Journal Article

·2022 OPEN ACCESS

Predicting the Profitability of the Stock Market during a Pandemic

Jamilu Said Babangida YTU , Attahir Babaji Abubakar , Suleiman O. Mamman , Fadwa BEN BRAHİM

Aksaray Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi

Abstract

This paper investigates the impact of the Covid-19 pandemic in predicting the profitability of the stock market of the ten most hit countries at the beginning of the pandemic. The study employed the Artificial Neural Network models for the analysis. Specifically, the Backward Propagation (BP) and Feed-Forward (FF) Neural Network models are used to predict the profitability of the stock market on a daily time frame. Taking Covid-19 into account, the estimation result shows that the Neural Network built is resilient in its ability to forecast the profitability of the stock market in Brazil and China. However, in the case of Germany, Russia, Turkey, and the United States, the Neural Network is partly resilient in its forecasting ability; predicted profitability deviated from the actual profitability in some of the periods. For the remaining countries in the sample, the Artificial Neural Network is found to have a weak prediction power.

Keywords

Profitability index Artificial neural network Econometrics Stock market Predictive power Stock (firearms) Economics Sample (material) Business Computer science Engineering Artificial intelligence Finance Geography

Subject Areas

COVID-19 Pandemic Impacts ·Economics and Econometrics ·Social Sciences
Stock Market Forecasting Methods ·Management Science and Operations Research ·Social Sciences
Market Dynamics and Volatility ·Economics and Econometrics ·Social Sciences