No-arbitrage semi-martingale restrictions for continuous-time volatility models subject to leverage effects, jumps and i.i.d. noise: Theory and testable distributional implications

被引:180
作者
Andersen, Torben G. [1 ]
Bollerslev, Tim
Dobrev, Dobrislav
机构
[1] Northwestern Univ, JL Kellogg Grad Sch Management, Dept Finance, Evanston, IL 60208 USA
[2] Duke Univ, Dept Econ, Durham, NC 27708 USA
[3] NBER, Cambridge, MA 02138 USA
基金
美国国家科学基金会;
关键词
high-frequency data; realized volatility; jump detection; financial time sampling; normality tests;
D O I
10.1016/j.jeconom.2006.05.018
中图分类号
F [经济];
学科分类号
02 ;
摘要
We develop a sequential procedure to test the adequacy of jump-diffusion models for return distributions. We rely on intraday data and nonparametric volatility measures, along with a new jump detection technique and appropriate conditional moment tests, for assessing the import of jumps and leverage effects. A novel robust-to-jumps approach is utilized to alleviate microstructure frictions for realized volatility estimation. Size and power of the procedure are explored through Monte Carlo methods. Our empirical findings support the jump-diffusive representation for S&P500 futures returns but reveal it is critical to account for leverage effects and jumps to maintain the underlying semi-martingale assumption. (c) 2006 Elsevier B.V. All rights reserved.
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页码:125 / 180
页数:56
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