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Simulation-Based Exact Tests with Unidentified Nuisance Parameters under the Null Hypothesis : the Case of Jumps Tests in Model with Conditional Heteroskedasticity

Author

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  • Khalaf, Lynda
  • Saphores, Jean-Daniel
  • Bilodeau, Jean-François

Abstract

We use the Monte-Carlo (MC) test technique to find valid p-values when testing for discontinuities in jump-diffusion models. While the distribution of the LR statistic for this test is typically non-standard, we show that the MC p-value is finite sample exact if no other (identified) nuisance parameter is present. Otherwise, we derive nuisance-parameter free bounds and obtain exact bounds p-values. We illustrate our approach on four classes of jump-diffusion models we use to model spot prices of copper, nickel, gold, and crude oil. We find significant jumps in all weekly time series and in a few monthly time series.

Suggested Citation

  • Khalaf, Lynda & Saphores, Jean-Daniel & Bilodeau, Jean-François, 2000. "Simulation-Based Exact Tests with Unidentified Nuisance Parameters under the Null Hypothesis : the Case of Jumps Tests in Model with Conditional Heteroskedasticity," Cahiers de recherche 0004, Université Laval - Département d'économique.
    • Handle: RePEc:lvl:laeccr:0004
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    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • Q3 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation

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