Neural Forecasting of the Italian Sovereign Bond Market with Economic News
In this paper, we employ economic news within a neural network framework to forecast the Italian 10-year interest rate spread. We use the big, open-source, database known as Global Database of Events, Language and Tone to distil 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 the one obtained by using classical interest rates determinants alone.
CONSOLI Sergio;
TIOZZO PEZZOLI Luca;
TOSETTI Elisa;
2023-01-04
WILEY
JRC124232
0964-1998 (online),
https://rss.onlinelibrary.wiley.com/doi/10.1111/rssa.12813,
https://publications.jrc.ec.europa.eu/repository/handle/JRC124232,
10.1111/rssa.12813 (online),
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