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On the (intradaily) seasonality and dynamics of a financial point process: a semiparametric approach

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  • VEREDAS, David
  • RODRIGUEZ, Juan
  • ESPASA, Antoni

Abstract

A new method of estimating a component model for the analysis of financial durations is proposed. The components are long-run dynamics and seasonality. The latter is left unspecified and the former is assumed to fall within the class ofa certain family of parametric functions. The proposed estimation procedure is based on a generalized profile likelihood approach and requires the assumption either of a likelihood function for the model errors or, at least, that the errordensity belongs to the class of exponential densities. Its main interest is twofold: first, consistent and asymptotically normal estimators for both the parameters of the long-run stochastic component and the nonparametric curve that approximatesthe deterministic seasonal component are provided. Hence, it is possible to derive correct inference for both parametric and nonparametric components. Second, the method is computationally very appealing since the resulting nonparametricestimator of the seasonal curve has an explicit form that turns out to be a transformation of the Nadaraya-Watson estimator. The method is applied to price and volume durations of a stock traded at the NYSE, and compared to estimation with splines and with adjustment methods. It is shown that the proposed method outperforms the other methods.

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Bibliographic Info

Paper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers with number 2002023.

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Date of creation: 00 Apr 2002
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Handle: RePEc:cor:louvco:2002023

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Keywords: Tick-by-tick; ACD model; seasonal analysis; nonparametric method;

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References

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Cited by:
  1. repec:ulb:ulbeco:2013/5867 is not listed on IDEAS
  2. Fernandes, Marcelo & Grammig, Joachim, 2003. "Nonparametric specification tests for conditional duration models," Economics Working Papers (Ensaios Economicos da EPGE) 502, Graduate School of Economics, Getulio Vargas Foundation (Brazil).
  3. Ben Omrane, Walid & de Bodt, Eric, 2007. "Using self-organizing maps to adjust for intra-day seasonality," Journal of Banking & Finance, Elsevier, vol. 31(6), pages 1817-1838, June.
  4. Nikolaus Hautsch, 2002. "Modelling Intraday Trading Activity Using Box-Cox-ACD Models," CoFE Discussion Paper 02-05, Center of Finance and Econometrics, University of Konstanz.
  5. 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.
  6. Hujer, Reinhard & Vuletic, Sandra, 2007. "Econometric analysis of financial trade processes by discrete mixture duration models," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 635-667, February.
  7. Nikolaus Hautsch & Winfried Pohlmeier, 2001. "Econometric Analysis of Financial Transaction Data: Pitfalls and Opportunities," CoFE Discussion Paper 01-05, Center of Finance and Econometrics, University of Konstanz.

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