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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

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Author Info
Khalaf, Lynda
Saphores, Jean-Daniel
Bilodeau, Jean-François

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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.

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Paper provided by Université Laval - Département d'économique in its series Cahiers de recherche with number 0004.

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Date of creation: 2000
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Handle: RePEc:lvl:laeccr:0004

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Related research
Keywords: Monte-Carlo test; bounds test; discontinuous process; conditional heteroscedasticity;

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Find related papers by JEL classification:
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing
Q3 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation

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