Mean Variance Optimization of Non–Linear Systems and Worst–case Analysis
نویسندگان
چکیده
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 based 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 optimal expected performance in a stochastic setting. Both approaches are used with a macroeconomic policy model to illustrate relative performance, robustness and trade-offs between the strategies. JEL Classification Codes: C61, E43 ∗Department of Computing, Imperial College, London SW7 2AZ †Corresponding author. E-mail: [email protected], tel: +44-20-7594-8345. ‡Goethe University Frankfurt, Frankfurt am Main, Germany 1
منابع مشابه
Mean and variance optimization of non-linear systems and worst-case analysis
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 based on expected value optimization and worst-case robustness. The latter is a minimax strategy and ensures opt...
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