Semiparametric Diffusion Estimation and application to a Stock Market Index

Hardle, WK; Kleinow, T; Korostelev, A; Logeay, C; Platen, E

Semiparametric Diffusion Estimation and application to a Stock Market Index

Hardle, WK Kleinow, T Korostelev, A Logeay, C Platen, E

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Publisher:: IOP Publishing Ltd.
Publication Type:: Journal Article
Citation:: Quantitative Finance, 2008, 8 (1), pp. 81 - 92
Issue Date:: 2008-01

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Field	Value	Language
dc.contributor.author	Hardle, WK	en_US
dc.contributor.author	Kleinow, T	en_US
dc.contributor.author	Korostelev, A	en_US
dc.contributor.author	Logeay, C	en_US
dc.contributor.author	Platen, E https://orcid.org/0000-0003-4595-3123	en_US
dc.date.issued	2008-01	en_US
dc.identifier.citation	Quantitative Finance, 2008, 8 (1), pp. 81 - 92	en_US
dc.identifier.issn	1469-7688	en_US
dc.identifier.uri	http://hdl.handle.net/10453/10256
dc.description.abstract	The analysis of diffusion processes in financial models is crucially dependent on the form of the drift and diffusion coefficient functions. A new model for a stock market index process is proposed in which the index is decomposed into an average growth process and an ergodic diffusion. The ergodic diffusion part of the model is not directly observable. A methodology is developed for estimating and testing the coefficient functions of this unobserved diffusion process. The estimation is based on the observations of the index process and uses semiparametric and non-parametric techniques. The testing is performed via the wild bootstrap resampling technique. The method is illustrated on S&P 500 index data.	en_US
dc.publisher	IOP Publishing Ltd.	en_US
dc.relation.ispartof	Quantitative Finance	en_US
dc.relation.isbasedon	http://dx.doi.org/10.1080/14697680601026998	en_US
dc.rights	This is an author-created, un-copyedited version of an article accepted for publication in Quantitative Finance. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The definitive publisher-authenticated version is available online at http://dx.doi.org/10.1080/14697680601026998.	en_US
dc.subject.classification	Finance	en_US
dc.title	Semiparametric Diffusion Estimation and application to a Stock Market Index	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	8	en_US
utslib.for	010205 Financial Mathematics	en_US
utslib.for	150201 Finance	en_US
utslib.for	01 Mathematical Sciences	en_US
utslib.for	14 Economics	en_US
utslib.for	15 Commerce, Management, Tourism and Services	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
pubs.organisational-group	/University of Technology Sydney/Strength - QFRC - Quantitative Finance Research Centre
utslib.copyright.status	closed_access
pubs.consider-herdc	true	en_US
pubs.issue	1	en_US
pubs.volume	8	en_US

Abstract:

The analysis of diffusion processes in financial models is crucially dependent on the form of the drift and diffusion coefficient functions. A new model for a stock market index process is proposed in which the index is decomposed into an average growth process and an ergodic diffusion. The ergodic diffusion part of the model is not directly observable. A methodology is developed for estimating and testing the coefficient functions of this unobserved diffusion process. The estimation is based on the observations of the index process and uses semiparametric and non-parametric techniques. The testing is performed via the wild bootstrap resampling technique. The method is illustrated on S&P 500 index data.

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http://hdl.handle.net/10453/10256