Model Designing for Prediction of Future Cash Flow By Using Exploratory Research Method and Experts Survey

The purpose of this research is to achieve an optimal model to predict future cash flow in firms accepted on Tehran Stock Exchange. So, the information of 250 companies during 2004 to 2016 were considered. At first, by using exploratory research and an experts survey, effective variables were identified. These variables are divided into two groups, firm operation based (Sale growth rate, Life cycle and financial leverage) and market and economy based (sanctions, business cycles and currency fluctuation) and they added to BCN model and the model estimated with generalized momentsstep by step. By considering these variables, the optimal and final model provided the least predictive error. Then, the effect of life cycle on future cash flow prediction of firms was analyzed and found that mature firms have less future cash flow prediction error than growing or declining ones. This conclusion implies that, considering the effective variables can lead to increase in the accuracy and reduce the forecasting error. In the other hand, the inclusion of companies in different life cycles can be effective in predicting their cash flow. Therefore, considering the heterogeneity of firms can also effective on prediction of future cash flow.