Technology changing the world is nothing new. Homo Sapiens (that’s us) have been doing it since cave man times. Eons ago, the first man (and woman) learned how to make fire. Fire not only cooked dinner and warmed the cave but used overnight at the cave mouth kept out predators crouching in the dark looking for a meal of their own. Fire was good.
Later our ancestors chipped flint into arrowheads and cutting knives. That was progress. Next came domesticated animals. First dogs for safety and companionship and then cows for milk. In the Bronze Age we figured out how to forge metal in furnaces for even better tools. Progress has never ceased.
Developing and using new tools for our betterment is unique to our species and arguably the primary reason we are at the apex of life on earth. Progress has come so far that with the ever increasing computing power generated by better semiconductors, computer scientists now have their sights on tools that no longer require humans to operate them. Artificial intelligence will set all sorts of existing tools on their own to operate themselves. The most tangible example is self-driving vehicles. Most everyone in the investing world seems to think that self-driving cars and trucks are a given and the major question is when, not if, they become ubiquitous. Most seem to think they will be here in the very near future, certainly within the next ten years. Count me as skeptical.
Technology has Its Limits
Despite what our optimistic culture, particularly our mostly always bullish business culture espouses, technological progress has its limitations. My first job in the investment business after graduating from the University of Chicago’s Graduate School of Business (now known as the Booth School of Business) was analyzing the wireless and cable telecommunications industry. That was way back in 1996. My first few weeks on the job I immersed myself in learning the industry and its future prospects. As with today’s emerging technologies, Wall Street had tremendous faith in wireless. I recall reading reports that eventually wireline technology would die off. The existing system of landlines would be entirely replaced by wireless. Why pay to wire new buildings or homes when wireless would get you connected at a much lower cost?
Although most of the projections about wireless telephony were met or exceeded, the full replacement of wireline never happened. Why? It’s simple. Twenty two years after I read those reports wireless reception is still inferior to landline. The technology is great but it has its limits. Just the other day, while waiting in the Delta lounge at LaGuardia Airport for a flight back to Florida from New York, a cell call I was on dropped 3 times. This was not on some rural road far from a nearby cell tower. . . it was in a major airport in the so-called financial capital of the world.
Which brings us back to self-driving cars and other vehicles. Can scientists really develop a system for self-driving cars that will run seamlessly without failure? Certainly they couldn’t do it for wireless phones. But when wireless phones don’t operate properly lives aren’t at stake (at least not usually).
Can technology really cost effectively deliver a self-driving car that doesn’t malfunction at a rate that would cause far more accidents than the public would accept? Perhaps someday, but, not likely soon.
On the other hand, the technology that is being developed for self-driving cars is already useful and making auto travel safer. For example, systems that warn drivers when cars are in their blind spot or that can sense a driver has fallen asleep are proving effective and valuable.
Technology in CWA’s Research Process
This month’s Risk On / Risk Off report however, is not about artificial intelligence or any other emerging technology. Rather it’s about how our company’s research department uses technology as a tool. Technology helps us to identify new investment ideas and curb our very human but very self-defeating instincts to not break from the herd.
It is not easy to find new investment ideas. There are thousands of equities in which to invest. Bloomberg lists 15,544 companies with a market capitalization in excess of $200 million traded on United States exchanges alone. There are thousands of investment newsletters touting one of these companies or another. There are hundreds of brokerage firm analysts with buy ratings on a slew of companies. Their job is to try to get investors like us to trade in those companies. Besides the sheer number of investments, the financial industry tends to regularly attempt to whip up a frenzy about a new “hot” sector. There seems to be a lot of cacophony and herd behavior.
Followers of our publications know, we try our best to ignore all the noise and to look for undervalued companies and the early macro-economic trends and cycles that create real, sustained opportunities.
Our research team has years of experience doing deep research and knows many companies and their management teams. We also have created many tools to help us identify cycle and macroeconomic condition changes.
However, even with all that, we are only able to scratch the surface of all the potential investments and of being able to evaluate every new hot sector. So, to bridge that gap, we use computer generated screens to dispassionately sift through thousands of securities to identify the ones on which to focus our research effort. These screens are not simple tools that look at technical factors (such as price movements relative to moving averages or the like) nor are they simple fundamental factor screens (such as ranking securities by the Price/ Earnings Ratio or Book Value). Rather, the tools we have developed and refined over many years look at a myriad of fundamental factors and seek to identify deeply undervalued securities that we believe have a high probability of performing well in the future.
What they emphasize is not only finding securities that are cheap relative to their earning power or their peer group but also cheapness relative to the company’s own trading history and the degree to which past cheapness has tended to result in strong subsequent stock performance. For example, we have a screen that does not simply look for securities with high dividend yields. Our screen goes further to look for securities with high dividend yields relative to the market and compares that to where the company’s relative dividend has traded over time. A stock with a 4.5% dividend yield might seem attractive compared to other equities however if it usually trades with a 5.5% yield it might not be. Also, how has the stock tended to trade after it had a 4.5% yield in the past? These are examples of the goals of our tools.
Logic Versus Emotion
Our system does not delegate investing to machines. Far from it. We use technology to helps us humans identify prospective investments for us humans to analyze. Unlike the automobiles that presumably will be on our streets soon, we prefer to keep a real person at the controls.
Technology is a great way to help our brains though. Humans are known for emotional and prejudiced decisions. For most investors, it is far too easy to be swayed by the sentiment of the financial media and the investing crowd. Valuation driven security screens mitigate that. Their dispassionate logic helps us to venture more confidently into controversial, and therefore likely undervalued, securities.
A security that our valuation-driven screens identify as potentially undervalued almost always has something “obviously wrong with it.” That’s likely how it came to be cheap! When we begin to examine these securities and learn of the bad thing or things that have befallen the company or its negative outlook our computer tools remind us that there is a good chance that bad news has already caused the stock to fall . . . it is already showing up as very cheap on our screen. This is known as the news is already “priced into the stock.”
This situation is not uncommon at all. Most great companies fell once into controversy and doubt, at some point, even if only for a short period of time. How about the tremendous flop of “New Coke" for the Coca-Cola Company? Who could forget Johnson and Johnson and the Tylenol poisoning controversy? Moody’s and the subprime crisis? The cigarette companies and their multi-billion-dollar lawsuit settlements? These companies and their stocks are thriving today, despite navigating tremendous and terrifying disappointments. Investors who braved the headlines and bought while the herd was rushing to sell reaped incredible rewards. This is not easy to do. Seeing these companies on the top of a list of 5,000 securities generated by a computer sometimes gives one that extra bit of courage needed. Certainly it gives us the impetus to really dig in to understand the controversy that has made the security so cheap.
Conclusion
Computers are a great help to an investment program because they help us in important ways, especially in ways we are deficient – being able to sift through thousands of investment ideas to find the already cheap ones and over-coming the danger of succumbing to the emotional negativity of “bad news” when that news has already caused a stock to be cheap. They help us get to a starting point of de-risked and already controversial securities which we believe is the best raw material for a successful portfolio.
As noted above, we do not let the computer model choose our investments, only to optimize our research effort. However, the computer models we have built are smart, perhaps smarter than our own brains whose logic inevitably is subject to emotion and prejudices. I, for one, have tremendous respect for the computer screens we use and have come to take very seriously the output they generate. I have often ignored their recommendations because my fundamental research led me to conclude the cheapness of the company was not adequately reflected in the stock. In those situations where it was a tough call and ultimately came down to a decision between my gut and the computer, the computer was right far more often than I care to admit.
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Sony Ericsson cell phone circa 1996. Source: Google Images