Estimation of integrated volatility in stochastic volatility models

被引:24
|
作者
Woerner, JHC [1 ]
机构
[1] Univ Gottingen, Inst Math Stochast, D-37073 Gottingen, Germany
关键词
stochastic volatility; limit theorem; power variation; quadratic variation; semimartingale; jump process; fractional Brownian motion; high-frequency data;
D O I
10.1002/asmb.548
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
In the framework of stochastic volatility models we examine estimators for the integrated volatility based on the pth power variation (i.e. the sum of pth absolute powers of the log-returns). We derive consistency and distributional results for the estimators given high-frequency data, especially taking into account what kind of process we may add to our model without affecting the estimate of the integrated volatility. This may on the one hand be interpreted as a possible flexibility in modelling, for example adding jumps or even leaving the framework of sernimartingales by adding a fractional Brownian motion, or on the other hand as robustness against model misspecification. We will discuss possible choices of p under different model assumptions and irregularly spaced data. Copyright (C) 2005 John Wiley Sons, Ltd.
引用
收藏
页码:27 / 44
页数:18
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