How to Use Stock Data for Data Science Education: A Simulated Trading Platform in Classroom

The research hereby presents an innovate practice to enhance data science education by integrating an in-house-developed stock trading platform. Students of Data Science area usually face the difficulty of understanding the complex of real-time data and sophisticated statistical indicators and models. Another difficulty is students are easy to lost interests and patience during the process of learning programming and analysis process, such as R-language. Stock market, as a huge data source and an important data disciplinary, is comparatively easy to attract student attentions. Thus, we developed an intuitive trading platform for education purpose. The platform contains three components: an exploring window, a control windows and a report window. The exploring window shows current and historical stock price trends and related indicators. Several representative stocks from different sectors can be picked and specific time frames can be assigned. The control window allows students to develop their own trading strategies. A trading strategy can be created by either intuitive way, or through single or combinations of indicators, or be built generically though plug-in R-programing module. The report window demonstrates the expected return of a stock in a specific time frame through a specific strategy. A more comprehensive report with detailed transaction information is also provided for back-testing purpose. Students are involved into the development of the software and get experience for R-programming. Preliminary version of the product has been tested and surveyed in a data science classroom. About ten junior Data Science students have practiced and provided feedback. The positive survey results show the feasibility of the approach. In the future, artificial intelligent component will be integrated into the platform.