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The main contribution of this article is to propose a bootstrap test for jumps based on functions of realized volatility and bipower variation. Bootstrap intraday returns are randomly generated from a mean zero Gaussian distribution with a variance given by a local measure of integrated volatility (which we denote by {vˆni}). We first discuss a set of high-level conditions on {vˆni} such that any bootstrap test of this form has the correct asymptotic size and is alternative-consistent. We then provide a set of primitive conditions that justify the choice of a thresholding-based estimator for {vˆni}. Our cumulant expansions show that the bootstrap is unable to mimic the higher-order bias of the test statistic. We propose a modification of the original bootstrap test which contains an appropriate bias correction term and for which second-order asymptotic refinements are obtained.
Original language | English |
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Journal | Journal of the American Statistical Association |
Volume | 114 |
Issue | 526 |
Pages (from-to) | 793-803 |
Number of pages | 11 |
ISSN | 0162-1459 |
DOIs | |
Publication status | Published - 2019 |
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ID: 136791896