News Analytics: Exploring Predictive Power of Aggregated Text Sentiment Measure
نویسندگان
چکیده
News analytics and text sentiment detection were established in recent years as methods that can support forecasting of market movements. The body of literature exploring relations between sentiment measures and various financial indicators is rapidly growing. We contribute by taking a more global view and by proving that there is a positive and significant relation between average sentiment of all news published about one country and that country’s GDP and GDP change. This relation holds also when observing aggregated sentiment in one year against GDPs and GDP changes in following years.
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