AbstractIn this paper, three approaches are presented for generating scenario trees for financial portfolio problems. These are based on simulation, optimization and a hybrid simulation/optimization method. In the simulation approach, the price scenarios at each time period are generated as the centroids of random scenario simulations generated sequentially or in parallel. In the optimization procedure, a limited number of discrete outcomes which satisfy specified statistical properties are generated by solving either a sequence of nonlinear optimization models (one at each node of the scenario tree) or one large optimization problem. In the hybrid approach, the optimization problem is reduced in size by fixing some variables to values obtained by simulations. These procedures are back-tested on a set of historical data and computational results are presented.
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Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 2001 with number 124.
Date of creation: 01 Apr 2001
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