 Short-term forecasting and impact analysis of COVID-19 and the stock market in Morocco using ARIMAN’Adoi Aboagye and Saralees Nadarajah PLOS ONE, 2026, vol. 21, issue 2, 1-23 Abstract: This study aimed to predict the short-term trends of confirmed COVID-19 cases and the MASI stock index in Morocco using the ARIMA method. COVID-19 case data were obtained from Our World in Data, while MASI stock market data were obtained from Investing.com. The dataset covered the period from March 2, 2020 to April 28, 2022. To develop the predictive model, data from March 2, 2020 to April 28, 2022, were used for training. Data from April 22, 2022 to April 28, 2022, were used for model fitting for COVID-19 cases, and from April 25, 2022 to April 29, 2022, for the MASI index. Based on these models, we conducted short-term forecasts for April 29, 2022 to May 1, 2022, for COVID-19 cases, and May 4, 2022 to May 6, 2022, for the MASI index. The forecasting accuracy was mainly evaluated using the mean absolute percentage error (MAPE). Furthermore, we applied the Granger causality test to investigate the potential directional relationship between COVID-19 case trends and MASI index fluctuations. To the best of our knowledge, this is the first study to perform short-term forecasting of both COVID-19 cases and the MASI stock index in Morocco while also assessing their dynamic interplay, providing a novel contribution to the intersection of epidemiological and financial modeling in the region. Date: 2026 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0328202 DOI: 10.1371/journal.pone.0328202 Access Statistics for this article More articles in PLOS ONE from Public Library of Science |
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