with the number of traders in the market.

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

JEL Classification: G10, G11, D43, D82

Suggested Citation

Xue, Yi and Gencay, Ramazan, Trading Frequency and Volatility Clustering (December 20, 2008). Available at SSRN: https://ssrn.com/abstract=1365705 or http://dx.doi.org/10.2139/ssrn.1365705

Yi Xue (Contact Author)

Department of Economics, Simon Fraser University ( email )

Burnaby, V5A 1S6
Canada

Ramazan Gencay

Simon Fraser University ( email )

Department of Economics
8888 University Drive
Burnaby, British Columbia V5A 1S6
Canada

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