#DigitalDollar #AlternativeData

How can measuring momentum from the language of public policy generate predictive analytics? The last time we answered this question, we walked through a monetary policy example using our Bloomberg Terminal App.


Let's take today's digital currency news as an opportunity to take it one step at a time. Specifically, let's talk about the digital dollar announcement today by the Federal Reserve Bank of New York (FRBNY).


Step 1: The Daily Horizon Scan

Public discussion of a digital dollar by government officials in general and Federal Reserve officials in particular is a low-volume, low-frequency activity. Even after the March 2022 Biden Executive Order, and even with mounting media coverage during the summer, policymakers refused to discuss publicly their views on a digital dollar.


The silence ended in early November, when an FRBNY Executive Vice President delivered strikingly bullish remarks on a digital dollar in Singapore. The inflection point looked like this:


Step 2: Assess the Dynamics and Reaction Functions


Anecdotally, the charts illustrate a pattern: policymakers take action regarding a digital dollar roughly every two months.....and they stay studiously silent in between announcements. In addition, announcements on this specific issue tend to occur when the broader news cycle is otherwise fixated on other issues (today's context: FTX, missile strike in Poland, COP27, US elections) and/or on vacation (August).


Human readers using the daily horizon scan on our Bloomberg Terminal App and .csv data customers evaluating daily data would have seen that pop in activity in early November. Users that incorporate DCVS data (Digital Currency Policy Volatility) data in general or DCVS5 (Digital Dollar) specifically into their automated workflows would additionally have received an alert that policymakers were taking action with respect to the digital dollar.


The questions and analytical process they follow from here includes:


--was official sector action prompted by/reacting to media stories? If the amount of action exceeds the amount of media coverage (i.e., rhetoric), then an informational advantage exists and media coverage will likely follow....which will in turn trigger a market reaction function.


--does the official sector activity reflect convergence with a pre-existing pattern (in which case the activity is 'normal') or is it out of cycle?


Step 3: Assess Market Dynamics and Scenario/Nowcasting Model Parameterization


Portfolio managers will immediately assess market data as well as the recent performance of portfolio positions to determine whether/or not other market participants are pricing in the latest policy move.


Our 2021 backtests indicate it can take up to 22 days before the market prices in technical policy shifts.






Step 4: Assess the Current News Cycle


Technical policy shifts measured by our award-winning, patented process can provide material informational advantages using immediately actionable information. The immediate next question is: has anyone else noticed?

Consider today's announcement (15 November 2022) that the FRBNY has announced a digital dollar pilot program. Our data users and our human readers are not exactly surprised. They saw the precursor to this activity on November 5.


Seeing the news flash across the screen for informed data users enables portfolio managers to connect the dots more swiftly relative to their counterparts that either do not know the move occurred or are wasting time asking "where did this come from?" Advocacy users also connect the dots more swiftly and thus start operating more efficiently, advancing faster and farther across the competitive field compared with others that did not see the situation developing over the preceding months.


Portfolio managers and advocates alike achieve significant strategic and informational advantages by using next-gen technology to identify policy shifts as they materialize. We are delighted to be able to help both sets of professionals accelerate their capacity to make data-driven decisions by delivering state-of-the-art data and policy risk measurements every day.