MODELING HIGH-FREQUENCY FINANCIAL DATA BY PURE JUMP PROCESSES

• 成果类型: Article
• 署名作者: Jing, Bing-Yi; Kong, Xin-Bing; Liu, Zhi
• 署名单位: Hong Kong University of Science & Technology; Fudan University; Xiamen University
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/12-AOS977
• 发表日期: 2012
• 页码: 759-784
• 关键词: stochastic volatility; microstructure noise; Levy process; options; functionals; valuation; driven

摘要

It is generally accepted that the asset price processes contain jumps. In fact, pure jump models have been widely used to model asset prices and/or stochastic volatilities. The question is: is there any statistical evidence from the high-frequency financial data to support using pure jump models alone? The purpose of this paper is to develop such a statistical test against the necessity of a diffusion component. The test is very simple to use and yet effective. Asymptotic properties of the proposed test statistic will be studied. Simulation studies and some real-life examples are included to illustrate our results.