EQUILIBRIUM IN STOCHASTIC OPTIMIZATION MODELS WITH ECONOMIC APPLICATIONS
Authors
Keywords
Stochastic linear quadratic model, optimization problem, Markov jump linear systems, generalized discrete-time Riccati equations, linear matrix inequality
Summary
The subject of this work is the application of a linear quadratic model which is a result of the stochastic modeling process in the economic field. A dynamic economic process is modeled, which occurs in conditions described by a stochastic differential equation. The dynamics of the process is subject to jump-like changes. Such systems are known as Markov jump linear systems. The target in the observed process is modeled through a functional which has to be minimized. The result is a linear quadratic stochastic model. The equilibrium search model is related to the numerical solution of a system of generalized discrete-time algebraic Riccati equations. Methods for finding the maximal solution to a system of discrete-time algebraic Riccati equations are investigated. Moreover, new methods and algorithms for computing of this maximal solution are proposed. The numerical characteristics of algorithms are analyzed in special cases of negative definite weighting matrices and indefinite weighting ones. Conclusions are derived of the applicability and efficiency of the proposed methods.
Pages: 28
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