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Forecasting KOSPI using Elman network
- Ahn, Hongchul;
- Hong, Hotak;
- Nang, Jongho;
- Kim, Saejoon
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0초록
Due to the non-stationary nature of stock market index, making a prediction on its course is a truly challenging task. Research has been actively conducted to predict stock market indices by means of machine learning in recent years. In our research, we made a prediction of KOSPI for one week based on Elman Network. Based on the predictive result, we ran a simulation from which we obtained 3.16% yield over a period of one year. In this paper, we describe how we exploited Elman network to make predictions on stock markets, then we propose a method for using the predictive values for investment.
- 제목
- Forecasting KOSPI using Elman network
- 저자
- Ahn, Hongchul; Hong, Hotak; Nang, Jongho; Kim, Saejoon
- 발행일
- 2016-04-22
- 유형
- Proceedings Paper
- 저널명
- MATEC Web of Conferences
- 권
- 54