Forecasting Taiwan Capitalization Weighted Stock Index by Using Convolutional Neural Network

Chia Hung Liao, Te Lun Kao, Shyan Ming Yuan*

*此作品的通信作者

研究成果: Conference contribution同行評審

1 引文 斯高帕斯(Scopus)

摘要

Deep learning has been widely used in many research areas recently. One of the common applications is financial forecasting. Convolutional neural network (CNN), a class of deep learning, which is capable of capturing complex features from the images. In this paper, we proposed a method for forecasting Taiwan capitalization weighted stock index by using Xception, a CNN presented by Chollet, F from Google. Furthermore, with the labeling technique we proposed which aims to predict the median of the closing price of future 20, 30, or 40 days. Based on the results produced by each model, we propose a method to find the optimal trading strategy. Then, after the simulation based on trading the common ETFs in Taiwan which includes 0050.TW, 0056.TW, the promising results show that we can make more profits than those traditional trading strategies such as Buy and Hold and some technical indicators.

原文English
主出版物標題2nd IEEE Eurasia Conference on IOT, Communication and Engineering 2020, ECICE 2020
編輯Teen-Hang Meen
發行者Institute of Electrical and Electronics Engineers Inc.
頁面326-329
頁數4
ISBN(電子)9781728180601
DOIs
出版狀態Published - 23 10月 2020
事件2nd IEEE Eurasia Conference on IOT, Communication and Engineering, ECICE 2020 - Yunlin, Taiwan
持續時間: 23 10月 202025 10月 2020

出版系列

名字2nd IEEE Eurasia Conference on IOT, Communication and Engineering 2020, ECICE 2020

Conference

Conference2nd IEEE Eurasia Conference on IOT, Communication and Engineering, ECICE 2020
國家/地區Taiwan
城市Yunlin
期間23/10/2025/10/20

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