Intelligent data analysis of the influence of COVID-19 on the stock market using Case Based Reasoning

• Main Authors: Antonio Lorenzo Sánchez, Jose Olivas
• Format: Article
• Language: English
• Published: Postgraduate Office, School of Computer Science, Universidad Nacional de La Plata 2020-10-01
• Series: Journal of Computer Science and Technology
• Subjects: forecast; prediction; covid-19; stock markets; case-based reasonig (cbr); analogy learning
• Online Access: https://journal.info.unlp.edu.ar/JCST/article/view/1433

Starting with the differences between forecasting and prediction and going deeper into prediction, a knowledge-based model is presented. The evolution of the stocks markets are analyzed, as well as how the epidemics and pandemics prior to the stock markets have affected them and how it is currently being affected by covid-19. The defined model is applied to a use case using Case-Based Reasoning (CBR): it makes an analogy between the 2008 crisis with the covid-19 crisis in 2020 to predict whether the stock markets will take more or less time to recover.