Nonparametric specification tests for stochastic volatility models based on volatility density

Zu, Y. (2015). Nonparametric specification tests for stochastic volatility models based on volatility density. Journal of Econometrics, 187(1), pp. 323-344. doi: 10.1016/j.jeconom.2015.02.045

[img]
Preview
Text - Accepted Version
Available under License : See the attached licence file.

Download (576kB) | Preview
[img]
Preview
Text (Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International) - Other
Download (201kB) | Preview

Abstract

This paper develops a specification test for stochastic volatility models by comparing the nonparametric kernel deconvolution density estimator of an integrated volatility density with its parametric counterpart. L2 distance is used to measure the discrepancy. The asymptotic null distributions of the test statistics are established and the asymptotic power functions are computed. Through Monte Carlo simulations, the size and power properties of the test statistics are studied. The tests are applied to an empirical example.

Item Type: Article
Additional Information: © 2015, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords: nonparametric tests, kernel deconvolution estimator, stochastic volatility model
Subjects: H Social Sciences > HB Economic Theory
Divisions: School of Social Sciences > Department of Economics
URI: http://openaccess.city.ac.uk/id/eprint/8090

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics