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The Grid Bootstrap for Continuous Time Models

Author

Listed:
  • Yiu Lim Lui

    (School of Economics, Singapore Management University)

  • Weilin Xiao

    (School of Management, Zhejiang University)

  • Jun Yu

    (School of Economics, Singapore Management University)

Abstract

This paper considers the grid bootstrap for constructing confidence intervals for the persistence parameter in a class of continuous time models driven by a Levy process. Its asymptotic validity is established by assuming the sampling interval (h) shrinks to zero. Its improvement over the in-fill asymptotic theory is achieved by expanding the coefficient-based statistic around its in fill asymptotic distribution which is non-pivotal and depends on the initial condition. Monte Carlo studies show that the gird bootstrap method performs better than the in-fill asymptotic theory and much better than the longspan theory. Empirical applications to U.S. interest rate data highlight differences between the bootstrap confidence intervals and the confidence intervals obtained from the in-fill and long-span asymptotic distributions.

Suggested Citation

  • Yiu Lim Lui & Weilin Xiao & Jun Yu, 2018. "The Grid Bootstrap for Continuous Time Models," Economics and Statistics Working Papers 20-2018, Singapore Management University, School of Economics.
    • Handle: RePEc:ris:smuesw:2018_020
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    References listed on IDEAS

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    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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