Publication Type

Journal Article

Version

acceptedVersion

Publication Date

10-2016

Abstract

We propose a consistent functional estimator for the occupation time of the spot variance of an asset price observed at discrete times on a finite interval with the mesh of the observation grid shrinking to zero. The asset price is modeled nonparametrically as a continuous-time Itô semimartingale with nonvanishing diffusion coefficient. The estimation procedure contains two steps. In the first step we estimate the Laplace transform of the volatility occupation time and, in the second step, we conduct a regularized Laplace inversion. Monte Carlo evidence suggests that the proposed estimator has good small-sample performance and in particular it is far better at estimating lower volatility quantiles and the volatility median than a direct estimator formed from the empirical cumulative distribution function of local spot volatility estimates. An empirical application shows the use of the developed techniques for nonparametric analysis of variation of volatility.

Keywords

semimartingale, long memory, stochastic volatility, semiparametric efficiency, local asymptotic mixed normality, irregular sampling.

Discipline

Econometrics

Research Areas

Econometrics

Publication

Econometric Theory

Volume

32

Issue

5

First Page

1253

Last Page

1288

ISSN

0266-4666

Identifier

10.1017/S0266466615000171

Publisher

Cambridge University Press

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1017/S0266466615000171

Included in

Econometrics Commons

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