A class of nonlinear stochastic volatility models

DOI

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.

Copyright

© 2006, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jun Yu
AU  - Zhenlin Yang
PY  - 2006/10
DA  - 2006/10
TI  - A class of nonlinear stochastic volatility models
BT  - Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.87
DO  - 10.2991/jcis.2006.87
ID  - Yu2006/10
ER  -