Stationary and multi-self-similar random fields with stochastic volatility
File(s)
Accepted version
Author(s)
Veraart, AED
Type
Journal Article
Abstract
This paper introduces stationary and multi-self-similar random fields which account for stochastic volatility and have type G marginal law. The stationary random fields are constructed using volatility modulated mixed moving average (MA) fields and their probabilistic properties are discussed. Also, two methods for parameterizing the weight
functions in the MA representation are presented: one method is based on Fourier techniques and aims at reproducing a given correlation structure, the other method is based on ideas from stochastic partial differential equations. Moreover, using a generalized Lamperti transform we construct volatility modulated multi-self-similar random fields which have type G distribution.
functions in the MA representation are presented: one method is based on Fourier techniques and aims at reproducing a given correlation structure, the other method is based on ideas from stochastic partial differential equations. Moreover, using a generalized Lamperti transform we construct volatility modulated multi-self-similar random fields which have type G distribution.
Date Issued
2013-10-01
Date Acceptance
2015-01-22
Citation
Stochastics, 2013, 87 (5), pp.848-870
ISSN
0090-9491
Publisher
Taylor & Francis
Start Page
848
End Page
870
Journal / Book Title
Stochastics
Volume
87
Issue
5
Copyright Statement
© 2015 Taylor & Francis. This is an Author's Accepted Manuscript of an article published in [include the complete citation information for the final version of the article as published in the Stochastics, available online at: http://www.tandfonline.com/10.1080/17442508.2015.1012081
Identifier
http://arxiv.org/abs/1402.2882
Publication Status
Published