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 AJIBM  Vol.8 No.3 , March 2018
Selection of Investment Basis Using Neural Networks in Stock Exchange
Abstract: A generalization is considered on the standard Marvowitz mean-variance model, which includes some limitative limbs. These restrictions guarantee the investment in a certain number of assets and limit the amount of capital that must be invested in any asset (stock). When the Markovitz mean-variance model is considered, the basket selection problem is a quadratic programming problem. But if this model is generalized with limitations, then the basket selection problem will be transformed into a quadratic programming and numerical design. In this recent model, there is no algorithm and method that can solve the basket selection problem optimally. In this case, the use of the heuristic algorithm is essential. Here in this paper a special neural network model has been used. The Hopfield network has been used to optimize some of the other optimization problems and it is used to solve the portfolio selection problem.
Cite this paper: Kalani, E. , Elhami, A. , Kazem-Zadeh, R. and Kamrani, E. (2018) Selection of Investment Basis Using Neural Networks in Stock Exchange. American Journal of Industrial and Business Management, 8, 548-562. doi: 10.4236/ajibm.2018.83036.
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