چكيده به لاتين
Return and risk are two important and fundamental factors for decision making in the field of financial issues. Simultaneously with the development of methods for portfolio optimization, based on the Markowitz model, The need to know new methods to find the optimal capital portfolio has always been discussed by researchers and financial analysts. The present study was conducted with scientific objectives to find the optimal portfolio. One of the methods that is currently very popular among analysts and researchers in this field, Methods based on artificial intelligence, followed by methods aimed at reducing risk, It is like a measure of risk. In this research, an attempt has been made to find the optimal capital portfolio using the methods of value at risk and conditional value at risk with a new approach and a combination with fuzzy theory. But before that, for filtering and classifying a large number of shares, we have used different and widely used artificial intelligence algorithms to determine the positive class according to the features provided. In this study, shares were first selected with two approaches of industry diversity and high market depth. In the next stage, it enters the learning machines and according to the technical characteristics and indicators and efficiency, Classification has been done on them. The output of each method enters the random forest algorithm and forecasting is done by this algorithm. Finally, forecasters enter the risk-value and condition-risk value optimization model by either classification methods to form a portfolio. At the end of each of these methods and steps will be measured and compared with the actual market return. It should be noted that the values of confidence level in this study compared to 3 levels of 0.9 and 0.95 0.99 have been considered. After ranking the studied methods, We use the trainer criterion to evaluate the optimality of the created portfolios. Share data is daily and its time period is from the beginning of 1394 to the middle of 1398.
