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A Dynamic Integer Count Data Model for Financial Transaction Prices

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  • Pohlmeier, Winfried
  • Liesenfeld, Roman

Abstract

In this paper we develop a dynamic model for integer counts to capture the dis- creteness of price changes for financial transaction prices. Our model rests on an autoregressive multinomial component for the direction of the price change and a dynamic count data component for the size of the price changes. Since the model is capable of capturing a wide range of discrete price movements it is particularly suited for financial markets where the trading intensity is moderate or low as for most European exchanges. We present the model at work by applying it to transaction data of the Henkel share traded at the Frankfurt stock exchange over a period of 6 months. In particular, we use the model to test some theoretical implications of the market microstructure theory on the relationship between price movements and other marks of the trading process.

Suggested Citation

  • Pohlmeier, Winfried & Liesenfeld, Roman, 2003. "A Dynamic Integer Count Data Model for Financial Transaction Prices," CoFE Discussion Papers 03/03, University of Konstanz, Center of Finance and Econometrics (CoFE).
    • Handle: RePEc:zbw:cofedp:0303
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    References listed on IDEAS

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    6. Russell, Jeffrey & Engle, Robert F, 1998. "Econometric Analysis of Discrete-Valued Irregularly-Spaced Financial Transactions Data Using a New Autoregressive Conditional Multinomial Model," University of California at San Diego, Economics Working Paper Series qt00m2c5hk, Department of Economics, UC San Diego.
    7. Mullahy, John, 1986. "Specification and testing of some modified count data models," Journal of Econometrics, Elsevier, vol. 33(3), pages 341-365, December.
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    11. Winfried Pohlmeier & Volker Ulrich, 1995. "An Econometric Model of the Two-Part Decisionmaking Process in the Demand for Health Care," Journal of Human Resources, University of Wisconsin Press, vol. 30(2), pages 339-361.
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    Cited by:

    1. Drescher, Daniel, 2005. "Alternative distributions for observation driven count series models," Economics Working Papers 2005-11, Christian-Albrechts-University of Kiel, Department of Economics.
    2. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Australasian Meetings 272, Econometric Society.
    3. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Far Eastern Meetings 730, Econometric Society.

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    More about this item

    Keywords

    Autoregressive conditional multinomial model; GLARMA; transaction prices; count data; market microstructure;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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