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 nonstation-
arity 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.
parameter in volatility for long memory stochastic volatility models with potential nonstation-
arity 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.
| Originalsprog | Engelsk |
|---|---|
| Udgivelsessted | Aarhus |
| Udgiver | Inistitut for Økonomi, Aarhus Universitet |
| Antal sider | 15 |
| Status | Udgivet - 2008 |