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. (TU Delft Numerical Analysis) Oosterlee, C.W. (TU Delft Numerical Analysis; Centrum Wiskunde & Informatica (CWI)) 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 managementFourier cosine expansion methodLeast-square regressionSimulation methodTaylor expansion To reference this document use: http://resolver.tudelft.nl/uuid:e92a38d0-27f9-4598-9f7f-3fce78f63c9f DOI https://doi.org/10.1007/s10614-016-9569-0 ISSN 0927-7099 Source Computational Economics, 49 (3), 433-458 Part of collection Institutional Repository Document type journal article Rights © 2016 F. Cong, C.W. Oosterlee Files PDF 12339502.pdf 817.85 KB Close viewer /islandora/object/uuid:e92a38d0-27f9-4598-9f7f-3fce78f63c9f/datastream/OBJ/view