ARIMA: An Applied Time Series Forecasting Model for the Bovespa Stock Index

Paulo Rotella · Fernando Luiz Riêra Salomon · Edson de Oliveira Pamplona

54 citations0/0 files storedApplied Mathematics

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Stock Market Forecasting Methods Forecasting Techniques and Applications Time Series Analysis and Forecasting

Abstract

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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1970EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK*1970Efficient Capital Markets: A Review of Theory and Empirical Work 1975the delphi method: techniques and applications 1963A Simplified Model for Portfolio Analysis 1993Forecasting methods and applications 2010Operations management 2002Operations management research methodologies using quantitative modeling 1998Forecasting: Methods and Applications, 3rd Edition

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