Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/130016
Authors: 
Kanaya, Shin
Kristensen, Dennis
Year of Publication: 
2015
Series/Report no.: 
cemmap working paper, Centre for Microdata Methods and Practice CWP09/15
Abstract: 
A two-step estimation method of stochastic volatility models is proposed. In the first step, we nonparametrically estimate the (unobserved) instantaneous volatility process. In the second step, standard estimation methods for fully observed diffusion processes are employed, but with the filtered/estimated volatility process replacing the latent process. Our estimation strategy is applicable to both parametric and nonparametric stochastic volatility models, and can handle both jumps and market microstructure noise. The resulting estimators of the stochastic volatility model will carry additional biases and variances due to the first-step estimation, but under regularity conditions we show that these vanish asymptotically and our estimators inherit the asymptotic properties of the infeasible estimators based on observations of the volatility process. A simulation study examines the finite-sample properties of the proposed estimators.
Subjects: 
Realized spot volatility
stochastic volatility
kernel estimation
nonparametric
semi-parametric
JEL: 
C14
C32
C58
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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