Timing of investments in oligopoly under uncertainty: A framework for numerical analysis
We present a modeling framework for the analysis of investments in an oligopoly market for a homogenous commodity. The demand evolves stochastically and the firms carry out investment projects in order to adjust their production cost functions or production capacities. The model is formulated as a discrete time state-space game where the firms use feedback strategies. The firms are assumed to move sequentially to ensure a unique Markov-perfect Nash equilibrium. Once the equilibrium has been solved, Monte Carlo simulation is used to form probability distributions for the firms' cash flow patterns and accomplished investments. Such information can be used to value firms operating in an oligopoly market. An example of the model is given in a duopoly market. The example illustrates the trade-off between the value of flexibility and economies of scale under competitive interaction.
investment analysis game theory uncertainty modeling real options