Due to the relative uncertainty involved with the variables which affect financial market behavior, forecasting future variations in a time series of the Brazilian stock market Index (Ibovespa) can be considered a difficult task. This article aims to evaluate the performance of the model ARIMA for time series forecasting of Ibovespa. The research method utilized was mathematical modeling and followed the Box-Jenkins method. In order to compare results with other smoothing models, the parameter of evaluation MAPE (Mean Absolute Percentage Error) was used. The results showed that the model utilized obtained lower MAPE values, thus indicating greater suitability. This therefore demonstrates that the ARIMA model can be used for time-series indices related to stock market index forecasting.
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机译:The Impacts of Margin Trading on Rate of Return and Volatility in the Stock Market: A Study Using the SVAR Model and Panel Regressions =融资对股价收益与波动的影响特征研究——基于SVAR模型与面板模型的实证分析