Nonparametric volatility density estimation for discrete time models.

Authors
Publication date 2005
Journal Journal of Nonparametric Statistics
Volume | Issue number 17 | 2
Pages (from-to) 237-251
Number of pages 16
Organisations
  • Faculty of Science (FNWI) - Korteweg-de Vries Institute for Mathematics (KdVI)
Abstract Abstract:
We consider discrete time models for asset prices with a stationary volatility process. We aim at estimating the multivariate density of this process at a set of consecutive time instants. A Fourier type deconvolution kernel density estimator based on the logarithm of the squared process is proposed to estimate the volatility density. Expansions of the bias and bounds on the variance are derived.
Document type Article
Published at https://doi.org/10.1080/1048525042000267752
Published at http://journalsonline.tandf.co.uk/app/home/contribution.asp?wasp=94cf166b2ddb4690ae9cd18e236cc46e&referrer=parent&backto=issue,7,8;journal,4,19;linkingpublicationresults,1:101461,1
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