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A Study on Stock Trend Determination in Stock Trend Prediction

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2020, 25(12), pp.35-44
  • DOI : 10.9708/jksci.2020.25.12.035
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : August 31, 2020
  • Accepted : November 19, 2020
  • Published : December 31, 2020

Lim, Chung-soo 1

1한국교통대학교

Accredited

ABSTRACT

In this study, we analyze how stock trend determination affects trend prediction accuracy. In stock markets, successful investment requires accurate stock price trend prediction. Therefore, a volume of research has been conducted to improve the trend prediction accuracy. For example, information extracted from SNS (social networking service) and news articles by text mining algorithms is used to enhance the prediction accuracy. Moreover, various machine learning algorithms have been utilized. However, stock trend determination has not been properly analyzed, and conventionally used methods have been employed repeatedly. For this reason, we formulate the trend determination as a moving average-based procedure and analyze its impact on stock trend prediction accuracy. The analysis reveals that trend determination makes prediction accuracy vary as much as 47% and that prediction accuracy is proportional to and inversely proportional to reference window size and target window size, respectively.

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