Paper
Network techniques for solving asset diversification problems in finance

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Abstract

In this paper, we study a problem of asset diversification or dynamic portfolio selection arising in the field of finance. This problem is first formulated as a nonlinear mathematical program and is solved via a special-purpose computer code that exploits the underlying network structure. A second model for asset diversification is presented which is linear in the decision variables and is therefore much easier to solve computationally than the first formulation. On the other hand, the linear model produces solutions that are consistently inferior to those generated by the nonlinear program in terms of expected profit. This trade-off of accuracy versus efficiency is discussed and assessed for several sample problems. Extensive computational results are presented.

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Bruce L. Golden is Chairman of the Department of Management Science and Statistics at the University of Maryland. His research interests include network optimization, mathematical programming, and applied statistics, and he has published numerous articles in these fields. He is currently an Associate Editor of Networks, a member of ORSA's Long Range Planning Committee, and a member of ORSA's Transportation Science Dissertation Prize Committee. Dr. Golden received his B.A. from the University of Pennsylvania in Mathematics. Later he earned his M.S. and Ph.D. in Operations Research from M.I.T.

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