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Bootstrap based probability forecasting in multiplicative error models

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  • Perera, Indeewara
  • Silvapulle, Mervyn J.

Abstract

As evidenced by an extensive empirical literature, multiplicative error models (MEM) show good performance in capturing the stylized facts of nonnegative time series; examples include, trading volume, financial durations, and volatility. This paper develops a bootstrap based method for producing multi-step-ahead probability forecasts for a nonnegative valued time-series obeying a parametric MEM. In order to test the adequacy of the underlying parametric model, a class of bootstrap specification tests is also developed. Rigorous proofs are provided for establishing the validity of the proposed bootstrap methods. The paper also establishes the validity of a bootstrap based method for producing probability forecasts in a class of semiparametric MEMs. Monte Carlo simulations suggest that our methods perform well in finite samples. A real data example illustrates the methods.

Suggested Citation

  • Perera, Indeewara & Silvapulle, Mervyn J., 2021. "Bootstrap based probability forecasting in multiplicative error models," Journal of Econometrics, Elsevier, vol. 221(1), pages 1-24.
  • Handle: RePEc:eee:econom:v:221:y:2021:i:1:p:1-24
    DOI: 10.1016/j.jeconom.2020.01.022
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    Cited by:

    1. Giuseppe Cavaliere & Indeewara Perera & Anders Rahbek, 2021. "Specification tests for GARCH processes," Discussion Papers 21-06, University of Copenhagen. Department of Economics.
    2. Giuseppe Cavaliere & Indeewara Perera & Anders Rahbek, 2021. "Specification tests for GARCH processes," Papers 2105.14081, arXiv.org.

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    More about this item

    Keywords

    Multiplicative error model; Bootstrap; Probability forecast; Goodness-of-fit; Multi-step forecast;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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