| Autor: |
Ahn Hongchul, Hong Hotak, Nang Jongho, Kim Saejoon |
| Jazyk: |
English<br />French |
| Rok vydání: |
2016 |
| Předmět: |
|
| Zdroj: |
MATEC Web of Conferences, Vol 54, p 05007 (2016) |
| Druh dokumentu: |
article |
| ISSN: |
2261-236X |
| DOI: |
10.1051/matecconf/20165405007 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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