- The dot plot is quantitative but infrequent and faceless. Speeches are much more frequent and personalized, but prior to Prattle scores, speeches were not quantifiable.
- Prattle scores bridge the information gap between the dot plots and policymaker speeches, providing a quantitative method for market participants to continuously update their views during the three-month-long periods between dot plots.
- This study merely hints of the powerful policy forecasting capabilities that Prattle provides.
FOMC participants’ rate projections (the dots) have become the most prominent policy signal for market participants. They are explicit, numerical, and cover a forecast horizon of a several years, but they have two critical shortcomings.
- The dots are infrequent. They are reported only once every three months, so the information quickly becomes stale.
- The dots are anonymous. It can be difficult to judge the likely inclinations of decision-making members of the FOMC despite having some measure of the central tendency.
We have long held the view that FOMC’s verbal communications (individual participants’ speeches and FOMC statements and minutes) are indispensable policy tools because they are nuanced, wide-ranging, and frequent. But until the advent of Prattle’s sentiment scores, we had no way to quantify them. Prattle’s proprietary algorithm places the full information content of any speech or communication on a quantitative hawkish-dovish scale. Prattle scores make it possible to compare speeches from the same policymaker, between different policymakers, and to compare them with committee communications.
San Francisco Fed researchers have utilized Prattle data to analyze the relationship between FOMC participants’ speeches and the FOMC’s median dots. Using Prattle sentiment scores to represent the content of speeches, Nechio and Regan found that the median Prattle scores of speeches in the weeks before FOMC meetings correlate positively with the median medium-term SEP projections.
The attention that the San Francisco Fed is giving to text analysis—specifically Prattle scores as they relate to monetary policy communication—speaks to the growing use of Prattle’s technology by both market participants deciphering Fed communications and policymakers seeking to improve communication.
This study suggests that market participants with Prattle scores at their disposal could use the scores to approximate the likely evolution of the dots between those long periods during which the FOMC does not update its rate projections. Although this is valuable information, the study only scratches the surface of potential uses for Prattle scores. Specifically, Prattle scores have a layer of precision above and beyond the dots because they are always associated with specific policymakers or the committee consensus. These speaker-specific tags allow for easier tracking of a particular policymaker’s views over time and in relation with others, in essence naming the dots. Also worth noting, Prattle scoring reflects the history of how the market actually reacted to previous communication, making it particularly useful for tweaking strategic portfolio allocations much more frequently than the quarterly dot plot.
The San Francisco Fed study was a straightforward univariate correlation analysis, so it is merely a hint of the powerful policy forecasting capabilities that Prattle provides.
Larry Meyer, former Fed Governor and President of LH Meyer