Bootstrapping High-Frequency Jump Tests

• 成果类型: Article
• 署名作者: Dovonon, Prosper; Goncalves, Silvia; Hounyo, Ulrich; Meddahi, Nour
• 署名单位: Concordia University - Canada; McGill University; State University of New York (SUNY) System; University at Albany, SUNY; CREATES; Universite de Toulouse; Universite Toulouse 1 Capitole; Toulouse School of Economics
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1080/01621459.2018.1447485
• 发表日期: 2019
• 页码: 793-803
• 关键词: stochastic volatility; prices; models

摘要

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 ). We first discuss a set of high-level conditions on 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 . 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.