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EFFICIENT ESTIMATION OF INTEGRATED VOLATILITY AND RELATED PROCESSES

Published online by Cambridge University Press:  15 March 2016

Eric Renault ,
Cisil Sarisoy  and
Bas J.M. Werker
Eric Renault
Affiliation:
Brown University
Cisil Sarisoy
Affiliation:
Tilburg University
Bas J.M. Werker*
Affiliation:
Tilburg University
*
*Address correspondence to Bas J.M. Werker, Econometrics and Finance Groups, CentER, Tilburg University; e-mail: B.J.M.Werker@TilburgUniversity.edu.
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Abstract

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We derive nonparametric efficiency bounds for regular estimators of integrated smooth transformations of instantaneous variances, in particular, integrated power variance. We find that realized variance attains the efficiency bound for integrated variance under both regular and irregular sampling schemes. For estimating higher powers such as integrated quarticity, the block-based procedures of Mykland and Zhang (2009) can get arbitrarily close to the nonparametric bounds, when observation times are equidistant. Moreover, the estimator in Jacod and Rosenbaum (2013), whose efficiency was documented for the submodel assuming constant volatility, is efficient also for nonconstant volatility paths. When the observation times are possibly random but predictable, we provide an estimator, similar to that of Kristensen (2010), which can get arbitrarily close to the nonparametric bound. Finally, parametric information about the functional form of volatility leads to a lower efficiency bound, unless the volatility process is piecewise constant.

Information

Type
ARTICLES
Information
Econometric Theory , Volume 33 , Issue 2 , April 2017 , pp. 439 - 478
Copyright
Copyright © Cambridge University Press 2016 

References

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