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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/26350
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| Title: | The Local Whittle Estimator of Long Memory Stochastic Volatility |
| Authors: | Hurvich, Clifford M.
Ray, Bonnie K. |
| Keywords: | long-range dependence
nonlinearity
semiparametric estimation |
| Issue Date: | Apr-2001 |
| Publisher: | Stern School of Business, New York University |
| Series/Report no.: | SOR-2001-1 |
| Abstract: | We propose a new semiparametric estimator of the degree of persistence
in volatility for long memory stochastic volatility (LMSV) models. The
estimator uses the periodogram of the 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 yields more accurate
confidence intervals than the widely-used GPH estimator. In an empirical
analysis of the daily Deutschemark/Dollar exchange rate, the new
estimator indicates stronger persistence in volatility than the GPH
estimator, provided that a large number of frequencies is used. |
| URI: | http://hdl.handle.net/2451/26350 |
| Appears in Collections: | IOMS: Statistics Working Papers
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