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Stocks Market Trading Strategy Recommendation Using Experts’ Opinion Aggregation

Faryabi, Mohammad Mahdi | 2023

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 56054 (19)
  4. University: Sharif University of Technology
  5. Department: Computer Engineering
  6. Advisor(s): Fazli, Mohammad Amin
  7. Abstract:
  8. Investors highly value the ability to predict the behavior of the capital market. Over time, various methods have been introduced to forecast the future of this market and anticipate its movements. A novel approach to achieving this is by developing data-driven decision support systems that can assist investors in making informed trading decisions. The opinions of experts play a crucial role in shaping people's perception of the market, which ultimately affects its final behavior. In this study, we have created a decision support system that can help investors by considering the complexities and meaningful relationships between different aspects of the problem. We have developed frameworks based on people's perception of market behavior and utilized machine learning techniques to construct behavioral prediction models. Our goal has been to provide suitable buy and sell offers for transactions in the capital market. To evaluate our proposed method, we have employed various techniques, including comparing its efficiency with that of top experts. By doing so, we hope to provide investors with a reliable tool for predicting market behavior and making informed investment decisions
  9. Keywords:
  10. Growds Wisdom ; Machine Learning ; Decision Making Support System ; Opinion Aggregation ; Experts' Prediction ; Capital Market

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