Discretized Time and Conditional Duration Modelling for Stock Transaction Data

Kurt Brännäs () and Ola Simonsen ()
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Ola Simonsen: Department of Economics, Umeå University, Postal: S 901 87 Umeå, Sweden

No 610, Umeå Economic Studies from Umeå University, Department of Economics

Abstract: The paper considers conditional duration models in which durations are in continuous time but measured in grouped or discretized form. This feature of recorded durations in combination with a frequently traded stock is expected to negatively influence the performance of conventional estimators. A few estimators that account for the discreteness are discussed and compared in a Monte Carlo experiment. An EM-algorithm accounting for the discrete data performs better than those which do not. Empirical results are reported for trading durations in Ericsson B at Stockholmsbörsen for a three-week period of July 2002. The incorporation of level variables for past trading is rejected in favour of change variables. This enables an interpretation in terms of news effects. No evidence of asymmetric responses to news about prices and spreads is found.

Keywords: Grouped data; Maximum likelihood; EM-algorithm; Estimation; Finance; News (search for similar items in EconPapers)
JEL-codes: C12 C22 C41 C51 G12 G14 (search for similar items in EconPapers)
Pages: 28 pages
Date: 2003-05-20
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (2)

Published in Applied Financial Economics, 2007, pages 647-658.

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Journal Article: Discretized time and conditional duration modelling for stock transaction data (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:hhs:umnees:0610

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