In this research, we show that variables from the Global Database of Events, Language and Tone (GDELT) convey significant informational content that can improve on a purely macroeconomic approach when modeling the US equity market. Based on these metrics, we construct time-series that represent and measure how some narratives that appear to be battling each other are changing in the current market environment. Namely we are able to appraise the strength of the roaring 20s, back to the 70s, secular stagnation and monetary economic narratives, but we also add up topical societal narratives related to environmental or social aspects, as well as a geopolitical risk narrative. We formalize an informational content framework and show that including quantitative signals that translate into qualitative stories brings added value when determining the stock market’s movement. Indeed, on top of higher explanatory power from their underlying variables, narratives can improve the diversification of standard macroeconomic models and enhance their quality. As such, our results advocate for a close monitoring of narratives in financial markets.