Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/171341 
Year of Publication: 
2013
Citation: 
[Journal:] Journal of Mathematical Finance [ISSN:] 2162-2442 [Volume:] 3 [Issue:] 2A [Publisher:] Scientific Research [Place:] Wuhan, China [Year:] 2013 [Pages:] 1-10
Publisher: 
Scientific Research, Wuhan, China
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.
Subjects: 
real options
supply chain
agent-based models
genetic algorithms
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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