Abstract
This work has as objective the genetic algorithm application in cash balance policies definition. This financial problem was first treated by Baumol (1952) and Tobin (1956) which used deterministic models of inventory control applied to enterprises' cash balance. The authors drew a parallel between cash balance and assets inventory for minimizing cash balance's costs. Later, Miller and Orr (1966) improve the approach using a stochastic model which no more defines the cash balance ideal level, but a fluctuation band. Despite of that, the models show only one option of investment against cash. This work proposes a methodology based on evolutive models, with genetic algorithm, to optimize cash balance using the assumptions in literature. For this simulations are used in the model support and validation. The results show that genetic algorithm can be very useful in optimal cash level parameters definition, showing promising results in this problem field. The work letting futures perspectives in better application of genetic algorithms in cash balance optimization problem.
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