IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Modelling Financial High Frequency Data Using Point Processes

  • Luc Bauwens
  • Nikolaus Hautsch

In this paper, we give an overview of the state-of-the-art in the econometric literature on the modeling of so-called financial point processes. The latter are associated with the random arrival of specific financial trading events, such as transactions, quote updates, limit orders or price changes observable based on financial high-frequency data. After discussing fundamental statistical concepts of point process theory, we review durationbased and intensity-based models of financial point processes. Whereas duration-based approaches are mostly preferable for univariate time series, intensity-based models provide powerful frameworks to model multivariate point processes in continuous time. We illustrate the most important properties of the individual models and discuss major empirical applications.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2007-066.pdf
Download Restriction: no

Paper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2007-066.

as
in new window

Length: 35 pages
Date of creation: Nov 2007
Date of revision:
Handle: RePEc:hum:wpaper:sfb649dp2007-066
Contact details of provider: Postal: Spandauer Str. 1,10178 Berlin
Phone: +49-30-2093-5708
Fax: +49-30-2093-5617
Web page: http://sfb649.wiwi.hu-berlin.de
Email:


More information through EDIRC

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.:

as in new window
  1. Siem Jan Koopman & Andr� Lucas & Andr� Monteiro, 2005. "The Multi-State Latent Factor Intensity Model for Credit Rating Transitions," Tinbergen Institute Discussion Papers 05-071/4, Tinbergen Institute, revised 04 Jul 2005.
  2. BAUWENS, Luc & VEREDAS, David, . "The stochastic conditional duration model: a latent variable model for the analysis of financial durations," CORE Discussion Papers RP 1688, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  3. Nikolaus Hautsch, 2003. "Assessing the Risk of Liquidity Suppliers on the Basis of Excess Demand Intensities," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 1(2), pages 189-215.
  4. Engle, Robert F & Lunde, Asger, 1998. "Trades and Quotes: A Bivariate Point Process," University of California at San Diego, Economics Working Paper Series qt8bh079sq, Department of Economics, UC San Diego.
  5. Luc Bauwens & Arie Preminger & Jeroen V.K. Rombouts, 2006. "Regime switching GARCH models," Cahiers de recherche 06-08, HEC Montréal, Institut d'économie appliquée.
  6. Mika Meitz & Pentti Saikkonen, 2007. "Ergodicity, mixing, and existence of moments of a class of Markov models with applications to GARCH and ACD models," Economics Series Working Papers 327, University of Oxford, Department of Economics.
  7. Christian M. Hafner, 2000. "Durations, Volume and the Prediction of Financial Returns in Transaction Time," Econometric Society World Congress 2000 Contributed Papers 0599, Econometric Society.
  8. 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.
  9. Fernandes, Marcelo & Grammig, Joachim, 2006. "A family of autoregressive conditional duration models," Journal of Econometrics, Elsevier, vol. 130(1), pages 1-23, January.
  10. Yacine Ait-Sahalia, 1995. "Testing Continuous-Time Models of the Spot Interest Rate," NBER Working Papers 5346, National Bureau of Economic Research, Inc.
  11. Eric Ghysels & Christian Gourieroux & Joanna Jasiak, 1997. "Stochastic Volatility Duration Models," Working Papers 97-46, Centre de Recherche en Economie et Statistique.
  12. Meitz, Mika & Terasvirta, Timo, 2006. "Evaluating Models of Autoregressive Conditional Duration," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 104-124, January.
  13. Luc Bauwens & Nikolaus Hautsch, 2006. "Stochastic Conditional Intensity Processes," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(3), pages 450-493.
  14. Bowsher, Clive G., 2007. "Modelling security market events in continuous time: Intensity based, multivariate point process models," Journal of Econometrics, Elsevier, vol. 141(2), pages 876-912, December.
  15. 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.
  16. Meddahi, N. & Renault, E. & Werker, B.J.M., 2003. "GARCH and Irregularly Spaced Data," Discussion Paper 2003-27, Tilburg University, Center for Economic Research.
  17. BAUWENS, Luc & ROMBOUTS, Jeroen V.K., . "Econometrics," CORE Discussion Papers RP 1713, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Rombouts, Jeroen V. K. & Bauwens, Luc, 2004. "Econometrics," Papers 2004,33, Humboldt-Universität Berlin, Center for Applied Statistics and Economics (CASE).
  18. Giovanni De Luca & Paola Zuccolotto, 2003. "Finite and infinite mixtures for financial durations," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 431-455.
  19. Luc Bauwens & Pierre Giot & Joachim Grammig & David Veredas, 2000. "A Comparison of Financial Duration Models via Density Forecasts," Econometric Society World Congress 2000 Contributed Papers 0810, Econometric Society.
  20. Anthony Hall & Nikolaus Hautsch, 2006. "Order aggressiveness and order book dynamics," Empirical Economics, Springer, vol. 30(4), pages 973-1005, January.
