Developing stock market analysis skills for students majoring in Economics through an automatic information extraction system

Abstract

With the rapid advancement of information technology, there is a growing demand for digital data research among organizations, companies, and individuals. This includes the stock market, where access to stock data is essential. To address this need, we have developed a system that employs automatic data extraction techniques, facilitating user access to stock data from the three major stock exchanges: HNX, HOSE, and UPCOM. The system applies the principles of Extract, Transform, and Load (ETL) to extract data from various sources, primarily websites and open data, as accessing the API of the Vietnam stock exchange is limited. By extracting data from multiple sources, the system ensures data authenticity and provides users with the latest information promptly.