Arbeitspapier
Local polynomial Whittle estimation of perturbed fractional processes
We propose a semiparametric local polynomial Whittle with noise estimator of the memory parameter in long memory time series perturbed by a noise term which may be serially correlated. The estimator approximates the log-spectrum of the short-memory component of the signal as well as that of the perturbation by two separate polynomials. Including these polynomials we obtain a reduction in the order of magnitude of the bias, but also inflate the asymptotic variance of the long memory estimator by a multiplicative constant. We show that the estimator is consistent for d in (0,1), asymptotically normal for d in (0,3/4), and if the spectral density is sufficiently smooth near frequency zero, the rate of convergence can become arbitrarily close to the parametric rate, sqrt(n). A Monte Carlo study reveals that the proposed estimator performs well in the presence of a serially correlated perturbation term. Furthermore, an empirical investigation of the 30 DJIA stocks shows that this estimator indicates stronger persistence in volatility than the standard local Whittle (with noise) estimator.
- Language
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Englisch
- Bibliographic citation
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Series: Queen's Economics Department Working Paper ; No. 1218
- Classification
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Wirtschaft
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- Subject
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bias reduction
local Whittle
long memory
perturbed fractional process
semiparametric estimation
stochastic volatility
Schätztheorie
Nichtparametrisches Verfahren
- Event
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Geistige Schöpfung
- (who)
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Frederiksen, Per
Nielsen, Frank S.
Nielsen, Morten Ørregaard
- Event
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Veröffentlichung
- (who)
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Queen's University, Department of Economics
- (where)
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Kingston (Ontario)
- (when)
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2009
- Handle
- Last update
-
20.09.2024, 8:22 AM CEST
Data provider
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Object type
- Arbeitspapier
Associated
- Frederiksen, Per
- Nielsen, Frank S.
- Nielsen, Morten Ørregaard
- Queen's University, Department of Economics
Time of origin
- 2009