A Survey on Machine Learning for Stock Price Prediction: Algorithms and Techniques

Stock market trading is an activity in which investors need fast and accurate information to make effective decisions. Since many stocks are traded on a stock exchange, numerous factors influence the decision-making process. Moreover, the behaviour of stock prices is uncertain and hard to predict. For these reasons, stock price prediction is an important process and a challenging one. This leads to the research of finding the most effective prediction model that generates the most accurate prediction with the lowest error percentage. This paper reviews studies on machine learning techniques and algorithm employed to improve the accuracy of stock price prediction.

• Publication year

  2020

• Venue

  International Conference on Finance, Economics, Management and IT Business

• Publication date

  2020-05-06

• Fields of study

  Business, Computer Science

• Identifiers
  DOI 10.5220/0009340700630071
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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