Chapter 8. Advances in Numerical Dynamic Programming and New Applications

Dynamic programming is the essential tool in dynamic economic analysis. Problems such as portfolio allocation for individuals and optimal economic growth are typical examples. Numerical methods typically approximate the value function. Recent work has focused on making numerical methods more stable, and more efficient in its use of information. This chapter presents two examples where numerical dynamic programming is applied to high-dimensional problems from finance and the integration of climate and economic systems.

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Year of publication:	2014
Authors:	Cai, Yongyang ; Judd, Kenneth L.
Published in:	Handbook of computational economics : volume 3. - Amsterdam : Elsevier, ISBN 0-444-89857-3. - 2014, p. 479-516
Subject:	Numerical dynamic programming \| Value function iteration \| Shape preservation \| Hermite interpolation \| Parallel computing \| Optimal growth \| Dynamic portfolio optimization \| Climate change \| Stochastic IAM \| Theorie \| Theory \| Mathematische Optimierung \| Mathematical programming \| Dynamische Optimierung \| Dynamic programming \| Portfolio-Management \| Portfolio selection \| Klimawandel

Type of publication:	Article
Language:	English
Other identifiers:	10.1016/B978-0-444-52980-0.00008-6 [DOI]
Classification:	C61 - Optimization Techniques; Programming Models; Dynamic Analysis ; C63 - Computational Techniques ; G11 - Portfolio Choice ; Q54 - Climate; Natural Disasters ; D81 - Criteria for Decision-Making under Risk and Uncertainty
Source:	ECONIS - Online Catalogue of the ZBW

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