Shakespeare’s Juliet once famously asked “what’s in a name?” If you know the play, she was talking about roses and how they would smell as sweet, even if they had an alternative name. Would her modern-day self not ask the same about data? And what makes today’s alt-data different from plain old data, such as the Cuneiform writings developed by the Sumerians of Mesopotamia circa 3500 BCE?
Data in fact is, well…just data. The difference, perhaps, is the explosive volume we have experienced in the recent decade, mostly due to the advent of the smart phone and the digitization that came with it. We have tweeted, liked, searched, and shared our way to an impressive 4 billion webpages and 1.2 million terabytes of data, as the seemingly omnipresent sensors capture our every emotion and impulse. This beast needed a name and some clever Madison Avenue wizard, or maybe it was Al Gore, came up with the moniker, alt-data.
What makes alt-data different is that it is mostly a story about the size and structure of data sets that separately, or together, can potentially provide an information edge to virtually any industry, including those practicing the craft of asset management. One could naturally conclude that this edge can be monetized into untapped alpha but a recent paper in The Journal of Financial Data Science entitled Rethinking Alternative Data in Institutional Investment did a very good job of debunking this opportunistic use-case to one mostly seen amongst the day-trader crowd. The use of alt-data by the market participant on the couch versus the more patient investor who thinks about the concepts of risk management and organizational alpha is as different as the Montagues and the Capulets.
Public markets have become highly efficient. At every moment, a geopolitical flare, an earnings surprise, or a tweet, can cause bouts of volatility. In the short-term the markets become a less efficient voting machine and the opportunistic trader looks to pounce and profit from these gyrations. It is becoming increasingly difficult to exploit these opportunities as the correlations of the trading algorithms move closer to 1, and the investment process and philosophy of being able to find good ideas faster than the competition, is neither sustainable nor of institutional quality.
The paper goes on to talk about the anticipatory benefits of this data and how it can help build a better thesis around the direction of inflation, a company’s true conviction and exposure to ESG risks, or the ability to monitor an emerging market project and the inherent agency problems of local management, using orbital imagery. These types of risk-based approaches should yield better outcomes for the patient investor and provide for more context around the fuzzy border of the fat-tail that can erode years of wealth creation in a single swoon. The concept of organizational alpha is equally well developed around the simple approach of eliminating internal inefficiencies; easier said than done, but the successful investors have long understood that less cost equals more alpha.
Investors need to get with this alt-data program either by outsourcing innovation to their asset managers or developing partnerships with alt-data vendors or other service providers. As the paper concludes, this space has become too big to be relegated into the ‘passing fad’ category and every asset owner, asset manager, regulator, and educator needs to take a stand. As for the CAIA Association, our answer is the FDP Institute and the FDP Credential and it should be no surprise that the above referenced paper is part of this new curriculum. It’s your move; a rose may always be a rose, but thou industry will be forever changed with the alpha and beta of alt-data.
Seek diversification, education, and know your risk tolerance. Investing is for the long term.