Discretization of Lévy semistationary processes with application to estimation

Mikkel Bennedsen (), Asger Lunde () and Mikko S. Pakkanen ()
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Mikkel Bennedsen: Aarhus University and CREATES, Postal: Department of Economics and Business, Fuglesangs Allé 4, 8210 Aarhus V, Denmark
Asger Lunde: Aarhus University and CREATES, Postal: Department of Economics and Business, Fuglesangs Allé 4, 8210 Aarhus V, Denmark
Mikko S. Pakkanen: Aarhus University and CREATES, Postal: Department of Economics and Business, Fuglesangs Allé 4, 8210 Aarhus V, Denmark

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

Abstract: Motivated by the construction of the Itô stochastic integral, we consider a step function method to discretize and simulate volatility modulated Lévy semistationary processes. Moreover, we assess the accuracy of the method with a particular focus on integrating kernels with a singularity at the origin. Using the simulation method, we study the finite sample properties of some recently developed estimators of realized volatility and associated parametric estimators for Brownian semistationary processes. Although the theoretical properties of these estimators have been established under high frequency asymptotics, it turns out that the estimators perform well also in a low frequency setting.

Keywords: Stochastic simulation; discretization; Lévy semistationary processes; stochastic volatility; estimation; finite sample properties (search for similar items in EconPapers)
JEL-codes: C13 C15 C63 (search for similar items in EconPapers)
Pages: 28
Date: 2014-08-11
New Economics Papers: this item is included in nep-ecm and nep-ets
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Citations: View citations in EconPapers (3)

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