In this paper, the stock portfolio of active companies listed on the Tehran Stock Exchange is optimized based on the combined model of omega ratio and mean-variance Markowitz (MVOF). For this purpose, 480 companies listed on the Tehran Stock Exchange during the years 13
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In this paper, the stock portfolio of active companies listed on the Tehran Stock Exchange is optimized based on the combined model of omega ratio and mean-variance Markowitz (MVOF). For this purpose, 480 companies listed on the Tehran Stock Exchange during the years 1390 to 1399 were selected and based on the input data, the companies were filtered. Hence a combined method consisting of trading rules optimization method based on technical analysis (6 indicators RSI, ROC, SMA, EMA, WMA and MACD) and two-level collective learning machine (SVM, RF, BN, MLP and KNN) for Data training and purchase signal presentation were addressed. Therefore, 85 companies were selected to optimize the stock portfolio. To teach the data, 85 companies filtered by the combined method were used and the number of different classes with 50 learners was used. The results show that using the OF model compared to the MVF model has the highest stock portfolio returns during the years 1395 to 1399. While the MVF model has the lowest investment risk. As a result, by combining the above models, the stock portfolio return in this method is much higher than other methods. While the investment risk was lower. Therefore, if the MVOF model is used, the return on the stock portfolio will increase and the investment risk in it will decrease.
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