Testing for non-correlation between price and volatility jumps

被引:9
作者
Jacod, Jean [1 ,2 ]
Klueppelberg, Claudia [3 ,4 ]
Mueller, Gernot [5 ]
机构
[1] CNRS, Inst Math Jussieu, UMR 7586, 4 Pl Jussieu, F-75005 Paris, France
[2] Univ Pierre & Marie Curie P6, 4 Pl Jussieu, F-75005 Paris, France
[3] Tech Univ Munich, Ctr Math Sci, Boltzmannstr 3, D-85748 Garching, Germany
[4] Tech Univ Munich, Inst Adv Study, Boltzmannstr 3, D-85748 Garching, Germany
[5] Univ Augsburg, Inst Math, Univ Str 14, D-86159 Augsburg, Germany
关键词
Common jumps; Discrete sampling; High-frequency data; Ito semimartingale; Statistical test; Stochastic volatility model; MODEL;
D O I
10.1016/j.jeconom.2016.11.007
中图分类号
F [经济];
学科分类号
02 ;
摘要
We consider a log-price process X-t, which is observed at discrete times 0, Delta(n), 2 Delta(n),, and the process has a stochastic squared volatility sigma(2)(t). Assuming that the price process as well as the volatility process have common jumps, we suggest tests for non-correlation between log-price and squared volatility jumps, or functions of such jumps. Our tests have a prescribed asymptotic level, as the mesh Delta(n) tends to 0 and the observation time T-n tends to infinity. The finite sample performance of our test is studied using simulations. We finally apply our tests to real data, and the test rejects the non-correlation hypothesis for the combination of squared log-price jumps and the moduli of the jumps of the squared volatility. This sheds new light on economically motivated statements on causality between price and volatility jumps and on econometric modeling. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:284 / 297
页数:14
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