List of Articles بازار سهام

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  1 - Sentiment analysis for stock market predection with deep neural network: A case study for international corporate stock database
  hakimeh mansour Saeedeh Momtazi Kamran Layeghi
  Emotional analysis is used as one of the main pillars in various fields such as financial management, marketing and economic changes forecasting in different countries. In order to build an emotion analyzer based on users' opinions on social media, after extracting impo More

  Emotional analysis is used as one of the main pillars in various fields such as financial management, marketing and economic changes forecasting in different countries. In order to build an emotion analyzer based on users' opinions on social media, after extracting important features between words by convolutional layers, we use LSTM layers to establish the relationship behind the sequence of words and extract the important features of the text. With discovery of new features extracted by LSTM, the ability of the proposed model to classify the stock values of companies increases. This article is based on the data of Nguyen et al. (2015) and uses only the emotional information of people in social networks to predict stocks. Given that we categorize each user's message into one of the emotional classes "Strong Buy", "Buy", "Hold", "Sell", "Strong Sell", this model can predict the stock value of the next day, whether it will be high or low. The proposed structure consisted of 21 layers of neural networks consisting of convolutional neural networks and long short-term memory network. These networks were implemented to predict the stock markets of 18 companies. Although some of the previously presented models have used for emotion analysis to predict the capital markets, the advanced hybrid methods have not been performed in deep networks with a good forecasting accuracy. The results were compared with 8 baseline methods and indicate that the performance of the proposed method is significantly better than other baselines. For daily forecasts of stocks changes, it resulted in 19.80% improvement in the prediction accuracy, compared with the deep CNN, and 24.50% and 23.94% improvement compared with the models developed by Nguyen et al. (2015) and Derakhshan et al. (2019), respectively. Manuscript profile
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  2 - Analysis of Factors Affecting Stock Selection Using Logarithmic Fuzzy Preference Programming Approach
  Daryush  Farid َAbolfazl Dehghani firoozabadi Davood Andalib Ardakani hamidreza mirzaei
  The stock market is especially important as a capital investment instrument both for the investor and for the investor. Stock markets are affected not only by large parameters but also by thousands of other factors. The high number and unknown factors affecting stock p More

  The stock market is especially important as a capital investment instrument both for the investor and for the investor. Stock markets are affected not only by large parameters but also by thousands of other factors. The high number and unknown factors affecting stock prices, as well as the complexity of the relationship between these factors and the stock price, have caused uncertainty in the field of investment. One of the tools to reduce uncertainty and the most important discussion of investing in the stock exchange is the selection of the stock portfolio optimally. In this study, through interviewing experts and reviewing existing documents, 6 main criteria for identifying the optimal stock portfolio selection were identified. Using logistic fuzzy preferential programming, weighing these criteria and, finally, weighting the indexes related to We defined each criterion. The results show that the criteria for profitability, efficiency and risk are the most important criteria in choosing stock portfolios Manuscript profile