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ANOVA for diffusions and Ito processes

delete2006-08-01
delete114
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OA
AI
M
Mykland, Per Aslak *
Z
Zhang, Lan
DOI:10.1214/009053606000000452delete
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Abstract

Abstract

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U processes are the most common form of continuous semimartingales, and include diffusion processes. This paper is concerned with the nonparametric regression relationship between two such U processes. We are interested in the quadratic variation (integrated volatility) of the residual in this regression, over a unit of time (such as a day). A main conceptual finding is that this quadratic variation can be estimated almost as if the residual process were observed, the difference being that there is also a bias which is of the same asymptotic order as the mixed normal error term. The proposed methodology, ANOVA for diffusions and Ito processes, can be used to measure the statistical quality of a parametric model and, nonparametrically, the appropriateness of a one-regressor model in general. On the other hand, it also helps quantify and characterize the trading (hedging) error in the case of financial applications.
Keywords:
ANOVA
continuous sernimartingale
statistical uncertainty
goodness of fit
discrete sampling
parametric and nonparametric estimation
small interval asymptotics
stable convergence
option hedging
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Journal

Annals of Statistics cover
Annals of Statistics
IF:
3.7
Papers:
2.8K
Citations:
2.9W

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