Gauging the State of the Economy with News Narrative and Sentiment

Advances in natural language processing have allowed to quantify the intuitive yet elusive notion of sentiment expressed in text and to test its predictive power in relation to changes in social systems.

Studies in cognitive sciences as well as economics have found that unsettling narrative preceded events such as the Great Depression in the 1920s and the Global Financial Crisis in 2008, suggesting that news sentiment is a means of forecasting the economy (1,2). ECB President Mario Draghi’s “whatever it takes” speech from July 2012 is a great example of a narrative that has impacted markets and the economy. These three words marked the turnaround of the euro crisis, purely achieved by Draghi’s verbal intervention.

Newspapers are a proven means for both individuals and institutions to share and distribute information. Most publications have an online presence and generate large amounts of data. This data includes information in the shape of sentiment and opinions about the economy, which is not yet reflected in macro-economic indicators.

The Global Database of Events, Language, and Tone (GDELT) (3) is a research collaboration that monitors the world’s newspapers from a multitude of perspectives, extracting items such as themes, emotions, events, mentions of organizations, and persons and locations for every news article analyzed almost in real-time.

News sentiment and the economic recovery following COVID-19

As the coronavirus spread around the world, governments in many countries were forced to impose strict lockdowns and temporarily close businesses. As a result, a lot of companies are struggling to survive. Many had to lay off employees, leading to a spike in unemployment.

The chart shows the average tone, financial uncertainty, and confidence indices based on emotions from GDELT, with news items filtered thematically for “economic growth.”

Net sentiment (i.e. positive minus negative tone) from global newspapers has improved notably since bottoming in April this year.

Levels of financial uncertainty peaked at the height of the outbreak in early spring. Financial uncertainty has since been declining but remains at elevated levels.

Confidence increased until February, perhaps reflecting confidence in local governments’ ability to contain the virus. The index plunged in March as lockdowns were imposed in countries around the world. Confidence moderately recovered in April but moved mostly sideways in May and June as the longer-term economic repercussions from the COVID-19 outbreak became apparent.

According to net sentiment, recovery is well on underway. However, the two other indices tell a somewhat different story. The coronavirus is likely to have a powerful impact on confidence as consumers are staying at home for a prolonged period, possibly feeling pessimistic about the future. With heightened levels of financial uncertainty and worsening financial conditions, household consumption typically falls as savings go up, weighing on economic growth.

Thoughts and conclusions

Net sentiment lacks the insights that more specific emotions can convey about the economic recovery, as it merely indicates whether positive outweighs negative sentiment. More specific emotions from news narratives can help form a clearer view of the present state of the economy. Both confidence and financial uncertainty suggest that the global economy is only at the beginning of a recovery from this year’s COVID-19 outbreak. The shape and speed of the recovery depend on factors like the economic impact of physical distancing, the effectiveness of government support packages, as well as the pace of the easing of lockdown restrictions and the occurrence of a second wave.

Traditional GDP forecasts are unreliable during normal market conditions and become even more challenging at present when the virus’s trajectory is unknown. It is difficult to capture the impact of COVID-19 on consumer and business behavior in a timely manner and thus to estimate a likely recovery path.

To find out more about forecasting the economy with news, narrative, and emotions, join me for my talk at ODSC Europe, “Forecasting the Economy with Fifty Shades of Emotions.”

(1) Robert J. Shiller. NARRATIVE ECONOMICS. Jan. 2017
(2) David Tuckett et al. “Bringing Social Psychological Variables into Economic Modeling: Uncertainty, Animal Spirits and the Recovery from the Great Recession”. In: IEA World Conference, Jordan (2014)
(3) gdeltproject.org

More on the author/speaker:

Sonja Tilly is a PhD candidate at UCL. Her research focuses on forecasting macro-economic variables and stock market movements using narrative and emotions from global newspapers.

Sonja has over a decade of experience working in asset management, most recently at Quoniam Asset Management, where she contributed to the development of trading strategies using media sentiment. Prior to that, she was a Quantitative Analyst at Hiscox. Sonja is a CFA Charterholder.