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Estimating Stochastic Volatility Models using Prediction-based Estimating Functions

Asger Lunde () and Anne Floor Brix ()
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Asger Lunde: Aarhus University and CREATES, Postal: Department of Economics and Business, Fuglesangs Allé 4, 8210 Aarhus V, Denmark
Anne Floor Brix: 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: In this paper prediction-based estimating functions (PBEFs), introduced in Sørensen (2000), are reviewed and PBEFs for the Heston (1993) stochastic volatility model are derived. The finite sample performance of the PBEF based estimator is investigated in a Monte Carlo study, and compared to the performance of the GMM estimator based on conditional moments of integrated volatility from Bollerslev and Zhou (2002). The case where the observed log-price process is contaminated by i.i.d. market microstructure (MMS) noise is also investigated. First, the impact of MMS noise on the parameter estimates from the two estimation methods without noise correction are studied. Second, a noise robust GMM estimator is constructed by approximating integrated volatility by a realized kernel instead of realized variance. The PBEFs are also recalculated in the noise setting, and the two estimation methods ability to correctly account for the noise are investigated. Our Monte Carlo study shows that the estimator based on PBEFs outperforms the GMM estimator, both in the setting with and without MMS noise. Finally, an empirical application investigates the possible challenges and general performance of applying the PBEF based estimator in practice.

Keywords: GMMestimation; Heston model; high-frequency data; integrated volatility; market microstructure noise; prediction-based estimating functions; realized variance; realized kernel (search for similar items in EconPapers)
JEL-codes: C13 C22 C51 (search for similar items in EconPapers)
Pages: 38
Date: 2013-02-07
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for, nep-mst and nep-ore
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