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Nonparametric specification tests for stochastic volatility models based on volatility density

Zu, Yang

Authors

YANG ZU yang.zu@nottingham.ac.uk
Assistant Professor



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.

Journal Article Type Article
Journal Journal of Econometrics
Print ISSN 0304-4076
Electronic ISSN 0304-4076
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 187
APA6 Citation Zu, Y. (in press). Nonparametric specification tests for stochastic volatility models based on volatility density. Journal of Econometrics, 187, https://doi.org/10.1016/j.jeconom.2015.02.045
DOI https://doi.org/10.1016/j.jeconom.2015.02.045
Keywords Nonparametric tests, Kernel deconvolution estimator, Stochastic volatility model
Publisher URL http://www.sciencedirect.com/science/article/pii/S0304407615001190
Copyright Statement Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0





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