Automatic Prediction of Future Business Conditions

  • Lucia Noce
  • Alessandro Zamberletti
  • Ignazio Gallo
  • Gabriele Piccoli
  • Joaquin Alfredo Rodriguez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8686)


Predicting the future has been an aspiration of humans since the beginning of time. Today, predicting both macro- and micro-economic events is an important activity enabling better policy and the potential for profits. In this work, we present a novel method for automatically extracting forward-looking statement from a specific type of formal corporate documents called earning call transcripts. Our main objective is that of improving an analyst’s ability to accurately forecast future events of economic relevance, over and above the predictive contribution of quantitative firm data that companies are required to produce. By exploiting both Natural Language Processing and Machine Learning techniques, our approach is stronger and more reliable than the ones commonly used in literature and it is able to accurately classify forward-looking statements without requiring any user interaction nor extensive tuning.


Natural Language Processing Information Retrieval forward-looking statement earning call 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Lucia Noce
    • 1
  • Alessandro Zamberletti
    • 1
  • Ignazio Gallo
    • 1
  • Gabriele Piccoli
    • 1
  • Joaquin Alfredo Rodriguez
    • 1
  1. 1.Department of Theoretical and Applied ScienceUniversity of InsubriaVareseItaly

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