Mean variance optimization of non-linear systems and worst-case analysis

Panos Parpas, Berc Rustem, Volker Wieland and Stan Zakovic

No 2006/03, CFS Working Paper Series from Center for Financial Studies (CFS)

Abstract: In this paper, we consider expected value, variance and worst-case optimization of nonlinear models. We present algorithms for computing optimal expected values, and variance, based on iterative Taylor expansions. We establish convergence and consider the relative merits of policies beaded on expected value optimization and worst-case robustness. The latter is a minimax strategy and ensures optimal cover in view of the worst-case scenario(s) while the former is optimal expected performance in a stochastic setting. Both approaches are used with a macroeconomic policy model to illustrate relative performances, robustness and trade-offs between the strategies.

JEL-codes: C61 E43 (search for similar items in EconPapers)
Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:cfswop:200603

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