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Predictor distribution and forecast accuracy of threshold models

Author

Listed:
  • Alessandra Amendola

    (Universitá di Salerno)

  • Marcella Niglio

    (Universitá di Salerno)

Abstract

. In the present paper the predictor distribution of a SETAR (Self Exciting Threshold Autoregressive) model (Tong and Lim, 1980) has been investigated when the lead time is greater than the threshold delay. After a brief presentation of the model under study, some relevant aspects of the density forecasts are shown highlighting how they can be used to generate more accurate predictions and to estimate an approximation of the probability density function of the SETAR predictors. The performances of competing predictors have been evaluated through a simulation study and an application to financial market data of the daily Nikkey 300 stock market returns.

Suggested Citation

  • Alessandra Amendola & Marcella Niglio, 2004. "Predictor distribution and forecast accuracy of threshold models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 13(1), pages 3-14, April.
    • Handle: RePEc:spr:stmapp:v:13:y:2004:i:1:d:10.1007_s10260-003-0072-0
    DOI: 10.1007/s10260-003-0072-0
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    Cited by:

    1. Błażej Mazur & Mateusz Pipień, 2012. "On the Empirical Importance of Periodicity in the Volatility of Financial Returns - Time Varying GARCH as a Second Order APC(2) Process," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 4(2), pages 95-116, June.
    2. Amendola, Alessandra & Christian, Francq, 2009. "Concepts and tools for nonlinear time series modelling," MPRA Paper 15140, University Library of Munich, Germany.

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