Be honest: have you ever read the Terms and Conditions page on WebMD? If you had, you would’ve surely noticed the bold, underlined disclaimer stating, “The Site Does Not Provide Medical Advice.” Yet, as any doctor might describe, one of his or her greatest daily frustrations involves patients who have already self-diagnosed before setting foot in the office. Unto itself, WebMD is a great resource…if used correctly. But who hasn’t read a list of symptoms and concluded—even momentarily—that a simple stomachache or sprained ankle might be a far worse malady? The sheer knowledge of such possibilities brings on new levels of distress. And worst of all? With such information so readily available, it’s practically impossible to avoid searching it out. Such is the double-edged sword of the democratization of information.
Yahoo Search Bar: Where are we?
Throughout history, as new modes of communication became available, humans struggled to both adopt them and adapt to them. This was the case in pre-history, as humans battled superstition, and the struggle took a quantum leap forward with the arrival of the Gutenberg Press. Each new advance—be it the press, standardized education, or television, for example—faced resistance from certain segments of society. At one time, television sets were so stigmatized that the mere act of sitting too close was considered dangerous. So what makes our current day’s information overload different? The democratization of information, while an incredible advance for humanity, has also equitized its spread in unpredictable ways. If everyone has a megaphone, how can we best weigh their message appropriately?
We saw this come to a head as the nation battled the pandemic and people “picked” their information sources. At such a critical juncture in the history of information dissemination, opinions were incredibly easy to obtain yet just as difficult to interpret. Those who didn’t want to wear a facemask had plenty of voices backing their cause. And those who thought facemasks were a worthwhile precaution had abundant sources backing their stance. Every decision in 2020 seemed to come down to what side a person chose. Information, unto itself, was no longer the ultimate arbiter of truth when people could pick and choose the data source that validated their pre-existing opinions.
The world of investment and finance was not immune. Never before in the history of financial markets has so much information been so easily accessible. A tug of war ensued between the economic damage done by the virus and the backstop of the Central Bank rescue. Once again, people had a choice about which information they chose to believe. The market staged the quickest recessionary downturn-and-recovery in its history, assets sloshed in and out of the major indexes and a decisive winner in this tug of war has yet to be declared. Yet this transformation of the industry did not happen overnight. In fact, like so many roads that go down unintended paths, this data availability started off with good intentions.
Google Page: When did this happen?
Although the idea had been conceived ten years prior, the SEC’s Electronic Data Gathering, Analysis, and Retrieval system, EDGAR, began in earnest during the dawn of the internet in 1993. To that point, investors who wished to view public company financial statements and other filings would need to file specific requests, which were themselves printed on paper, and then wait for a package to arrive in the mail. With the advent of EDGAR, they could access the same information in a matter of seconds.
However, with this new proliferation of information, came frustration. Some companies were divulging material non-public information to their preferred investors and analysts prior to the information’s public release, giving those special few an enormous advantage over typical investors. The SEC took notice and, in October of 2000, passed Regulation FD. This required companies to make available to the public the same material, non-public information otherwise limited to preferred constituents. Concurrently, the internet irrevocably altered everyday life by making information both simpler to process and more convenient to access. Put side-by-side, this flood of equitizing information should have been a godsend for investors everywhere. But, as we know now, this democratization of information had many unintended side effects.
“Alexa, how did we get here?”
Choice is a funny thing. While nearly universally lauded for obvious reasons such as freedom and self-determinism, there was a reason Steve Jobs, for example, wore the same style shirt every day. He recognized the danger of Decision Fatigue and actively took steps to limit his choices on mundane matters. He wasn’t the first to grow skeptical of the deleterious effects of such information overload. As sources of information exploded, entire branches of science have evolved to examine its effect on people. In 1974, for example, a landmark study by Jacoby, Speller and Kohn Berning proved that more information actually led to poorer decision making.
Meanwhile, in the financial realm, the rise of online trading platforms such as Robinhood has been a direct result of both this data availability revolution and the convenience designed explicitly for at-home investors. But such unconstrained access begs the question: what is the difference between a liberating movement and a child escaped from the playpen? Because if one thing is certain, it’s that an ignorant person never appreciates quite how ignorant they are. The well-known Dunning–Kruger effect proves as much. And if such a cognitive bias causes people with low ability to habitually overestimate their aptitude, how is it possible to get an objective analysis of one’s own decision-making skills?
H-Factor System: Where do we go now?
The Achilles Heel in this democratization of information is obvious. Human behavior and lazy heuristics have created a maelstrom of informational noise. People are now implicitly encouraged to arrive at a conclusion first and then search for supporting evidence afterward, without any formal process to account for contradictory data. As a means of problem solving, it’s entirely backward. In fact, just as too much information results in Decision Fatigue, the same excess can hamper a person’s understanding of risk.
This has been confirmed in many controlled scientific experiments. For example, the Ellsberg Paradox proved that, in side-by-side experiments, people preferred the known odds of an outcome to unknown odds, even though a positive outcome in the first would contradict a positive outcome in the second. A logical paradox resulted that people were blind to. Meanwhile, dating back to Daniel Bernoulli’s groundbreaking St. Petersburg paper in 1738 before culminating in the formal establishment of Prospect Theory by Kahneman and Tversky in 1979, market experts recognized a particularly human weakness: the satisfaction gained from an increase in wealth moves inversely with the quantity of the goods already possessed. The main takeaway from these and other experiments is that people, consciously or unconsciously, disregard known information in favor of a more intellectually comfortable option.
But investing isn’t a comfy sweater or a nap on the couch. One can’t choose which investment risks are real and which are not. Because to us, the hard truth is the only risk that matters is the risk of human behavior. And to mitigate this risk, we believe one needs to avoid the informational noise, focus on a very limited set of data and select the correct metrics most reflective of this problem.
We believe vague and ambiguous information is interpreted by humans in a systematically incorrect way. This information is impounded into stock prices leading to mispricing. It’s called the H-Factor. At New Age Alpha, we measure the H-Factor’s effect on stock prices to identify which stocks are over- or underpriced. We believe that by measuring the H-Factor and deliberately avoiding stocks with high H-Factor (i.e. stocks that are overpriced), we can outperform.
The democratization of information has been a great advance for society, but we argue it needs to be tempered with an acknowledgement of ignorance. It’s impossible for a person to read everything available. And it’s not advisable to try. In this manner, we look at risk very differently than other managers. Instead of worrying about volatility or beta—or any other risk measure for that matter—we focus on asking one question and one question only: Can the company deliver the growth implied by its stock price? Our goal isn't to pick winners but to simply avoid losers.
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