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H. Dawid, “Adaptive Learning by Genetic Algorithms: Analytical Results and Applications to Economic Models,” Lecture Notes in Economics and Mathematical Systems, No. 441, Springer, Berlin, 1996.

has been cited by the following article:

• TITLE: Investment Reluctance in Supply Chains: An Agent-Based Real Options Approach

  AUTHORS: Alfons Balmann, Karin Kataria, Oliver Musshoff

  KEYWORDS: Real Options; Supply Chain; Agent-Based Models; Genetic Algorithms

  JOURNAL NAME: Journal of Mathematical Finance, Vol.3 No.2A, April 29, 2013

  ABSTRACT: This paper shows how agent-based stochastic approaches can provide a complementary and more flexible approach to study investment incentives and price dynamics in a real options framework. We particularly study the case of two-stage production chains in which one sector produces an intermediate product and the other the final product, and the intermediate product is traded on the spot market. An agent-based competitive model using a genetic algorithm allows us to explicitly model the behaviors and interactions of the firms competing in each subsector and trading the intermediate product with each other on a spot market, and optimal investment strategies can be identified.