Information Extraction From the GDELT Database to Analyse EU Sovereign Bond Markets
| Autor: | Luca Tiozzo Pezzoli, Elisa Tosetti, Sergio Consoli |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
050208 finance
Open platform Database business.industry 05 social sciences Big data Government yield spread Features engineering computer.software_genre Popularity Article Underdevelopment GDELT Machine learning Information extraction Open research Sovereignty Settore SECS-P/05 - ECONOMETRIA 0502 economics and business Bond market Business 050207 economics computer |
| Zdroj: | Mining Data for Financial Applications Mining Data for Financial Applications ISBN: 9783030669805 MIDAS@PKDD/ECML |
| Popis: | In this contribution we provide an overview of a currently on-going project related to the development of a methodology for building economic and financial indicators capturing investor’s emotions and topics popularity which are useful to analyse the sovereign bond markets of countries in the EU.These alternative indicators are obtained from the Global Data on Events, Location, and Tone (GDELT) database, which is a real-time, open-source, large-scale repository of global human society for open research which monitors worlds broadcast, print, and web news, creating a free open platform for computing on the entire world’s media. After providing an overview of the method under development, some preliminary findings related to the use case of Italy are also given. The use case reveals initial good performance of our methodology for the forecasting of the Italian sovereign bond market using the information extracted from GDELT and a deep Long Short-Term Memory Network opportunely trained and validated with a rolling window approach to best accounting for non-linearities in the data. |
| Databáze: | OpenAIRE |
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