The volatility structure of the fixed income market under the HJM framework: A nonlinear filtering approach

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dc.contributor.author Chiarella, C
dc.contributor.author Hung, H
dc.contributor.author To, T
dc.date.accessioned 2010-05-28T09:42:27Z
dc.date.issued 2009-01
dc.identifier.citation Computational Statistics and Data Analysis, 2009, 53 (6), pp. 2075 - 2088
dc.identifier.issn 0167-9473
dc.identifier.other C1 en_US
dc.identifier.uri http://hdl.handle.net/10453/8322
dc.description.abstract The dynamics for interest rate processes within the well-known multi-factor Heath, Jarrow and Morton (HJM) specification are considered. Despite the flexibility of and the notable advances in theoretical research about the HJM model, the number of empirical studies of it is still very sparse. This paucity is principally due to the difficulties in estimating models in this class, which are not only high-dimensional, but also nonlinear and involve latent state variables. The estimation of a fairly broad class of HJM models as a nonlinear filtering problem is undertaken by adopting the local linearization filter, which is known to have some desirable statistical and numerical features, so enabling the estimation of the model via the maximum likelihood method. The estimator is then applied to the US, the UK and the Australian markets. Different two- and three-factor models are found to be the best for each market, with the factors being the level, the slope and the twist effect. The contribution of each factor towards overall variability of the interest rates and the financial reward each factor claims are found to differ considerably from one market to another.
dc.publisher Elsevier
dc.relation.hasversion Accepted manuscript version
dc.relation.hasversion NOTICE: this is the author’s version of a work that was accepted for publication in Computational Statistics & Data Analysis. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computational Statistics & Data Analysis, [Volume 53, Issue 6, 15 April 2009, Pages 2075–2088] DOI#http://dx.doi.org/10.1016/j.csda.2008.07.036
dc.relation.isbasedon 10.1016/j.csda.2008.07.036
dc.title The volatility structure of the fixed income market under the HJM framework: A nonlinear filtering approach
dc.type Journal Article
dc.parent Computational Statistics and Data Analysis
dc.journal.volume 6
dc.journal.volume 53
dc.journal.number 6 en_US
dc.publocation Netherlands en_US
dc.identifier.startpage 2075 en_US
dc.identifier.endpage 2088 en_US
dc.cauo.name BUS.School of Finance and Economics en_US
dc.conference Verified OK en_US
dc.for 0104 Statistics
dc.personcode 030348
dc.personcode 716350
dc.percentage 100 en_US
dc.classification.name Statistics en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords en_US
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Business
pubs.organisational-group /University of Technology Sydney/Faculty of Business/Finance
pubs.organisational-group /University of Technology Sydney/Strength - Quantitative Finance
utslib.copyright.status Open Access
utslib.copyright.date 2015-04-15 12:23:47.074767+10


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