Data gathering and mining has now advanced to the level that if information was the variable missing in the Efficient Market Hypothesis then the market should fast be approaching perfect pricing. Perhaps it is rationally priced for a specific moment in time. However, the next piece of information reshapes market reasoning and changes assumptions and then prices. Much of the thinking behind stock analysis in academic work has been concentrated on information changing the price of an individual stock or occasionally an industry. Through artificial intelligence and the old-fashioned wisdom of crowds, we suggest that one data point can ripple through the marketplace instantaneously evoking the famous butterfly effect or simply be market noise. It is humans not computers that own the skills to separate economic shifts from noise but only if expertise does not beget blind spots.
We imagine information as a continuum with tasks only humans can do on one end and tasks for computers on the other end. Moravec’s paradox states that computers can do very complicated tasks quickly involving logic but fail at perception. Moravec reasons that there are skills that have taken humans millions of years to fine tune such as reading a face for anger. The paradox is that the longer humans have been developing a skill, the less qualified the computer will be at mastering it. We break down the impact of information on economic changes into three subsets from noise to disruption. It is our contention that the simple skills are market noise that computers do exceptionally well at exploiting. However, there is information along the continuum that humans can utilize more efficiently than computers because of expertise. This will only occur when the expert is not assuming expertise is the only tool needed and remains receptive to the new information.
Continuum of Economic Information
We categorize the magnitude of the impact of economic information into three subsets:
The most common of the three disadvantages humans. Investors have a bias to believe that almost all new information is simply noise. Whether the C-suite has immediate departures interrupts sales patterns and the quarter had one less day to sell product are all common announcements that depress a stock for a short period of time before returning to equilibrium. Algorithmic trading has been exceptional at exploiting price differentials created by short term market anomalies.
- Economic Setback
This is described as the point where market noise begins to impact the economic results of the company. In common vernacular this is the grey swan. The negative announcement turned out to be the beginning of a string of negative announcements. When investors realize that it was not weather but inferior market positioning or the entrance of a superior product that led to soft sales, stock price change occurs. At this point the company is affected and potentially the competitors with the same market deficiencies. This is near the tipping point that humans have over computers.
The grey swan is so dark it borders on black. The marketplace is changed for all participants and there will be ramifications in the supply chain and beyond. Computers are deficient to humans in solving for disruptive trends such as the satisfaction of taking the first Uber ride versus driving.
Although humans have a distinctive advantage in observing disruptive trends, expertise may play a negative role. Arien Mack’s seminal work Inattentive Blindness suggests that the brain fails to notice an image or an event that is fully visible. (The common trick is to have someone counting basketball passes as man in a gorilla suit walks through the middle of the game. Usually 50% of the participants do not see the gorilla). One of the causes of inattentive blindness is the lack of cognitive capture from an easily observed stimuli. Prior focus to a matter on hand leaves one unable to spot the obvious.
Analyzing business environments consists of observing stimuli (such as economic noise) while filtering it for relevant information. Expertise allows one to filter information faster than a non-expert but also risks the investor’s version of inattentive blindness. Expertise is acquired by concentrating and following rules. As the investor focuses on an economic landscape that is consistent with her views, she may miss the obvious as she is not expecting change. Gorillas may be walking through basketball games unnoticed as the investor is focused on her checklist and remains inattentive to obvious change. Our eyes are not cameras taking pictures for us to review later, they see what the brain tells them to see.
The biggest mistake an investor can make is not seeing a disruptor entering an industry. Often it is the result of a technology that appears trivial at first until it grows to be economically dominant over the incumbents. Expertise in an industry may make it more difficult for an investor to observe the beginning of a phase of disruption because numerous observations of economic noise dull the senses. Although the investor’s brain is better suited than a computer to observe the sea change of disruption, concentrating on a known set of rules may make the obvious unseen.
The Gorilla in the Room
Investors need to realize that blind spots exist due to their expertise. It is necessary to ask oneself if we are too focused on what we want to see to catch the gorillas in the room known as disruptors.