Negative Economic Sentiment Index Based on Finnish News Titles


  • Aleksi Avela Aalto University, School of Science
  • Markku Lehmus Bank of Finland



economic sentiment, natural language processing, machine learning, naive Bayes classifier, economic forecasting


We construct an index for measuring negative economic sentiment in Finland by using news titles collected from the Finnish broadcasting company Yle's archive. Our approach uses supervised machine learning text classification for detecting news titles featuring negative economic sentiment, and the monthly aggregated proportional frequencies of those titles are then used for defining the index. We find a negative correlation between our index and the consumer confidence index by Statistics Finland, and more remarkably, our index seems to lead the consumer confidence index, somewhat, by one month. We also show that our index correlates positively with Finnish stock market volatility. In addition, based on a simple VAR model, we examine how certain macro variables respond to changes in economic sentiment and show that our index could prove helpful in assessing the current and near-future state of the Finnish economy.