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Open Access Article
1 - Designing Native Decision-Making Model for Selecting Venture Capital Investment in Emerging Companies
Mohammadreza Radfar Gholamreza Zomorodian Mansoureh Aligholi Mehrzad Minouei Farhad HanifiVenture capital companies play an important role in the economy of countries and greatly influences economic and employment growth. VC is the provision of capital for companies and entrepreneurs that is prone to leaping and growing value and, of course, a lot of risk. H MoreVenture capital companies play an important role in the economy of countries and greatly influences economic and employment growth. VC is the provision of capital for companies and entrepreneurs that is prone to leaping and growing value and, of course, a lot of risk. However, the volume of venture capital in our country is far less than the economic capacity. Many of analysts consider having no model for venture capital in our country as the main reason for this. Therefore, the present study by the qualitative method aims to design decision-making native model for selecting venture capital investment in emerging companies. To achieve this goal, by collecting qualitative data through literature reviews and having deep interview with experts and venture capital firms, a native decision-making model for selecting venture capital in emerging companies is presented. The methodology of this research based on purpose, is fundamental and through the qualitative methods, thematic analysis method is used. Purposeful sampling method is used and interviewing experts continued to theoretical saturation level that means the number of selected samples includes 16 elites. The native decision-making model for selecting venture capital in emerging companies presented in this research has 16 main themes and 86 sub-themes. Manuscript profile -
Open Access Article
2 - Presenting an Explanatory Model of Stock Price Using Deep Learning Algorithm
Mojtaba Bavaghar Zaeimi Gholamreza Zomorodian Mehrzad Minooee Amirreza KeyghobadiThis study aimed to present an explanatory model of stock price using deep learning algorithm for companies listed in the Tehran Stock Exchange. In this study, a deep learning network was used to predict stock prices. The study was applied-developmental research in term MoreThis study aimed to present an explanatory model of stock price using deep learning algorithm for companies listed in the Tehran Stock Exchange. In this study, a deep learning network was used to predict stock prices. The study was applied-developmental research in terms of purpose. To test the research questions, accounting data were prepared from 2011 to 2020 and input variables were calculated based on it for the model. The method of systematic elimination sampling has been used in this study. The results indicated that the precisions of prediction has a high precisions in the deep learning model. The proposed algorithm was reviewed according to its prediction accuracy and modeling cost. According to the data volume, it was found that the prediction accuracy in the deep learning model has a relative superiority and the diagram of performance characteristic and AUC criteria also showed this superiority in detection power. Manuscript profile
List of Articles Gholamreza Zomorodian
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