Influência dos textos de notícias na queda de preços no mercado de ações brasileiro
Resumo
Forecasting financial losses and making decisions to avoid or reduce them has been a
challenge for every investor. On one hand, due to the availability of data and its simple
implementation, technical analysis methods have been quickly gaining supporters. On the
other hand, modern computers processing power together with advances in text mining
provides the opportunity to explore the investor’s behaviors in new data types: textual.
This research evaluates the relationship between the Brazilian stock market and news
published on national midia, focusing on automatic search for patterns related to down
movements using machine learning algorithms. Six experiments were performed to analyze
the possibility of predicting price falls automatically, followed by case studies in the search
of explanations from the classifiers that justify the predictions.The results show that text
mining based approaches overcome traditional strategies when forecasting losses, but the
underlying patterns understanding is limited due to the complexity of the classifiers and
high dimensional vocabulary.
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