#AlternativeData Frontiers

Twice a month, we publish essays on LinkedIn. The essay below appeared on LinkedIn earlier this week. If you would like to read the essays as soon as they are published, you can subscribe to the free AltData & Volatility Frontier newsletter HERE on LinkedIn.

The Frontier

The frontier can be thrilling, when it is not frightening. Fighter jet pilots that pushed the boundary of physical travel followed a long line of explorers and scientific innovators whose discoveries still shape the world in which we live. Start Up Nation chases unicorns, successful exits, and the bragging rights that accompany being “the first” to do something successfully.

Our colleagues across Alternative Data consistently enable analytical professionals to see the world from a different perspective using data that had not been accessible previously. We don’t need to tell the early adopters that they will reap large rewards from efficiency gains and unique insights. We all win together by being first.

But the frontier is not always benign.

Most forays along the innovation frontier do not occur in the void of empty space. Incumbents resent incursions on their turf. Going boldly where no one has gone before entails encountering new situations in which historical precedent may have limited utility; traditional tools may not be effective.

American pioneers and more than a few astronauts and scientists like Marie Curie learned this lesson the hard way:

the frontier is full of risk.

Large regulated financial firms know that taking a new path means risking exposure to downside risk and loss. They approach alternative data as an expedition into the risky frontier full of unknowns. This is a nuance about our industry that few outsiders truly appreciate.

Many mistakenly confuse the search for alpha as the quest to take risk with glee. They forget that financial professionals are either fiduciaries or they provide essential services to those fiduciaries.

Financial firms allocate significant sums and considerable effort to detecting and measuring risk in order to price, manage, and minimize it.

Risk – often presented in the form of market volatility – is to be respected and minimized. Financial firms may chase alpha, but they will only trade based on informed, data-driven decisions after exploring the contours of risk and how risk profiles shift under certain circumstances defined by scenario analysis and stress tests.

Alpha gains are acquired by finding technical insights and details that other market participants have missed.

Alternative data delivers new, more efficient vantage points
for risk detection and risk pricing.

The easiest data sets to acquire are those that align with established risk models. For example: alternative data from satellites or cell phones provides new measures of retail foot traffic (if privacy issues can be addressed). But the core risk analysis (the correlation between foot traffic and retail sales) already exists. The expedition into the frontier is minimal.

Language-derived alternative data is the next frontier for value creation, as we noted HERE recently. The daily rate by which digital language data is created every MINUTE of the day is staggering (searches, social media posts). The amount of language data increases when we include blog posts, reports, speeches, newscasts, etc.

Much research into human behavior over the decades at least provides a framework for analyzing retail-level communications. Other kinds of language-derived data must demonstrate multiple layers of validation.

Being on the frontier requires showing a nexus with market movements (see our own backtest results HERE), preferably with advanced notice, advanced speed, or both. For example, capital markets acquire machine-readable news feeds and faster access to market-moving headlines than firms that rely on human readers. This minimizes exposure to headline risk and accelerates trade execution.

Recent technological advances have enabled some academics to demonstrate mathematically what markets have known for centuries: markets respond to the news cycle. As our own patented process illustrates, technological innovation accelerates access to a broader range of actionable information regarding public policy language on the path towards a decision.

Volatility and the Shifting Boundary of the Frontier

Market volatility arises when financial markets rapidly re-price risks, often in response to an event. When exposed to risk of loss from market volatility, the first question is whether the event could have been expected. Public policy in many ways is the ultimate event risk, alongside weather.

Market volatility has a funny way of foisting the frontier on a portfolio manager. If a portfolio manager is not paying attention, he or she can wake up transported to the frontier with few tools to help them navigate a route back to safety.

Consider Jamie Dimon’s most recent shareholder letter. He discussed how COVID-19, monetary policy, and Russia’s invasion of Ukraine create the risk that the bank could lose as much as $1bn due to “completely different circumstances than what we’ve experienced in the past…While it is possible, and hopeful, that all of these events will have peaceful resolutions, we should prepare for the potential negative outcomes.” He also noted that policymakers are not-so-silent partners in corporate success. He is bracing for losses while hoping for the best.

If only there were a way for financial professionals to be able to measure the risks inherent in the words that government officials utter.

If only there were a way for finance professionals to do what the President of the United States does (focus on action)

and then use quantitative data drawn from the language to measure the risk and the opportunity. For example, one can define the size of informational advantages as the delta between official sector action and media coverage.

Oh wait….we have that tool already. It’s called PolicyScope data and it is generated using 9+ layers of patented analytical automation.

The frontier of alternative data (language-derived data)
may seem risky at first
because it has not been used before.
But the alternative is worse:
experiencing losses knowing that the risk could have been measured, anticipated, and managed better
using objective data.

Once an alternative dataset becomes familiar, portfolio managers have a completely different experience.

They abandon the covered wagon that journeys slowly along well-worn, risky ruts. They use alterative data to out-run risks by riding a more powerfully and technologically advanced vehicle. The question is how long it takes to summon up the courage to board the train.


BCMstrategy, Inc.helps portfolio managers and strategists anticipate market volatility related to public policy/headline risk and take strategic positions in the market by delivering quantitative volume-based objective data drawn directly from the public policy process paired with data generated from media coverage from fact-checked journalism publishers like Dow Jones and ThomsonReuters. The full data set is available exclusively through the Bloomberg Enterprise Access Point. Volatility signals are available via API. Charts, graphs, and verbal data are available through the V3 PolicyScope Data app on the Bloomberg Terminal at: {APPS PLCY <GO>}.