Investors seeking to translate the news cycle into tradeable signals often struggle. This is understandable. The news cycle in the best of times is noisy. We are not living in the best of times.
The 2021 Challenge
Dramatic, destabilizing developments once again dominate the media cycle as 2021 begins. The high volumes of media coverage, while important, may not directly impact economic risks embedded within portfolio positions. Technical policy developments that do impact portfolio level risks can be crowded out of the news cycle.
Ongoing political upheaval in the United States combine with ongoing pandemic, strategically significant geopolitical shifts, and an accelerating pivot towards the digital economy. Distinguishing between politics (the process by which policymakers are selected and authorized to act) and policy (the technical decisions made by policymakers once they are in office) is crucially important for investors seeking to make data-drive decisions in relation to the public policy cycle. The good news is that public policy decisions are far more predictable than political decisions, as noted by our infographic.
Never has it been more important – or more difficult – to maintain focus on technical public policy issues important to asset allocation and risk assessment. Shifts in public policy impact the cost of doing business directly by imposing taxes, tariffs, regulatory capital and/or product safety requirements and indirectly by imposing regulatory reporting and other compliance requirements. Public policy risks embedded in portfolios are most vulnerable to shifts when new governments take office, such as 2021 in the United States. The challenge, of course, is that most policy shifts can take months if not years to materialize. Moreover, the policy process does not align neatly with market processes much less options expiration dates.
The Nowcasting Solution
Minimizing exposure to public policy risks – and maximizing alpha generation potential from the public policy cycle – requires a laser-like focus on individual policy issues paired with a sharp time horizon definition. It requires nowcasting for public policy risks (as discussed HERE at Traders Insight during 2019).
Specifically, on any given day, investors do not need to know the ultimate policy decision. Investors also do not even need to agree with the wisdom of a particular policy shift. They only need to know what kind of intermediate policy shifts might arise in the next week or two that might impact their portfolio positions. Policy inflection points that signal a shift from the status quo require hedging.
Conquering Headline Risk
The relationship between public policy and investing is well known and well-worn. From the tickertape to headline-reading bots deployed by algorithmic traders, capital markets have long sought to decrease the latency between the news cycle and investment decision. But rapid reaction functions keyed to headlines generate their own unique class of risk (headline risk) and a suboptimal risk management mechanism because headlines can be misleading.
As Bloomberg reported last week, during 2020 human investors out-performed quant funds because human investors could use common sense and appreciate opportunities without being constrained by the lack of historical data. We have written elsewhere about how the pandemic creates data gaps and why those data gaps matter. We were not surprised to see that quant funds had a hard time during 2020.
When it comes to nowcasting for public policy risks, investors face an additional challenge: a mismatch between their models (which rely on structured data) and the sources of risk in the policy making cycle (which generates reams of unstructured verbal data). Investors seeking to adopt data-driven approaches to measuring public policy risks too often have either resorted to headline-reading bots or made the mistake of believing that public opinion polls important to setting political directions are also important for setting public policy.
Better alternatives now exist. It is now possible to convert the words of the public policy process into objective, transparent structure data using natural language processing. The creation of structured data makes it possible to measure momentum and generate time series data that illustrate the global policy reaction function with clarity.
By placing the noise of the news cycle into context, investors can measure the delta between actions policymakers take and media reporting about those actions.
The size and duration of the delta also demonstrates alpha generation opportunities because official sector actions not yet appearing in the media cycle deliver significant informational advantages to investors that can see them.
At BCMstrategy, Inc., we use patented processes to generate objective, transparent data from the global public policy process….without using sentiment analysis. The PolicyScope Platform provides a powerful suite of tools that can help both quant-based funds and human investors to make smarter decisions regarding public policy developments based on cold, hard facts rather than opinion.
Direct access to PolicyScope Platform data is available to professional investors via the Bloomberg Enterprise Access Point.: https://eap.bloomberg.com/catalogs/bbg/products/BCMStrategiesPolicyScopeEdition1 Customized derivative data products designed for strategists and investors are available through our API. Daily data-driven macro analysis is available to retail customers HERE.
Disclosure: Interactive Brokers
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