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The econometrics of randomly spaced financial data: a survey

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  • Andre A. Monteiro

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Abstract

This paper provides an introduction to the problem of modeling randomly spaced longitudinal data. Although Point Process theory was developed mostly in the sixties and early seventies, only in the nineties did this field of Probability theory attract the attention of researchers working in Financial Econometrics. The large increase, observed since, in the number of different classes of Econometric models for dealing with financial duration data, has been mostly due to the increased availability of both trade-by-trade data from equity markets and daily default and rating migration data from credit markets. This paper provides an overview of the main Econometric models available in the literature for dealing with what is sometimes called tick data. Additionally, a synthesis of the basic theory underlying these models is also presented. Finally, a new theorem dealing with the identifiability of latent intensity factors from point process data, jointly with a heuristic proof, is introduced.

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Bibliographic Info

Paper provided by Universidad Carlos III, Departamento de Estadística y Econometría in its series Statistics and Econometrics Working Papers with number ws097924.

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Date of creation: Dec 2009
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Handle: RePEc:cte:wsrepe:ws097924

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Keywords: Tick data; Financial duration models; Point processes; Migration models;

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  1. Frank Gerhard & Nikolaus Hautsch, . "Semiparametric autoregressive conditional proportional hazard models," Economics Papers 2002-W2, Economics Group, Nuffield College, University of Oxford.
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  4. Gagliardini, P. & Gourieroux, C., 2005. "Migration correlation: Definition and efficient estimation," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 865-894, April.
  5. FERNANDES, Marcelo & GRAMMIG, Joachim, 2001. "A family of autoregressive conditional duration models," CORE Discussion Papers 2001036, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  6. Patrick Gagliardini, 2005. "Stochastic Migration Models with Application to Corporate Risk," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 3(2), pages 188-226.
  7. BAUWENS, Luc & GALLI, Fausto, 2007. "Efficient importance sampling for ML estimation of SCD models," CORE Discussion Papers 2007053, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  8. Luc, BAUWENS & Nikolaus, HAUTSCH, 2006. "Modelling Financial High Frequency Data Using Point Processes," Discussion Papers (ECON - Département des Sciences Economiques) 2006039, Université catholique de Louvain, Département des Sciences Economiques.
  9. Sergio M. Focardi & Frank J. Fabozzi, 2005. "An autoregressive conditional duration model of credit-risk contagion," Journal of Risk Finance, Emerald Group Publishing, vol. 6(3), pages 208-225, May.
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  14. Jarrow, Robert A & Lando, David & Turnbull, Stuart M, 1997. "A Markov Model for the Term Structure of Credit Risk Spreads," Review of Financial Studies, Society for Financial Studies, vol. 10(2), pages 481-523.
  15. Eric Ghysels & Christian Gourieroux & Joanna Jasiak, 1997. "Stochastic Volatility Duration Models," Working Papers 97-46, Centre de Recherche en Economie et Statistique.
  16. 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.
  17. Harvey, Andrew & Ruiz, Esther & Shephard, Neil, 1994. "Multivariate Stochastic Variance Models," Review of Economic Studies, Wiley Blackwell, vol. 61(2), pages 247-64, April.
  18. Robert Engle, 2002. "New frontiers for arch models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 425-446.
  19. Koopman, Siem Jan & Lucas, Andre & Monteiro, Andre, 2008. "The multi-state latent factor intensity model for credit rating transitions," Journal of Econometrics, Elsevier, vol. 142(1), pages 399-424, January.
  20. Joann Jasiak, 1996. "Persistence in Intertrade Durations," Working Papers 1999_8, York University, Department of Economics, revised Mar 1999.
  21. Andre Monteiro & Georgi V. Smirnov & Andre Lucas, 2006. "Nonparametric Estimation for Non-Homogeneous Semi-Markov Processes: An Application to Credit Risk," Tinbergen Institute Discussion Papers 06-024/2, Tinbergen Institute, revised 27 Mar 2006.
  22. 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.
  23. 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.
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