The headline effect is the impact of headlines, news, and narratives on asset prices as well as the economy in general. The effect can be both positive or negative for asset prices. The effect runs counter to modern finance theory that gives no importance to headlines or narratives as causal factors that move market prices.
On the other hand, there is sufficient empirical evidence to show that many market movements can be attributed to specific headlines or underlying narratives. Below, we will look at a new economic framework introduced by the Nobel Prize-winning economist Robert J. Shiller called Narrative Economics, then we look at some applications of the headline effect in finance and investing.
In 2017, the Nobel Prize-winning economist Robert J. Shiller introduced a new framework to analyze the impact of narratives on the economy. To such an end, he presents a quantitative framework that uses modern epidemiology models used to model the spread of disease to measure the spread of narratives in a society.
In Shiller’s paper, he discusses the example of the short recession of 1920-21, which is the shortest and sharpest recession recorded in American economic history.
The traditional explanation for the short recession was given by the economist Milton Freedman as an unexpected increase in interest rates by the New York Federal Reserve by a full percent in January 1920.
Shiller, on the other hand, offers a narratives based explanation for the recession. He analyzed newspaper headlines and articles of the time to recreate the narratives that prevailed in those times.
The recession came in the aftermath of major world events of the time, such as the end of World War I, the Russian Revolution, and the influenza pandemic. The papers at the time talked of the end of war profiteering. All of the news created an expectation that prices would fall below the pre-war levels and that things would return to normal. Such a general atmosphere caused people to delay consumption, causing a deflation-led economic depression.
Headline Effect in Finance
Following the many studies done to measure the impact of news on the prices of financial assets, there are various sentiment indicators today that are used by market participants to predict the movement of markets.
One such example of the sentiment indicators is the Daily News Sentiment Indicator published by the Federal Reserve Bank of San Francisco. It uses the database of newspaper articles provided by LexisNexis. They perform sentiment analysis on the articles to get an aggregate news sentiment for the day.
As the figure below shows, the news sentiment tracks well with the Dow Jones Industrial Index (DJIA). In fact, in the study period from December 2019 to November 2020, the two series show a strong positive correlation of 0.75.
Another example of the use of the headline effect can be seen in the research presented by Clifford Asness of AQR Capital. In a paper describing what the authors termed deep value stocks. They are undervalued stocks that are currently doing poorly but with sound business models. Hence, it is expected that they will increase in value to reflect the sound fundamentals.
Typically characteristics of deep value stocks include a low price to book ratio, low market betas, and high selling pressure. In addition to the quantitative factors, the authors also utilized negative news sentiment to screen for deep value stocks. They also found that news sentiment for value stocks was lower than that for growth stocks. It is empirical proof that news and headlines are associated with asset prices.
In the recent past, there’s been widespread adoption of Natural Language Processing (NLP) techniques by various investment banks and other asset management firms. It is part of the alternative data revolution, which introduced the use of non-financial data like satellite imagery including news and social media data that is continuously monitored.
All of the above points to the headline effect being important to the investment process.
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