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Portfolio management using partially observable Markov decision process

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dc.contributor.authorZahedi, Ramin, author
dc.contributor.authorChong, Edwin Kah Pin, author
dc.date.accessioned2007-01-03T05:32:42Z
dc.date.available2007-01-03T05:32:42Z
dc.date.issued2006
dc.description.abstractPortfolio theory is concerned with how an investor should divide his wealth among different securities. This problem was first formulated by Markowitz in 1952. Since then, other more sophisticated formulations have been introduced. However, practical issues like transactions costs and their effects on the portfolio choice in multiple stages have not been widely considered. In our work, we show that the portfolio management problem is appropriately formulated as a Partially Observable Markov Decision Process. We use a Monte Carlo method called "rollout" to approximate an optimal strategy for making decisions. To capture the behavior of stock prices over time, we use two well known models.
dc.description.award2nd place, IS&T Graduate Group.
dc.format.mediumborn digital
dc.format.mediumStudent works
dc.format.mediumposters
dc.identifierSTUFISTC2006100018POST
dc.identifier.urihttp://hdl.handle.net/10217/526
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartofStudent Research Posters
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectstock price behavior
dc.subjectPOMDP
dc.subjectpartially observable Markov decision process
dc.subjectportfolio management
dc.subjectportfolio theory
dc.subjectrollout
dc.titlePortfolio management using partially observable Markov decision process
dc.typeText
thesis.degree.disciplineEngineering

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