ROLE OF DYNAMIC PROGRAMMING FOR DATA ANALYSIS & MATHEMATICAL APPLICATION
Dr. Brajesh Kumar
Investment decision, dynamic programming, uncertainty, Data Analysis, Mathematical Application.
Dynamic programming is a valuable mathematical method used to render a series of interrelated decisions. It calls for a standardized method to evaluate the best mix of decisions. Proper investment decision-making is vital to the investor's progress in their attempts to keep up with the dynamic market climate. Mitigation of risk management plays a critical function, because customers are already actively subjected to the volatile decision-making climate. The volatility (and risk) of an investment is growing with a growth in the amount of competitive investors joining the sector. As a consequence, the estimated return on investment (ROI) of a decision also contributes to a high degree of ambiguity. The goal is to devise a dynamic mathematical programming model for an investment decision, incorporating this complexity in a probabilistic manner. The Dynamic Programming Strategy Iteration algorithm is used to solve the problem. Our simulation test demonstrates that the algorithm is capable of enabling us to make an effective investment decision.