New research exploring the possibility of using sentiment analysis to predict the behaviour of financial indicators has shown promising results. A team headed by Professor Argimiro Arratia, a staff member on the Barcelona GSE Masters course in Data Science, investigated the possibility of using eleven news-based indicators to predict movements in stocks and shares. Their findings were promising; a volatility index based upon the eleven indicators was found to be an accurate predictor, particularly when interactions between the indicators were added to the model. Although this was not the first time sentiment analysis had been used in financial forecasting, this research used a wider range of sentiment indicators than previous studies.
These new findings present an exciting new development in computational finance. The addition of data science techniques to economic forecasting is an area of research with potentially wide implications for practitioners and academics.
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