MATEC Web of Conferences
Volume 54, 20162016 7th International Conference on Mechanical, Industrial, and Manufacturing Technologies (MIMT 2016)
|Number of page(s)||5|
|Section||Computer information science and Its Applications|
|Published online||22 April 2016|
Forecasting KOSPI using Elman network
Department of Computer Science and Engineering, Sogang University, Seoul 121-742, Korea
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.
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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