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Non-Parametric Specification Tests for Conditional Duration Models

Listed author(s):
  • Fernandes, M.
  • Grammig, J.

This paper deals with the estimation and testing of conditional duration models by looking at the density and baseline hazard functions. More precisely, we focus on the distance between the aprametric density (or hazard rate) function implied by the duration process and its non-parametric estimate.

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Paper provided by European University Institute in its series Economics Working Papers with number eco2000/4.

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Length: 51 pages
Date of creation: 2000
Handle: RePEc:eui:euiwps:eco2000/4
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  25. Newey, W.K., 1992. "Kernel Estimation of Partial Means and a General Variance Estimator," Working papers 93-3, Massachusetts Institute of Technology (MIT), Department of Economics.
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  30. 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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  32. Chen, Song Xi, 1999. "Beta kernel estimators for density functions," Computational Statistics & Data Analysis, Elsevier, vol. 31(2), pages 131-145, August.
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  39. 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.
  40. O. Scaillet, 2001. "Density Estimation Using Inverse and Reciprocal Inverse Gaussian Kernels," THEMA Working Papers 2001-24, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
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  48. repec:cup:etheor:v:10:y:1994:i:2:p:233-53 is not listed on IDEAS
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