Scenario Analysis Misconceptions (1 of 3): The Random Walk

Updated: Jan 15, 2021

So far this week, we have explored pandemic-era challenges for scenario analysis designers due to Two Data Deficits and Why Data Deficits Matter (i.e., when bad data happens to good models). In sum, low amounts of data or bad data increase the importance of getting scenario analysis right. Scenario analysis can provide perspective on potential risk exposures because they take today’s portfolio values as their starting point and help identify weaknesses under different conditions.

But generating solid scenario analysis is not as easy as it sounds when seeking to evaluate exposure to public policy risks. In order to generate optimum value from scenario analysis regarding public policy risks, it is important to debunk a few misconceptions about how scenario analysis operates.

Today we focus on the first – and possibly the most important – misconception.

Scenario Analysis Regarding Public Policy

Is Not a Dart Board

To the extent that the risk management discipline includes public policy risk as a discrete risk category, it typically falls under the broader “event risk” heading. The implicit assumption is that public policy risk is at best random. Less charitable interpretations also exist. Cynics suggest the policy process is corrupt and full of back room deals that are not transparent. Many paint political opponents as unpredictable, crazy, irrational, and/or evil.

This line of thinking leads many to conclude that efforts to identify possible shifts in public policy are a waste of time because it is impossible to assess with any accuracy whether any given scenario is likely. This increases exponentially the risk of inaccuracies associated with scenario analysis results.

In the language of risk management, random shifts in assumptions and parameters will generate similarly random outcomes without correlation to actual risks or likely outcomes.

Many believe that developing scenarios to address public policy risks might just as easily and effectively be conducted as if it were a game of darts. While some skilled players might be able to hit the bulls-eye, mostly the darts will fall wide of the mark. Most scenario analysis efforts thus retreat to a quantitative comfort zone by focusing on components for which reams of public market data exist, relegating public policy risk exposures to the random category.

We disagree.

Public policy professionals know something that is not immediately obvious to financial engineers or technology professionals: public policy risk is NOT random.

Understanding how to craft meaningful scenario analysis regarding public policy risks requires first and understanding of the difference between two overlapping disciplines: politics and policy.

Politics is driven by voter sentiment expressed at regular intervals through voting. It is profoundly fickle and can seem very random as multiple recent polling data fails illustrate.

Politics shifts perpetually in relation to public sentiment, which can be very malleable at the margins. This is why the increased velocity of information flows through social media and niche focus media outlets create the equivalent of Gresham’s Law (bad money drives out good money) in the marketplace of ideas. The consequence is increased exposure to misinformation, disinformation, and worse. We analyzed the situation in depth last summer in THIS POST, entitled "Finding Facts: A Distributed Age Scavenger Hunt."

While politics sets broad parameters for policymaking, the vast majority of policy decisions are technical…..and policymakers make their intentions known in advance in public. Advocates follow every twist and turn of the policy process at a minute level of detail.

Having been an advocate as well as a policymaker myself, I know from personal experience that public policy outcomes rarely surprise policy professionals. We know how to follow public policy in a way that takes the guesswork out of forecasting.

The patented BCMstrategy, Inc. technology automates the monitoring and analysis process.

Our daily data feeds make it possible to make smarter decisions regarding likely public policy scenarios as they emerge.

The data accelerates identification of inflection points as they emerge, making it easier to make solid decisions based on concrete facts:

Devising accurate and relevant scenario analysis regarding public policy risks requires neither a dartboard nor a crystal ball. It just requires advanced technology that helps a scenario analysis architect spot the signal in the noise.

We can help with that.

Our next post in this series will de-bunk Misconception #2 regarding scenario analysis.


PolicyScope data is available through the Bloomberg Enterprise Access Point.

Customized widgets and dashboards are available via API HERE.

Analytical scenario analysis (The Scenarios -- twice monthly) and daily global macro analysis of platform data (The PolicyScope Risk Monitor) are also available.