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Prediction of Financial Markets Using Combination of Artificial Intelligence and Technical Analysis

| 2022

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 55842 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Haji, Alireza
  7. Abstract:
  8. Generally, nowadays, machine learning methods are used in many different areas for their superiority over other methods of prediction. Although being a tough task, stock market prediction with machine learning approaches is being spread due to satisfying results published ever yday. Machine learning methods usually use varied kinds of data ,including structured data such as market data, technical indicators and some fundamental data as well as unstructured one entailing text and graph data in order to enhance their predictability capacity. In this thesis we aimed to find out more about the importance and the contribution of structured data in prediction and we tried to attain a framework relatively generalizable so that traders would be able to predict market properly without much concern about case sensitivity. Apart from prediction results we tried to do feature engineering so as to comprehend about features importance and effectiveness. besides, we manipulated different parts of our proposed framework in order to see effects of various steps on the final result. Our rsults were promising and inspirational and we were able to gain f1score of 95.1 on Microsoft and 90.0 on Apple both of which were our out of sample data. and our input data did not include any data of these two stocks. Also we calculated profit we could have gained if we had made use of this strategy in our trading. Results were 1159 and 1357 percent profit for microsoft and apple respectively, during about ten years, which implies that the framework has been completely successful
  9. Keywords:
  10. Artificial Intelligence ; Machine Learning ; Technical Analysis ; Fundamental Analysis ; Forecasting ; Market Prediction ; Financial Market

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