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Investment Reluctance in Supply Chains: An Agent-Based Real Options Approach
Leibniz Institute of Agricultural Development in Central and Eastern Europe (IAMO), Halle, Germany
Leibniz Institute of Agricultural Development in Central and Eastern Europe (IAMO), Halle, Germany
Department for Agricultural Economics and Rural Development, Faculty of Agricultural Sciences, University of Goettingen, Gottingen, Germany
- 1 Leibniz Institute of Agricultural Development in Central and Eastern Europe (IAMO), Halle, Germany
- 2 Leibniz Institute of Agricultural Development in Central and Eastern Europe (IAMO), Halle, Germany
- 3 Department for Agricultural Economics and Rural Development, Faculty of Agricultural Sciences, University of Goettingen, Gottingen, Germany
Journal of Mathematical Finance·Volume 03 (2013)·Pages 1–10·Published 29 April 2013·DOI10.4236/jmf.2013.32A001
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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 interme diate product with each other on a spot market, and optimal investment strategies can be identified.
KeywordsReal OptionsSupply ChainAgent-Based ModelsGenetic Algorithms
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