The Grid Bootstrap for Continuous Time Models
Yiu Lim Lui (),
Weilin Xiao () and
Jun Yu ()
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Yiu Lim Lui: School of Economics, Singapore Management University
Weilin Xiao: School of Management, Zhejiang University
No 20-2018, Economics and Statistics Working Papers from Singapore Management University, School of Economics
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.
Keywords: Grid bootstrap; In-fill asymptotics; Continuous time models; Long-span asymptotics. (search for similar items in EconPapers)
JEL-codes: C11 C12 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-sea
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Persistent link: https://EconPapers.repec.org/RePEc:ris:smuesw:2018_020
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