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Contribution Details
| Type | Journal Article |
| Scope | Discipline-based scholarship |
| Title | Trading Frequency and Volatility Clustering |
| Organization Unit | |
| Authors |
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| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Journal Title | Journal of Banking and Finance |
| Publisher | Elsevier |
| Geographical Reach | international |
| ISSN | 0378-4266 |
| Volume | 36 |
| Number | 3 |
| Page Range | 760 - 773 |
| Date | 2012 |
| Abstract Text | 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. |
| Free access at | Related URL |
| Related URLs | |
| Digital Object Identifier | 10.1016/j.jbankfin.2011.09.008 |
| Other Identification Number | merlin-id:5958 |
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