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Discretized time and conditional duration modelling for stock transaction data
Umeå University, Faculty of Social Sciences, Department of Economics.
Umeå University, Faculty of Social Sciences, Department of Economics.
2007 (English)In: Applied Financial Economics, ISSN 0960-3107, E-ISSN 1466-4305, Vol. 17, 647-658 p.Article in journal (Refereed) Published
Abstract [en]

This article 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 for intra-day duration models. 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 that do not. Empirical results are reported for trading durations in Ericsson B at Stockholmsbörsen for a 3-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.

Place, publisher, year, edition, pages
Routledge, Taylor & Francis Group , 2007. Vol. 17, 647-658 p.
Keyword [en]
Economics, Macroeconomics
National Category
Economics
Research subject
Econometrics; Econometrics
Identifiers
URN: urn:nbn:se:umu:diva-5233DOI: 10.1080/09603100600690044OAI: oai:DiVA.org:umu-5233DiVA: diva2:144684
Available from: 2006-08-30 Created: 2006-08-30 Last updated: 2017-12-14Bibliographically approved
In thesis
1. Stock data, trade durations, and limit order book information
Open this publication in new window or tab >>Stock data, trade durations, and limit order book information
2006 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis comprises four papers concerning trade durations and limit order book information. Paper [1], [2] and [4] study trader durations, e.g., the time between stock transactions in intra-day data. Paper [3] focus on the information content in the limit order book concerning future price movements in stock transaction data.

Paper [1] 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 for intraday duration models. 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. Empirically, 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.

Paper [2] considers an extension of the univariate autoregressive conditional duration model to which durations from a second stock are added. The model is empirically used to study duration dependence in four traded stocks, Nordea, Föreningssparbanken, Handelsbanken and SEB A on the Stockholm Stock Exchange. The stocks are all active in the banking sector. It is found that including durations from a second stock may add explanatory power to the univariate model. We also find that spread changes have significant effect for all series.

Paper [3] empirically tests whether an open limit order book contains information about future short-run stock price movements. To account for the discrete nature of price changes, the integer-valued autoregressive model of order one is utilized. A model transformation has an advantage over conventional count data approaches since it handles negative integer-valued price changes. The empirical results reveal that measures capturing offered quantities of a share at the best bid- and ask-price reveal more information about future short-run price movements than measures capturing the quantities offered at prices below and above. Imbalance and changes in offered quantities at prices below and above the best bid- and askprice do, however, have a small and significant effect on future price changes. The results also indicate that the value of order book information is short-term.

Paper [4] This paper studies the impact of news announcements on trade durations in stocks on the Stockholm Stock Exchange. The news are categorized into four groups and the impact on the time between transactions is studied. Times before, during and after the news release are considered. Econometrically, the impact is studied within an autoregressive conditional duration model using intradaily data for six stocks. The empirical results reveal that news reduces the duration lengths before, during and after news releases as expected by the theoretical litterature on durations and information flow.

Place, publisher, year, edition, pages
Umeå: Nationalekonomi, 2006. 16 p.
Series
Umeå economic studies, ISSN 0348-1018 ; 689
Keyword
Finance, Maximum likelihood, Estimation, ACD, News, Multivariate, Intraday, Market
National Category
Economics
Identifiers
urn:nbn:se:umu:diva-839 (URN)91-7264-142-8 (ISBN)
Public defence
2006-09-22, Naturvetarhuset, N200, Umeå universitet, Umeå, 10:15 (English)
Opponent
Supervisors
Available from: 2006-08-30 Created: 2006-08-30 Last updated: 2010-02-04Bibliographically approved

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  • de-DE
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