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Title:Predictive inference for integrated volatility PDF Logo
Authors:Corradi, Valentina
Distaso, Walter
Swanson, Norman R.
Issue Date:2011
Series/Report no.:Working Papers, Department of Economics, Rutgers, the State University of New Jersey 2011,09
Abstract:In recent years, numerous volatility-based derivative products have been engineered. This has led to interest in constructing conditional predictive densities and confidence intervals for integrated volatility. In this paper, we propose nonparametric estimators of the aforementioned quantities, based on model free volatility estimators. We establish consistency and asymptotic normality for the feasible estimators and study their finite sample properties through a Monte Carlo experiment. Finally, using data from the New York Stock Exchange, we provide an empirical application to volatility directional predictability.
Subjects:diffusions
realized volatility measures
kernels
microstructure noise
jumps
prediction
Document Type:Working Paper
Appears in Collections:Working Papers, Department of Economics, Rutgers University

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