The Journal of the Convergence on Culture Technology (문화기술의 융합)

The International Promotion Agency of Culture Technology (국제문화기술진흥원)
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An Implementation of Stock Investment Service based on Reinforcement Learning

강화학습 기반 주식 투자 웹 서비스

  • 박정연 (선문대학교 컴퓨터융합전자공학과) ;
  • 홍승식 (선문대학교 컴퓨터공학부) ;
  • 박민규 (선문대학교 컴퓨터융합전자공학과) ;
  • 이현 (선문대학교 컴퓨터공학부)
  • Received : 2021.10.19
  • Accepted : 2021.11.02
  • Published : 2021.11.30
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Abstract

As economic activities decrease, and the stock market decline due to COVID-19, many people are jumping into stock investment as an alternative source of income. As people's interest increases, many stock price analysis studies are underway to earn more profits. Due to the variance observed in the stock markets, it is necessary to analyze each stock independently and consistently. To solve this problem, we designed and implemented models and services that analyze stock prices using a reinforcement learning technique called Asynchronous Advantage Actor-Critic(A3C). Stock market data reflected external factors such as government bonds and KOSPI (Korea Composite Stock Price Index) as well as stock prices. Our proposed work provides a web service with a visual representation of predictions of stocks and stock information through which directions are given to investors to make safe investments without analyzing domestic and foreign stock market trends.

코로나-19로 인해 경제 활동이 낮아지고 주식 시장이 침체하면서 주식 투자를 통해 또 다른 소득을 마련하기 위해 많은 사람이 주식 시장에 뛰어들고 있다. 사람들의 관심이 높아지면서 더 많은 수익을 얻기 위한 주가 분석 연구가 많이 진행되고 있다. 주가는 종목별 변동의 흐름이 다르므로 각 주가 종목별로 독립적이며 일관적으로 분석할 필요가 있다. 이러한 문제를 해결하고자 본 논문에서는 강화학습 기법 중 하나인 Asynchronous Advantage Actor-Critic(A3C)를 이용하여 주가를 분석할 수 있는 모델 및 서비스를 설계 및 구현하였다. 주식 시장 데이터로 종목별 주가 및 국채, 코스피와 같은 외부 요인들을 반영하였다. 또한 웹페이지 제작을 통해 시각화한 정보를 제공하여 투자자들이 투자 기업에 대한 재무제표를 비롯하여 국내외 경제 및 정치의 흐름을 모두 분석하지 않고도 안전한 투자를 할 수 있도록 서비스를 제공한다.

Keywords

Acknowledgement

본 연구는 과학기술정보통신부 및 정보통신기술진흥센터의 SW중심대학지원사업의 연구 결과로 수행되었음

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