The Local Whittle Estimator of Long Memory Stochastic Volatility
22 Pages Posted: 3 Nov 2008
Date Written: May 2003
We propose a new semiparametric estimator of the degree of persistence in volatility forlong memory stochastic volatility (LMSV) models. The estimator uses the periodogram ofthe log squared returns in a local Whittle criterion which explicitly accounts for the noise term in the LMSV model. Finite-sample and asymptotic standard errors for the estimator are provided. An extensive simulation study reveals that the local Whittle estimator is much less biased and that the finite-sample standard errors yield more accurate confidence intervals than the widely-used GPH estimator. The estimator is also found to be robust against possible leverage effects. In an empirical analysis of the daily Deutsche Mark/US Dollar exchange rate, the new estimator indicates stronger persistence in volatility than the GPH estimator, provided that a large number of frequencies is used.
Keywords: long-range dependence, nonlinearity, semiparametric estimation
Suggested Citation: Suggested Citation