Considering the investment decisions with real options games approach

The mix of games theory with the real options has been a dynamic range of exploration in the most recent decade. The engaging quality of the specialists for displaying aggressive speculation choices by blending ideas from both hypotheses is on account of a venture choice in a focused business sector can be seen, in its substance, as a “game” between firms. In this paper, we expand a model to consider finite horizon real option games under incomplete information with various parameters. In incomplete information games, firms' actions express significant information about profitability to contestants. The encapsulation of this information proposed original blocks in models with strategic interactions. This is because of circularity where best exercise decisions are based on previous decisions taken, which at a given time are quiet to be mentioned because about the dynamic programming principle. We expand an extended version of the Least Squares Monte Carlo algorithm to confront these results. The model can aid in understanding the relation between strategic optionality and information besides how this influences the best decision policy and its value results. We find the informational feature is of great significance for firms' best decision policy and optimization of project values.