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Analyzing the Time between Trades with a Gamma Compounded Hazard Model. An Application to LIFFE Bund Future Transactions

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  • Nikolaus Hautsch

    (Center of Finance and Econometrics)

Abstract

This paper investigates the time between transactions on financial markets. It is assumed that the interval between transactions is a random variable and the relationship between the probability to observe a transaction at each instant of time and the type of the previous trade is investigated. To estimate these effects, a semiparametric proportional hazard model is used which is based on approaches proposed by Han and Hausman (1990) and Meyer (1990). Considering grouped durations the log-likelihood is formed by using differences in the survivor function. Hence, the model corresponds to an ordered response approach whereby the baseline hazard is estimated simultaneously with the coefficients of the covariates and is calculated by the thresholds. Clustering of the durations is taken into account by including lagged durations. A test is proposed to check for serial correlation in the errors based on the concept of generalized residuals along the lines of the work of Gourieroux, Monfort and Trognon (1987). Unobservable heterogeneity is implemented parametrically by a gamma distributed random variable entering the hazard function. It is shown that the resulting compounded model follows a BurrII form. In an empirical analysis high frequency intraday transaction data from the London International Financial Futures and Options Exchange (LIFFE) is investigated.

Suggested Citation

  • Nikolaus Hautsch, 1999. "Analyzing the Time between Trades with a Gamma Compounded Hazard Model. An Application to LIFFE Bund Future Transactions," Finance 9904002, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpfi:9904002
    Note: 32 pages
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    References listed on IDEAS

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    Cited by:

    1. Bidisha Chakrabarty & Zhaohui Han & Konstantin Tyurin & Xiaoyong Zheng, 2006. "A Competing Risk Analysis of Executions and Cancellations in a Limit Order Market," CAEPR Working Papers 2006-015, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    2. Gerhard, Frank & Hautsch, Nikolaus, 2002. "Volatility estimation on the basis of price intensities," Journal of Empirical Finance, Elsevier, vol. 9(1), pages 57-89, January.
    3. Hautsch, Nikolaus, 2002. "Modelling Intraday Trading Activity Using Box-Cox-ACD Models," CoFE Discussion Papers 02/05, University of Konstanz, Center of Finance and Econometrics (CoFE).
    4. Gerhard, Frank & Hautsch, Nikolaus, 2000. "Determinants of Inter-Trade Durations and Hazard Rates Using Proportional Hazard ARMA Model," CoFE Discussion Papers 00/20, University of Konstanz, Center of Finance and Econometrics (CoFE).
    5. P. Gagliardini & C. Gourieroux, 2008. "Duration time‐series models with proportional hazard," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(1), pages 74-124, January.

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    More about this item

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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