Stochastic Investment Decision Making with Dynamic Programming

Proper investment decision making is key to success for every investor in their efforts to keep pace with the competitive business environment. Mitigation of exposure to risk plays a vital role, since investors are now directly exposed to the uncertain decision environment. The uncertainty (and risk) of an investment is increasing with the increased number of competing investors entering to market. As a result, the expected return on investment (ROI) of a decision quite often carries a high degree of uncertainty. Our objective is to formulate a dynamic programming mathematical model for the investment decision with incorporating this uncertainty in a probabilistic manner. Policy iteration algorithm of the dynamic programming is adopted to solve the model. Our simulation result shows that the algorithm is able to help us in taking optimum investment decision.