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Econometric Analysis of Financial Transaction Data: Pitfalls and Opportunities

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Author Info
Nikolaus Hautsch () (Center of Finance and Econometrics)
Winfried Pohlmeier () (Center of Finance and Econometrics)

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Abstract

The recent availability of large data sets covering single transactions on financial markets has created a new branch of econometrics which has opened up a new door of looking at the microstructure of financial markets and its dynamics. The specific nature of transaction data such as the randomness of arrival times of trades, the discreteness of price jumps and significant intraday seasonalities, call for specific econometric tools combining both time series techniques as well as microeconomtric techniques arising from discrete choice analysis. This paper serves as an introduction to the econometrics of transaction data. We survey the state of the art and discuss its pitfalls and opportunities. Special emphasis is given to the analysis of the properties of data from various assets and trading mechanisms. We show that some characteristics of the transaction price process such as the dynamics of intertrade durations are quite similar across various assets with different liquidity and regardless whether an asset is traded electronically or on the floor. However, the analysis of other characteristics of transaction prices process such as volatility requires a careful choice of the appropriate econometric tool. Empirical evidence is presented using examples from stocks traded electronically and on the floor at the German Stock exchange and from BUND future trading at the LIFFE and the EUREX.

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Publisher Info
Paper provided by Center of Finance and Econometrics, University of Konstanz in its series CoFE Discussion Paper with number 01-05.

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Length: 37 Pages
Date of creation: Jun 2001
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Handle: RePEc:knz:cofedp:0105

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. BAUWENS, Luc & VEREDAS, David, 1999. "The stochastic conditional duration model: a latent factor model for the analysis of financial durations," CORE Discussion Papers 1999058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE). [Downloadable!]
  2. Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
  3. VEREDAS, David & RODRIGUEZ, Juan & ESPASA, Antoni, 2002. "On the (intradaily) seasonality and dynamics of a financial point process: a semiparametric approach," CORE Discussion Papers 2002023, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE). [Downloadable!]
    Other versions:
  4. Ederington, Louis H. & Lee, Jae Ha, 1995. "The Short-Run Dynamics of the Price Adjustment to New Information," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 30(01), pages 117-134, March. [Downloadable!]
  5. Grammig, Joachim & Wellner, Marc, 2002. "Modeling the interdependence of volatility and inter-transaction duration processes," Journal of Econometrics, Elsevier, vol. 106(2), pages 369-400, February. [Downloadable!] (restricted)
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  6. Alfonso Dufour & Robert F Engle, 2000. "The ACD Model: Predictability of the Time Between Concecutive Trades," ICMA Centre Discussion Papers in Finance icma-dp2000-05, Henley Business School, Reading University. [Downloadable!]
  7. Foster, F Douglas & Viswanathan, S, 1993. " Variations in Trading Volume, Return Volatility, and Trading Costs: Evidence on Recent Price Formation Models," Journal of Finance, American Finance Association, vol. 48(1), pages 187-211, March. [Downloadable!] (restricted)
  8. Diamond, Douglas W. & Verrecchia, Robert E., 1987. "Constraints on short-selling and asset price adjustment to private information," Journal of Financial Economics, Elsevier, vol. 18(2), pages 277-311, June. [Downloadable!] (restricted)
  9. Robert F. Engle, 1996. "The Econometrics of Ultra-High Frequency Data," NBER Working Papers 5816, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  10. Bollerslev, Tim & Melvin, Michael, 1994. "Bid--ask spreads and volatility in the foreign exchange market : An empirical analysis," Journal of International Economics, Elsevier, vol. 36(3-4), pages 355-372, May. [Downloadable!] (restricted)
  11. Gallant, A. Ronald, 1981. "On the bias in flexible functional forms and an essentially unbiased form : The fourier flexible form," Journal of Econometrics, Elsevier, vol. 15(2), pages 211-245, February. [Downloadable!] (restricted)
  12. Easley, David & O'Hara, Maureen, 1992. " Time and the Process of Security Price Adjustment," Journal of Finance, American Finance Association, vol. 47(2), pages 576-605, June.
  13. Joachim Grammig & Kai-Oliver Maurer, 2000. "Non-monotonic hazard functions and the autoregressive conditional duration model," Econometrics Journal, Royal Economic Society, vol. 3(1), pages 16-38.
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  14. Gourieroux, Christian & Jasiak, Joanna & Le Fol, Gaelle, 1999. "Intra-day market activity," Journal of Financial Markets, Elsevier, vol. 2(3), pages 193-226, August. [Downloadable!] (restricted)
  15. Frank Gerhard & Nikolaus Hautsch, 2000. "Determinants of Inter-Trade Durations and Hazard Rates Using Proportional Hazard ARMA Model," CoFE Discussion Paper 00-20, Center of Finance and Econometrics, University of Konstanz. [Downloadable!]
  16. Hausman, Jerry A. & Lo, Andrew W. & MacKinlay, A. Craig, 1992. "An ordered probit analysis of transaction stock prices," Journal of Financial Economics, Elsevier, vol. 31(3), pages 319-379, June. [Downloadable!] (restricted)
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  17. Easley, David & Kiefer, Nicholas M & O'Hara, Maureen, 1997. "One Day in the Life of a Very Common Stock," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 10(3), pages 805-35.
  18. Ball, Clifford A, 1988. " Estimation Bias Induced by Discrete Security Prices," Journal of Finance, American Finance Association, vol. 43(4), pages 841-65, September. [Downloadable!] (restricted)
  19. Joann Jasiak, 1996. "Persistence in Intertrade Durations," Working Papers 1999_8, York University, Department of Economics, revised Mar 1999. [Downloadable!]
  20. Feike C. Drost & Bas J. M. Werker, 2000. "Efficient Estimation in Semiparametric Time Series: the ACD Model," Econometric Society World Congress 2000 Contributed Papers 0836, Econometric Society. [Downloadable!]
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Far Eastern Meetings 730, Econometric Society. [Downloadable!]
  2. Chris M. Strickland & Catherine S. Forbes & Gael M. Martin, 2003. "Bayesian Analysis of the Stochastic Conditional Duration Model," Monash Econometrics and Business Statistics Working Papers 14/03, Monash University, Department of Econometrics and Business Statistics. [Downloadable!]
    Other versions:
  3. Hellström, Jörgen & Simonsen, Ola, 2006. "Does the Open Limit Order Book Reveal Information About Short-run Stock Price Movements?," UmeÃ¥ Economic Studies 687, Umeå University, Department of Economics. [Downloadable!]
  4. Winfried Pohlmeier & Roman Liesenfeld, 2003. "A Dynamic Integer Count Data Model for Financial Transaction Prices," CoFE Discussion Paper 03-03, Center of Finance and Econometrics, University of Konstanz. [Downloadable!]
  5. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Australasian Meetings 272, Econometric Society. [Downloadable!]
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