Determinants of Venture Capital on the Tehran Stock Exchange

The present study was applied in terms of purpose and In terms of the descriptive research method, it is a survey with a comparative causal approach. A number of 100 companies listed on the Tehran Stock Exchange in 2014 to 2019 were selected as a sample. Data were collected from the databases of the Central Bank of Iran, Statistics Center of Iran, Codal website, and WDI website and Tehran Stock Exchange website, and then analyzed using Excel, 9Eviews, and Matlab software. In this study, the determinants of venture capital on the Tehran Stock Exchange (capital volume, export volume, company tax, disclosure index, rule of law index, industry diversity, diversity of company life cycle stages, type of property, number of divisions and subsidiaries, company capital, company, size and company age) By studying the research literature and using neural network and fuzzy logic, a predictive model was created to determine the investment risk based on the determined indicators.. The classification model was presented using neural network without SOM supervision and fuzzy logic flexibility. The evaluation parameters of design, accuracy of the proposed ensemble classifier, mean error of the squares, and coefficient of explanation. The simulation results indicated that the performance of the proposed design compared to the classification by MLP neural network method was improved and the presented model based on the training provided predicted the status of capital with good accuracy.