Cheng Zhao¹, Shuyi Yang², Chu Qin³, Jie Zhou⁴, Longxiang Chen^5,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 477-491, 2023, DOI:10.32604/cmc.2023.034933

Abstract Rule-based portfolio construction strategies are rising as investment demand grows, and smart beta strategies are becoming a trend among institutional investors. Smart beta strategies have high transparency, low management costs, and better long-term performance, but are at the risk of severe short-term declines due to a lack of Risk Control tools. Although there are some methods to use historical volatility for Risk Control, it is still difficult to adapt to the rapid switch of market styles. How to strengthen the Risk Control management of the portfolio while maintaining the original advantages of smart beta has become a new issue of… More >

Omer Berat Sezer^*, Ahmet Murat Ozbayoglu

Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 323-334, 2020, DOI:10.31209/2018.100000065

Abstract Even though computational intelligence techniques have been extensively utilized in financial trading systems, almost all developed models use the time series data for price prediction or identifying buy-sell points. However, in this study we decided to use 2-D stock bar chart images directly without introducing any additional time series associated with the underlying stock. We propose a novel algorithmic trading model CNN-BI (Convolutional Neural Network with Bar Images) using a 2-D Convolutional Neural Network. We generated 2-D images of sliding windows of 30-day bar charts for Dow 30 stocks and trained a deep Convolutional Neural Network (CNN) model for our… More >