Trading Frequency and Volatility Clustering

Yi Xue () and Ramazan Gencay

Working Paper series from Rimini Centre for Economic Analysis

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 varies with the number of traders in the market.

Keywords: Trading frequency; Volatility clustering; Signal extraction; Hyperbolic decay (search for similar items in EconPapers)
JEL-codes: D43 D82 G10 G11 (search for similar items in EconPapers)
Date: 2009-01
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Journal Article: Trading frequency and volatility clustering (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:rim:rimwps:31_09

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