Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)

A class of nonlinear stochastic volatility models

Authors
Jun Yu 0, Zhenlin Yang
Corresponding Author
Jun Yu
0Singapore Management University
Available Online October 2006.
DOI
https://doi.org/10.2991/jcis.2006.87How to use a DOI?
Keywords
Box-Cox Transform, EMM, GARCH
Abstract
This paper proposes a class of nonlinear stochastic volatility (SV) models based on the Box-Cox transformation. The proposed class encompasses many parametric SV models that have appeared in the literature, including the well known lognormal SV model, and has an advantage in the ease with which different specifications on SV can be tested. In addition, the functional form of transformation which induces marginal normality of volatility is obtained as a byproduct of this general way of modeling SV. Efficient method of moments is used to estimate the model. Empirical results reveal that the lognormal SV model is rejected.
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Proceedings
Part of series
Advances in Intelligent Systems Research
Publication Date
October 2006
ISBN
978-90-78677-01-7
ISSN
1951-6851
DOI
https://doi.org/10.2991/jcis.2006.87How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Jun Yu
AU  - Zhenlin Yang
PY  - 2006/10
DA  - 2006/10
TI  - A class of nonlinear stochastic volatility models
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.87
DO  - https://doi.org/10.2991/jcis.2006.87
ID  - Yu2006/10
ER  -