Please use this identifier to cite or link to this item:
|Title:||Hidden Markov models for financial optimization problems|
|Keywords:||Scenario generation;Asset pricing;Hidden Markov models;Extreme events;Stability;Conditional value at risk|
|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.|
|Appears in Collections:||Dept of Mathematics Research Papers|
Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.