Abstract

This work analyzed the impact of the covid-19 pandemic in the year 2020 on Brazilian stocks using the Bovespa index and identified outliers in the data. It also observed a trend of stability in the following years, indicating economic recovery. The seasonality in the regular patterns was identified and represented in a line graph, highlighting the lowest medians in June and July. Prophet and autoARIMA models were used for forecasting, and the results were evaluated using various error metrics, including RMSE, MAE, SMAPE, MAPE, MASE, and RSQ. Although the Prophet model performed better with the differentiated data, the AutoARIMA model performed better with the original and log1p transformed data. The study is relevant to understand the impact of the pandemic on Brazilian stocks and how forecasting models can be used to assist in decision-making.

Keywords

• Statistical Modeling
• Time series
• Forecasting

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