Abstract/Details

Dynamic portfolio management: An approximate linear programming approach


2005 2005

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Abstract (summary)

Portfolio management is one of the central subjects of modern finance. However, in most cases it is difficult to determine optimal strategies for intertemporal portfolio management problems. In this thesis, we formulate a class of intertemporal portfolio management problems in the continuous-time framework, and offer a new computational approach, which we call approximate linear programming, to this class of portfolio problems. We start by deriving the corresponding Hamilton-Jacobi-Bellman equation, and transform it into an equivalent linear program. Since this equivalent linear program is intractable due to an infinite number of constraints, we use basis function approximations and constraint-sampling techniques to obtain a tractable approximating linear program. Finally we present efficient algorithms to solve the approximate linear program. Our approximate linear programming approach has four major features: it scales well with dimensions; it has a priori performance bounds; it can deal with both complete and incomplete markets; and it provides an approximate upper bound on the optimal value. We also present case studies to demonstrate the effectiveness of our algorithm, particularly for large portfolios as illustrated in a 10-dimensional problem.

Indexing (details)


Subject
Statistics;
Operations research
Classification
0463: Statistics
0796: Operations research
Identifier / keyword
Applied sciences; Pure sciences; Portfolio management
Title
Dynamic portfolio management: An approximate linear programming approach
Author
Han, Jiarui
Number of pages
69
Publication year
2005
Degree date
2005
School code
0212
Source
DAI-B 66/08, Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
ISBN
9780542285929, 0542285924
Advisor
Lai, Tze Leung; Roy, Benjamin Van
University/institution
Stanford University
University location
United States -- California
Degree
Ph.D.
Source type
Dissertations & Theses
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
3186347
ProQuest document ID
305390559
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
http://search.proquest.com/docview/305390559
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