A deep learning analysis of the KOSPI’s directions
Woosik Lee1
1Department of Information Statistics, Anyang University
Correspondence to: Woosik Lee
Adjunct faculty, Department of Information Statistics, Anyang University, Gyeonggi-do 14028, Korea. E-mail: woosiklee@hotmail.com
Adjunct faculty, Department of Information Statistics, Anyang University, Gyeonggi-do 14028, Korea. E-mail: woosiklee@hotmail.com
Received January 17, 2017; Revised March 2, 2017; Accepted March 10, 2017.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
- Abstract
- Since Google’s AlphaGo defeated a world champion of Go players in 2016, there have been many interests in the deep learning. In the financial sector, a Robo-Advisor using deep learning gains a significant attention, which builds and manages portfolios of financial instruments for investors.In this paper, we have proposed the a deep learning algorithm geared toward identification and forecast of the KOSPI index direction,and we also have compared the accuracy of the prediction.In an application of forecasting the financial market index direction, we have shown that the Robo-Advisor using deep learning has a significant effect on finance industry. The Robo-Advisor collects a massive data such as earnings statements, news reports and regulatory filings, analyzes those and recommends investors how to view market trends and identify the best time to purchase financial assets. On the other hand, the Robo-Advisor allows businesses to learn more about their customers, develop better marketing strategies, increase sales and decrease costs.
- Keywords : Artificial intelligence, deep learning, FinTech, Robo-Advisor, technical analysis
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