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A Comparison of Financial Duration Models via Density Forecasts

  • Luc Bauwens

    (Universite Catholique de Louvain)

  • Pierre Giot

    (Universite Catholique de Louvain)

  • Joachim Grammig

    (University of Frankfurt)

  • David Veredas

    (Universite Catholique de Louvain)

Using density forecasts, we compare the predictive performance of duration models that have been developed for modelling intra-day data on stock markets. The compared models are the autoregressive conditional duration (ACD) models, their logarithmic versions, in each case with three distributions (Burr, Weibull, and exponential), and the stochastic volatility duration (SVD) model. A pilot Monte Carlo study is conducted to illustrate the relevance of the approach. The evaluation is done on transaction, price, and volume durations of 4 stocks listed at the NYSE. The results lead us to conclude that ACD and Log-ACD models often capture the dependence in the data in a satisfactory way, that they fit correctly the distribution of volume durations, that they fail to do so for trade durations, while the evidence is mixed for price durations.

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Paper provided by Econometric Society in its series Econometric Society World Congress 2000 Contributed Papers with number 0810.

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Date of creation: 01 Aug 2000
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Handle: RePEc:ecm:wc2000:0810
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  1. Ghysels, E. & Harvey, A. & Renault, E., 1996. "Stochastic Volatility," Cahiers de recherche 9613, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  2. David Veredas & Juan M. Rodríguez-Poo & Antoni Espasa, 2001. "On The (Intradaily) Seasonality And Dynamics Of A Financial Point Process: A Semiparametric Approach," Statistics and Econometrics Working Papers ws013321, Universidad Carlos III, Departamento de Estadística y Econometría.
  3. Rombouts, Jeroen V. K. & Bauwens, Luc, 2004. "Econometrics," Papers 2004,33, Humboldt-Universität Berlin, Center for Applied Statistics and Economics (CASE).
  4. 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.
  5. Berkowitz, Jeremy, 2001. "Testing Density Forecasts, with Applications to Risk Management," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(4), pages 465-74, October.
  6. BAUWENS, Luc & GIOT, Pierre, . "The logarithmic ACD model: an application to the bid-ask quote process of three NYSE stocks," CORE Discussion Papers RP 1497, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  7. Fernandes, Marcelo & Grammig, Joachim, 2005. "Nonparametric specification tests for conditional duration models," Journal of Econometrics, Elsevier, vol. 127(1), pages 35-68, July.
  8. Christian Gourieroux & Joann Jasiak, 2001. "Dynamic Factor Models," Econometric Reviews, Taylor & Francis Journals, vol. 20(4), pages 385-424.
  9. Chen, Song Xi, 1999. "Beta kernel estimators for density functions," Computational Statistics & Data Analysis, Elsevier, vol. 31(2), pages 131-145, August.
  10. 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).
  11. Easley, David, et al, 1996. " Liquidity, Information, and Infrequently Traded Stocks," Journal of Finance, American Finance Association, vol. 51(4), pages 1405-36, September.
  12. Olivier Renault & Jean-Luc Prigent & Olivier Scaillet, 2000. "An Autoregressive Conditional Binomial Option Pricing Model," FMG Discussion Papers dp364, Financial Markets Group.
  13. 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.
  14. Ghysels, Eric & Gourieroux, Christian & Jasiak, Joann, 2004. "Stochastic volatility duration models," Journal of Econometrics, Elsevier, vol. 119(2), pages 413-433, April.
  15. Francis X. Diebold & Todd A. Gunther & Anthony S. Tay, 1997. "Evaluating Density Forecasts," Center for Financial Institutions Working Papers 97-37, Wharton School Center for Financial Institutions, University of Pennsylvania.
  16. repec:fth:inseep:9908 is not listed on IDEAS
  17. Granger, C.W.J. & Pesaran, H., 1996. "A Decision_Theoretic Approach to Forecast Evaluation," Cambridge Working Papers in Economics 9618, Faculty of Economics, University of Cambridge.
  18. J. Grammig & K. Maurer, 1999. "Non-Monotonic Hazard Functions and the Autoregressive Conditional Duration Model," SFB 373 Discussion Papers 1999,50, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  19. Kim, Sangjoon & Shephard, Neil & Chib, Siddhartha, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," Review of Economic Studies, Wiley Blackwell, vol. 65(3), pages 361-93, July.
  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.
  21. Zhang, Michael Yuanjie & Russell, Jeffrey R. & Tsay, Ruey S., 2001. "A nonlinear autoregressive conditional duration model with applications to financial transaction data," Journal of Econometrics, Elsevier, vol. 104(1), pages 179-207, August.
  22. repec:fth:inseep:9633 is not listed on IDEAS
  23. Gouriéroux, Christian & Jasiak, Joanna & Le Fol, Gaëlle, 1999. "Intra-day market activity," Economics Papers from University Paris Dauphine 123456789/5478, Paris Dauphine University.
  24. Engle, Robert F. & Russell, Jeffrey R., 1997. "Forecasting the frequency of changes in quoted foreign exchange prices with the autoregressive conditional duration model," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 187-212, June.
  25. Madhavan, Ananth, 2000. "Market microstructure: A survey," Journal of Financial Markets, Elsevier, vol. 3(3), pages 205-258, August.
  26. Goodhart, Charles A. E. & O'Hara, Maureen, 1997. "High frequency data in financial markets: Issues and applications," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 73-114, June.
  27. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
  28. 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.
  29. Song Chen, 2000. "Probability Density Function Estimation Using Gamma Kernels," Annals of the Institute of Statistical Mathematics, Springer, vol. 52(3), pages 471-480, September.
  30. GIOT, Pierre, 1999. "Time transformations, intraday data and volatility models," CORE Discussion Papers 1999044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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