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Improving Stock Price Prediction Models Using Sentiment Analysis

عنوان مقاله: Improving Stock Price Prediction Models Using Sentiment Analysis
شناسه ملی مقاله: CSIEM01_550
منتشر شده در اولین کنفرانس بین المللی چالش ها و راهکارهای نوین در مهندسی صنایع و مدیریت و حسابداری در سال 1399
مشخصات نویسندگان مقاله:

Mohammadreza Ghadimpoor, - Financial Engineering Group, Faculty of Industrial Engineering, K. N. Toosi University of Technology, Tehran,Iran
Ehsan Bagheri, - Financial Engineering Group, Faculty of Industrial Engineering, K. N. Toosi University of Technology, Tehran,Iran
Seyed Babak Ebrahimi - Assistant Professor at the Department of Industrial Engineering, K. N. Toosi University of Technology, Tehran,Iran

خلاصه مقاله:
With regards to behavioural financial theory, it is necessary to consider psychological aspects of investors when one wants to predict stock price. Everyday investors deal with various social media, blogs, news etc. Hence, these are appropriate resources for measuring investors sentiment leading to better prediction for what will happen in the future. The aim of this article is to use sentiment analysis and acquire sentiment index. Besides, we want to indicate the relationship between sentiment index and stock price movement by using LSDV regression. We select five companies from Dow Jones Industrial Average index and measure sentiment index. Then combine our sentiment index with historical data of price and volume of these five stocks for prediction. Results show that there is a significant relationship between stock price and mental status of investors. Also our propose model can define fluctuations of stock price by 91 percent. After that we prove that there is difference in relationship between each company individually and its own sentiment index.

کلمات کلیدی:
Behavioral finance, Opinion mining, Sentiment analysis, Text mining

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1045784/