Fuzzy Linear Regression Method for Analyzing Profits and Stock Returns in Selected Industries in Tehran Stock Exchange

In recent years, use of fuzzy linear regression has expanded significantly in economics, accounting and financial mathematics. In this type of regression, for data analysis, there is no need to meet the prerequisites that are required in normal linear regression. In addition, it is necessary to solve a linear programming problem to find coefficients of this type of regression. Since in examining the status of stability and the cash and accrual components of companies’ profits, the calculation of accruals is based on forecasts and estimates and is measured by less reliability, so implied greater stability of profit due to its cash component. Among the cases that have an accrual basis, the non-objectivity of the amount, especially the cash amount of the earnings, is very important for the future profitability. In this study, focusing on profit cash components and the stability, the profitability of the company and its efficiency compared to the accrual basis are investigated using fuzzy linear regression. In the issue of technical analysis and to check profits sustainability, a sample of four selected industries, vehicle manufacturing, pharmaceuticals, basic metals, and ceramic tiles during the years 2011-2016, has been selected in the Tehran Stock Exchange market. In this study, sign constraints are added to the set of constraints in the main linear programming problem so obtained solutions can be interpreted and justified. The results confirmed the hypothesis “cash components of profit have more stability of profit than accrual components”, but the hypothesis “more stability of profit due to cash components of profit has a greater impact on the amount of cash and the rights Stockholders” and also the hypothesis” the profit expectations implicit in the stock price fully reflect the stability of the profit related to the cash components of the profit”, were not confirmed.