Implementing an Integrated Assistance System for Stock Investment with Big Data Environments

In front of the blast wave of big data technology, stock investment is in need of prompt decision-making with support from big data analytics. This paper presents our work in the design and implementation of an integrated assistance system for stock investment with big data environments. We describe the overall architecture and the system architecture in detail. The system is designed with a typical three-tier architecture, in which we present the featured functionalities. We invited the practitioners in two professional stock investment communities to evaluate the effectiveness of the implemented system, and the result suggested that the design and implementation of the system are successful in achieving its goal of helping the practitioners to make prompt decisions in stock investment.