  21. Heinen, Andreas & Rengifo, Erick, 2007. "Multivariate autoregressive modeling of time series count data using copulas," Journal of Empirical Finance, Elsevier, vol. 14(4), pages 564-583, September.
  22. Robert F. Engle & Victor K. Ng, 1991. "Measuring and Testing the Impact of News on Volatility," NBER Working Papers 3681, National Bureau of Economic Research, Inc.
  23. Joann Jasiak, 1996. "Persistence in Intertrade Durations," Working Papers 1999_8, York University, Department of Economics, revised Mar 1999.
  24. Frank Gerhard & Nikolaus Hautsch, 1999. "Volatility Estimation on the Basis of Price Intensities," CoFE Discussion Paper 99-19, Center of Finance and Econometrics, University of Konstanz.
  25. Luc Bauwens & David Veredas, 2004. "The stochastic conditional duration model: a latent factor model for the analysis of financial durations," ULB Institutional Repository 2013/136234, ULB -- Universite Libre de Bruxelles.
  26. Roman Liesenfeld & Ingmar Nolte & Winfried Pohlmeier, 2006. "Modelling financial transaction price movements: a dynamic integer count data model," Empirical Economics, Springer, vol. 30(4), pages 795-825, January.
  27. James D. Hamilton & Oscar Jorda, 2002. "A Model of the Federal Funds Rate Target," Journal of Political Economy, University of Chicago Press, vol. 110(5), pages 1135-1167, October.
  28. Drost, F.C. & Werker, B.J.M., 2001. "Semiparametric Duration Models," Discussion Paper 2001-11, Tilburg University, Center for Economic Research.
  29. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
  30. Carrasco, Marine & Chen, Xiaohong, 2002. "Mixing And Moment Properties Of Various Garch And Stochastic Volatility Models," Econometric Theory, Cambridge University Press, vol. 18(01), pages 17-39, February.
  31. Giovanni Luca & Giampiero Gallo, 2009. "Time-Varying Mixing Weights in Mixture Autoregressive Conditional Duration Models," Econometric Reviews, Taylor & Francis Journals, vol. 28(1-3), pages 102-120.
  32. Fernandes, M. & Grammig, J., 2000. "Non-Parametric Specification Tests for Conditional Duration Models," Economics Working Papers eco2000/4, European University Institute.
  33. Dionne, Georges & Duchesne, Pierre & Pacurar, Maria, 2009. "Intraday Value at Risk (IVaR) using tick-by-tick data with application to the Toronto Stock Exchange," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 777-792, December.
  34. John Knight & Cathy Q. Ning, 2008. "Estimation of the stochastic conditional duration model via alternative methods," Econometrics Journal, Royal Economic Society, vol. 11(3), pages 593-616, November.
  35. BAUWENS, Luc & GIOT, Pierre, . "Asymmetric ACD models: Introducing price information in ACD models," CORE Discussion Papers RP 1670, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  36. Ghysels Eric & Jasiak Joanna, 1998. "GARCH for Irregularly Spaced Financial Data: The ACD-GARCH Model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 2(4), pages 1-19, January.
  37. repec:att:wimass:9520 is not listed on IDEAS
  38. Large, Jeremy, 2007. "Measuring the resiliency of an electronic limit order book," Journal of Financial Markets, Elsevier, vol. 10(1), pages 1-25, February.
  39. Pierre Giot, 2005. "Market risk models for intraday data," The European Journal of Finance, Taylor & Francis Journals, vol. 11(4), pages 309-324.
  40. De Luca Giovanni & Gallo Giampiero M., 2004. "Mixture Processes for Financial Intradaily Durations," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(2), pages 1-20, May.
  41. Han, Aaron & Hausman, Jerry A, 1990. "Flexible Parametric Estimation of Duration and Competing Risk Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(1), pages 1-28, January-M.
  42. Robert Engle, 2002. "New frontiers for arch models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 425-446.
  43. Drost, F.C. & Werker, B.J.M., 2004. "Semiparametric duration models," Other publications TiSEM a1895e3e-f720-454b-9613-f, Tilburg University, School of Economics and Management.
  44. Hall, Anthony D. & Hautsch, Nikolaus, 2007. "Modelling the buy and sell intensity in a limit order book market," Journal of Financial Markets, Elsevier, vol. 10(3), pages 249-286, August.
  45. Kiefer, Nicholas M, 1988. "Economic Duration Data and Hazard Functions," Journal of Economic Literature, American Economic Association, vol. 26(2), pages 646-79, June.
  46. Jan Henneke & Svetlozar Rachev & Frank Fabozzi & Metodi Nikolov, 2011. "MCMC-based estimation of Markov Switching ARMA-GARCH models," Applied Economics, Taylor & Francis Journals, vol. 43(3), pages 259-271.
  47. Diebold, Francis X & Gunther, Todd A & Tay, Anthony S, 1998. "Evaluating Density Forecasts with Applications to Financial Risk Management," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 863-83, November.
  48. Hasbrouck, Joel, 1991. " Measuring the Information Content of Stock Trades," Journal of Finance, American Finance Association, vol. 46(1), pages 179-207, March.
  49. 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.
  50. 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.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:hum:wpaper:sfb649dp2007-066. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (RDC-Team)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.