Bias-Reduced Estimation of Long Memory Stochastic Volatility

Frederiksen, Per Skaarup; Nielsen, Morten Ørregaard

doi:10.2139/ssrn.1150704

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Bias-Reduced Estimation of Long Memory Stochastic Volatility

CREATES Research Paper No. 2008-35

17 Pages Posted: 24 Jun 2008 Last revised: 1 Jul 2008

See all articles by Per Skaarup Frederiksen

Morten Ørregaard Nielsen

Aarhus University - Department of Economics and Business Economics

There are 2 versions of this paper

Date Written: June 24, 2008

Abstract

We propose to use a variant of the local polynomial Whittle estimator to estimate the memory parameter in volatility for long memory stochastic volatility models with potential nonstationarity in the volatility process. We show that the estimator is asymptotically normal and capable of obtaining bias reduction as well as a rate of convergence arbitrarily close to the parametric rate, n1=2. A Monte Carlo study is conducted to support the theoretical results, and an analysis of daily exchange rates demonstrates the empirical usefulness of the estimators.

Keywords: Bias reduction, local Whittle estimation, long memory stochastic volatility model

JEL Classification: C14, C22

Suggested Citation: Suggested Citation

Frederiksen, Per Skaarup and Nielsen, Morten Orregaard, Bias-Reduced Estimation of Long Memory Stochastic Volatility (June 24, 2008). CREATES Research Paper No. 2008-35, Available at SSRN: https://ssrn.com/abstract=1150704 or http://dx.doi.org/10.2139/ssrn.1150704