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On log-symmetric duration models applied to high frequency financial data

Author

Listed:
  • Helton Saulo

    (Department of Statistics, University of Brasília, Brasília, Brazil)

  • Jeremias Leão

    (Department of Statistics, Federal University of Amazonas, Brazil)

Abstract

This paper deals with a new generalization of autoregressive conditional duration (ACD) models. In special, we propose a new family of ACD models based on a class of log-symmetric distributions. In this new class, it is possible to model both median and skewness of the duration time distribution. We discuss maximum likelihood estimation of the model parameters. For illustrative purposes, we analyze a high frequency financial data set from the German DAX in 2016.

Suggested Citation

  • Helton Saulo & Jeremias Leão, 2017. "On log-symmetric duration models applied to high frequency financial data," Economics Bulletin, AccessEcon, vol. 37(2), pages 1089-1097.
    • Handle: RePEc:ebl:ecbull:eb-17-00030
    as

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    References listed on IDEAS

    as
    1. Fernandes, Marcelo & Grammig, Joachim, 2006. "A family of autoregressive conditional duration models," Journal of Econometrics, Elsevier, vol. 130(1), pages 1-23, January.
    2. 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.
    3. De Luca, Giovanni & Zuccolotto, Paola, 2006. "Regime-switching Pareto distributions for ACD models," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2179-2191, December.
    4. 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.
    5. Luc Bauwens & Pierre Giot, 2000. "The Logarithmic ACD Model: An Application to the Bid-Ask Quote Process of Three NYSE Stocks," Annals of Economics and Statistics, GENES, issue 60, pages 117-149.
    6. 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.
    7. repec:adr:anecst:y:2000:i:60:p:05 is not listed on IDEAS
    8. Luis Vanegas & Gilberto Paula, 2015. "A semiparametric approach for joint modeling of median and skewness," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(1), pages 110-135, March.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Marcelo Ventura & Helton Saulo & Victor Leiva & Sandro Monsueto, 2019. "Log‐symmetric regression models: information criteria and application to movie business and industry data with economic implications," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 35(4), pages 963-977, July.
    2. Saulo, Helton & Balakrishnan, Narayanaswamy & Vila, Roberto, 2023. "On a quantile autoregressive conditional duration model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 203(C), pages 425-448.

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    More about this item

    Keywords

    Log-symmetric distributions; likelihood method; high frequency data; autoregressive conditional;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics

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