This paper uses GDELT for financial forecasting:
In this article, the authors show that variables from the Global Database of Events, Language, and Tone convey significant information that can improve on a purely macroeconomic approach when modeling the US equity market. Based on these metrics, the authors construct time series that represent and measure how some narratives that appear to be battling each other are changing in the current market environment. Specifically, the authors appraise the strength of the roaring 20s, back to the 70s, secular stagnation, and monetary economic narratives, but they also add topical societal narratives related to environmental or social aspects and a geopolitical risk narrative. The authors formalize an information content framework and show that including quantitative signals that translate into qualitative stories brings added value when determining the stock market’s movement. Indeed, in addition to having higher explanatory power from their underlying variables, narratives can improve the diversification of standard macroeconomic models. As such, the authors’ results advocate a close monitoring of narratives in financial markets.