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Estimation of Long Memory in Volatility

Authors: Deo, Rohit S.
Hurvich, C. M.
Issue Date: 2000
Publisher: Stern School of Business, New York University
Series/Report no.: SOR-2000-14
Abstract: We discuss some of the issues pertaining to modelling and estimating long memory in volatility. The main focus is on semi parametric estimation of the memory parameter in the long memory stochastic volatility model. We present the asymptotic properties of the log periodogram regression estimator of the memory parameter in this model. A modest simulation study of the estimator is also presented to study its behaviour when the volatility possesses only short memory. We conclude with a discussion of the appropriate choice of transformation of returns to measure persistence in volatility.
Appears in Collections:IOMS: Statistics Working Papers

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