When capital markets interact with the news cycle and public policy, the focus usually is on the ultimate outcome. But today we suggest that this long-term focus is misplaced, even for macro and bond market investors. Capital market participants must mark their portfolios to market daily and adjust their exposure to risk accordingly. Adjustments can take the form of new or additional hedging activities, as well as asset disposition.
If your goal is to generate alpha from the news cycle, then there is no substitute for adjusting exposure to policy risk on at least a daily basis. As noted in previous blogposts in this series (particularly Rules 1 and 3), reacting to headlines is at best a suboptimal way to manage exposure to policy risk for many reasons. Strategic investors instead adopt a nowcasting approach to assessing policy risk in order to get ahead of the news cycle using publicly available information.
Nowcasting – A High Level Overview
Nowcasting is the process of generating short-range anticipated outcomes using current data.
It originated in meteorology in the 1860s to anticipate weather-related events for navigation purposes. More recently, it has been used in the healthcare and economics contexts as described in this article. The Federal Reserve uses nowcasting to anticipate GDP growth, as described in this 2014 Federal Reserve Bank of Atlanta working paper.
Because nowcasting relies on the most current data in a series (e.g., the latest quarter data release), it focuses like a laser on the real-time inflection point implied by the data. In other words: it is not drawing conclusions or making outlooks based on past historical data. It instead assesses whether the current trajectory is consistent with, or departing from, the previous trajectory in order to assess whether an inflection point may be materializing.
This makes nowcasting particularly relevant for policy risk analysis. One key attribute of policy risk is that new developments have the capacity to make historical information obsolete within a matter of seconds. Many thus view efforts to anticipate policy outcomes as akin to throwing darts at a board. Luck has at least as large a role to play in hitting the bullseye as skill. The rapid rate of change in the policy environment leads many to conclude incorrectly that policy outcomes cannot be anticipated accurately. This is especially true during periods of rapid structural shifts such as the period in which we currently find ourselves.
The problem, however, is in a mismatch of time horizons and data sets. Generating alpha from the news cycle requires a daily discipline of determining whether the developments of the day continue to support the investment thesis (and the cost of holding a position amid market volatility). Generating alpha does not require knowing today the specific outcome at the end of the year. It merely requires knowing whether the policy process today is trending towards one outcome or the other. It also requires understanding when the noise of the news cycle is generating false signals. See Rules 1, 2, and 4 for how to read the news cycle. It requires learning and implementing the core skills common to all “superforecasters.”
How To Use Nowcasting for Policy Risk
Every day, policymakers generate data that can be used to assess risk relative to a position exposed to public policy risk. They generate this data with every speech, statement, proposal, leak, and quote. In other words: they generate the data needed to conduct nowcasting with respect to the public policy process.
Generating alpha from the news cycle and managing related investment risks merely requires investors to adjust their time horizons to match the daily data release cycle. It requires the discipline of reassessing every day whether (or not) policymakers are proceeding towards a specific outcome. It also requires flexibility (Rule 6), relentlessness (Rule 5) and objectivity (Rule 1) to adjust portfolio positions in the event that policymakers are proceeding towards an outcome that you personally, or the market, do not favor.
Is your long-term view that policymakers “must” take a specific action because that action would be responsible/morally appropriate/necessary? Generating alpha requires instead a daily assessment of whether policymakers are pursuing that path. Consider the bond investors in Greece a few years ago. Daily market volatility associated with GGBs, and the Euro Area bond market in general, demonstrated daily moves at multiple standard deviations during peak moments of negotiations. Investors that listened carefully and relentlessly to what policymakers were actually saying and doing took a range of tactical measures throughout the period in order to generate substantial alpha using only publicly available information.
The Challenges of Using Nowcasting for Public Policy Risk
Implementing nowcasting for public policy risk is harder than it sounds. Executing well a nowcasting process on a daily basis requires three different sets of tools:
- First, the investor must know where to find the relevant information beyond the headlines. This usually requires specialized knowledge from individuals that once were policymakers themselves.
- Second, since policymakers operate in a 24/7 media cycle turbo-charged by social media, specialized and automated media monitoring is needed.
- Third, sophisticated technology based on Natural Language Processing is needed to capture and analyze the language policymakers are using. This is NOT sentiment analysis. A policymaker can use negative language and express negative emotions regarding a particular policy even as he or she proceeds to endorse that policy. Sentiment analysis will only capture the emotion in the language. Instead, a value-neutral approach is needed, which assesses the action from the language. This is the frontier of Natural Language Processing, where BCMstrategy, Inc.’s patented technology operates.
Why does it work? Because policymaking is a community activity that requires consensus. The business of a policymaker is to garner sufficient support for specific language that articulates that consensus. How do they find the acceptable language? By articulating language publicly through speeches, materials, and interviews with the media. These words comprise the data set needed to implement a nowcasting approach to policy trend outlooks, as discussed in detail in this blogpost.
When we filed for our patent in 2011, we were excited to find an automated way to measure the volume and analyze the direction of public policy from the words articulated by officials. Now that the platform has been built, we see on a daily basis the value of taking a nowcasting approach to assessing public policy risk. It enabled us to anticipate that the UK would reach the end of March with a “no-deal” Brexit as a reality. It enabled us to anticipate using transparent, objective data that the EU and the United States would begin building a more constructive trade policy relationship despite incendiary public rhetoric. And it enabled us to identify significant macrotrends regarding cryptocurrencies and their close (if not potentially competing) cousins in the central bank digital currency arena.
Nowcasting is a necessary condition for generating alpha from the news cycle because it enables investors to respond strategically and nimbly to developments in the public policy arena. Implementing it is harder than it sounds. It requires thinking clearly about how to match time horizons. It also requires next-generation Natural Language Processing technology to capture the signals incorporated in official sector language as it occurs. We are using that process today, successfully anticipating various outcomes at various inflection points.
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