Print Email Facebook Twitter Accurate and Robust Numerical Methods for the Dynamic Portfolio Management Problem Title Accurate and Robust Numerical Methods for the Dynamic Portfolio Management Problem Author Cong, F. Oosterlee, C.W. Faculty Electrical Engineering, Mathematics and Computer Science Department Delft Institute of Applied Mathematics Date 2016-03-03 Abstract This paper enhances a well-known dynamic portfolio management algorithm, the BGSS algorithm, proposed by Brandt et al. (Review of Financial Studies, 18(3):831–873, 2005). We equip this algorithm with the components from a recently developed method, the Stochastic Grid Bundling Method (SGBM), for calculating conditional expectations. When solving the first-order conditions for a portfolio optimum, we implement a Taylor series expansion based on a nonlinear decomposition to approximate the utility functions. In the numerical tests, we show that our algorithm is accurate and robust in approximating the optimal investment strategies, which are generated by a new benchmark approach based on the COS method (Fang and Oosterlee, in SIAM Journal of Scientific Computing, 31(2):826–848, 2008). Subject dynamic portfolio managementsimulation methodleast-square regressionTaylor expansionFourier cosine expansion method To reference this document use: http://resolver.tudelft.nl/uuid:920add41-aaad-4ae7-be75-c3afc4acf61b Publisher Springer ISSN 0927-7099 Source https://doi.org/10.1007/s10614-016-9569-0 Source Computational Economics, 2016 Part of collection Institutional Repository Document type journal article Rights © 2016 The Author(s)This article is published with open access at Springerlink.com Files PDF Cong_2016.pdf 571.91 KB Close viewer /islandora/object/uuid:920add41-aaad-4ae7-be75-c3afc4acf61b/datastream/OBJ/view