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Neural forecasting of the Italian sovereign bond market with economic news

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  • Sergio Consoli
  • Luca Tiozzo Pezzoli
  • Elisa Tosetti

Abstract

In this paper, we employ economic news within a neural network framework to forecast the Italian 10‐year interest rate spread. We use a big, open‐source, database known as Global Database of Events, Language and Tone to extract topical and emotional news content linked to bond markets dynamics. We deploy such information within a probabilistic forecasting framework with autoregressive recurrent networks (DeepAR). Our findings suggest that a deep learning network based on long short‐term memory cells outperforms classical machine learning techniques and provides a forecasting performance that is over and above that obtained by using conventional determinants of interest rates alone.

Suggested Citation

  • Sergio Consoli & Luca Tiozzo Pezzoli & Elisa Tosetti, 2022. "Neural forecasting of the Italian sovereign bond market with economic news," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(S2), pages 197-224, December.
    • Handle: RePEc:bla:jorssa:v:185:y:2022:i:s2:p:s197-s224
    DOI: 10.1111/rssa.12813
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