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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/3878

Title: Hidden Markov models for financial optimization problems
Authors: Roman, D
Mitra, G
Spagnolo, N
Keywords: Scenario generation
Asset pricing
Hidden Markov models
Extreme events
Stability
Conditional value at risk
Publication Date: 2009
Publisher: Oxford University Press
Citation: IMA Journal of Management Mathematics, 21(2): 111-129
Abstract: Many financial decision problems require scenarios for multivariate financial time series that capture their sequentially changing behaviour, including their extreme movements. We consider modelling financial time series by hidden Markov models (HMMs), which are regime-switching-type models. Estimating the parameters of an HMM is a difficult task and the multivariate case can pose serious implementation issues. After the parameter estimation, the calibrated model can be used as a scenario generator to describe the future realizations of asset prices. The scenario generator is tested in a single-period mean–conditional value-at-risk optimization problem for portfolio selection.
URI: http://imaman.oxfordjournals.org/cgi/content/abstract/dpp009
http://bura.brunel.ac.uk/handle/2438/3878
DOI: http://dx.doi.org/10.1093/imaman/dpp009
ISSN: 1471-678X
Appears in Collections:Mathematics
School of Information Systems, Computing and Mathematics Research Papers

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