英文标题：
《Global Stock Market Prediction Based on Stock Chart Images Using Deep
Q-Network》
---
作者：
Jinho Lee, Raehyun Kim, Yookyung Koh, and Jaewoo Kang
---
最新提交年份：
2019
---
英文摘要：
We applied Deep Q-Network with a Convolutional Neural Network function approximator, which takes stock chart images as input, for making global stock market predictions. Our model not only yields profit in the stock market of the country where it was trained but generally yields profit in global stock markets. We trained our model only in the US market and tested it in 31 different countries over 12 years. The portfolios constructed based on our model\'s output generally yield about 0.1 to 1.0 percent return per transaction prior to transaction costs in 31 countries. The results show that there are some patterns on stock chart image, that tend to predict the same future stock price movements across global stock markets. Moreover, the results show that future stock prices can be predicted even if the training and testing procedures are done in different countries. Training procedure could be done in relatively large and liquid markets (e.g., USA) and tested in small markets. This result demonstrates that artificial intelligence based stock price forecasting models can be used in relatively small markets (emerging countries) even though they do not have a sufficient amount of data for training.
---
中文摘要：
我们使用深度Q网络和卷积神经网络函数逼近器，以股票图表图像为输入，进行全球股市预测。我们的模型不仅在培训所在国的股票市场上产生利润，而且通常在全球股票市场上产生利润。我们仅在美国市场培训了我们的模型，并在12年内在31个不同的国家进行了测试。在31个国家，基于我们模型的产出构建的投资组合通常在交易成本之前，每笔交易的收益率约为0.1%至1.0%。结果表明，在股票图表图像上存在一些模式，这些模式倾向于预测全球股票市场上相同的未来股价走势。此外，结果表明，即使培训和测试程序在不同的国家进行，也可以预测未来的股票价格。培训程序可在相对较大且流动性较强的市场（如美国）进行，并可在小型市场进行测试。这一结果表明，基于人工智能的股票价格预测模型可以用于相对较小的市场（新兴国家），即使它们没有足够的数据进行培训。
---
分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：General Finance 一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
--
一级分类：Computer Science 计算机科学
二级分类：Computational Engineering, Finance, and Science 计算工程、金融和科学
分类描述：Covers applications of computer science to the mathematical modeling of complex systems in the fields of science, engineering, and finance. Papers here are interdisciplinary and applications-oriented, focusing on techniques and tools that enable challenging computational simulations to be performed, for which the use of supercomputers or distributed computing platforms is often required. Includes material in ACM Subject Classes J.2, J.3, and J.4 (economics).
涵盖了计算机科学在科学、工程和金融领域复杂系统的数学建模中的应用。这里的论文是跨学科和面向应用的，集中在技术和工具，使挑战性的计算模拟能够执行，其中往往需要使用超级计算机或分布式计算平台。包括ACM学科课程J.2、J.3和J.4（经济学）中的材料。
--
一级分类：Quantitative Finance 数量金融学
二级分类：Statistical Finance 统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
--

---
PDF下载：
-->