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Markov decision process algorithms for wealth allocation problems with defaultable bonds

Part of: Mathematical finance

Published online by Cambridge University Press:  10 June 2016

Iker Perez ,
David Hodge  and
Huiling Le
Iker Perez*
Affiliation:
The University of Nottingham
David Hodge*
Affiliation:
The University of Nottingham
Huiling Le*
Affiliation:
The University of Nottingham
*
* Current address: Horizon Digital Economy Research, The University of Nottingham, Geospatial Building, Triumph Road, Nottingham NG7 2TU, UK. Email address: [email protected]
** Postal address: School of Mathematical Sciences, The University of Nottingham, University Park, Nottingham NG7 2RD, UK.
** Postal address: School of Mathematical Sciences, The University of Nottingham, University Park, Nottingham NG7 2RD, UK.
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Abstract

In this paper we are concerned with analysing optimal wealth allocation techniques within a defaultable financial market similar to Bielecki and Jang (2007). We study a portfolio optimization problem combining a continuous-time jump market and a defaultable security; and present numerical solutions through the conversion into a Markov decision process and characterization of its value function as a unique fixed point to a contracting operator. In this paper we analyse allocation strategies under several families of utility functions, and highlight significant portfolio selection differences with previously reported results.

Keywords

Portfolio optimizationdefaultable bondMarkov decision process

MSC classification

Primary: 91G10: Portfolio theory
Secondary: 90C40: Markov and semi-Markov decision processes
Type
Research Article
Information
Advances in Applied Probability , Volume 48 , Issue 2 , June 2016 , pp. 392 - 405
Copyright
Copyright © Applied Probability Trust 2016 

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