This week, I am finishing my second graduate course toward earning my Master of Science in Personal Financial Planning. What’s been interesting for me in taking graduate courses in the field I have worked in for years is that I have had the opportunity to think about and test in a very different sort of way the research and work I have done for clients, while hopefully learning some new ideas or at least some fresh perspectives on different topics. A couple of weeks ago, I was asked in a prompt to compare what the stock market and trading was like 100 years ago, and the information that was available or not available, and compare it to the wealth of information available today and to share some insights on the markets in that comparison. What I did not expect from this prompt was to hone in on a key point of how Briggs Financial approaches the market differently and why an underlying assumption that has permeated investing for the better part of fifty years is just flat wrong.
Some background information: About fifty years ago, a Nobel-prize winning economist named Eugene Fama wrote a paper that spelled out what is known today as the “efficient market hypothesis.” This hypothesis suggests that asset prices reflect all available information, and that it is impossible to “beat the market” consistently on a risk-adjusted basis since market prices will adjust to take new information into account. In that paper, Fama suggests three empirical “tests” of efficiency; these are the weak-form, semi-strong-form, and strong-form tests.
The weak-form test stipulates that the market knows all pricing information historically and that pricing has been factored into the current price of a stock.
The semi-strong form stipulates that all publicly available information has been digested and factored into the current price of a stock.
The strong-form test stipulates that all public and private information has been factored into the current price of a stock.
As you can tell from these definitions, you have three levels or depths of the hypothesis that govern the degree to which the market is efficient. Now let’s go back to the question I was asked in class – if I was to compare what information and efficiency looked like 100 years ago to now, what forms of efficiency would I attach to those markets? Well, 100 years ago, we were using quote books to look up prices on companies, with virtually no insight into the business details of any given holding. Today, you can literally pull up an app that will let you sit in on any earnings call in the world, instantaneously. We can easily see previous pricing and volumes – we can even see how institutions are purchasing, let alone the broader market as a whole. It would be very easy to argue that at a minimum, we have weak-form and semistrong-form information baked into the market. Based on that, you might draw the conclusion that it is virtually impossible, given all that information baked in, to even attempt to beat the market. If that’s what you’re thinking, well, you are very much in the majority. According to a 2019 report by Yun Li of CNBC, 80% of trading is now automated, driven either by index funds/ETF’s (60%) or quants.
But I think the real question is, does the availability of information translate into efficiently responding to that information? In a 1988 letter to shareholders, Warren Buffett cuts through efficient market theory with a searing statement, comparing the 63- year performance of Berkshire to the broader market. “A $1,000 investment in an index fund would have grown to $405,000 . . . a 20% rate of return, however, would have produced $97 million. That strikes us as a statistically-significant differential that might, conceivably, arouse one’s curiosity.” He then continues “Naturally the disservice done to students and gullible investment professionals who have swallowed EMT has been an extraordinary service to us and other followers of (Ben) Graham. In any sort of contest – financial, mental, or physical – it’s an enormous advantage to have opponents who have been taught that it’s useless to even try.” Buffett then concludes this thought, stating “An investor cannot obtain superior profits from stocks by simply committing to a specific investment category or style. They can earn them only by carefully evaluating facts and continuously exercising discipline.”
As I ruminate on this point, I call back to the citation of Yun Li – 80% of the market now hinging on the very premise Buffett struck down. While a great sea of information freely exists that investors could be using to make investment decisions, they just aren’t. They have bought into the notion that, perhaps out of ease of use or ease of mind, or perhaps out of truly believing that the market is efficient in any respect, they are sold on just accepting what they perceive as “average” performance, as though it is some sort of safe haven, and calling it a day.
And yet while even the likes of Buffett concede that the market is “mostly efficient,” we don’t have to look back very far to find some really gross inefficiencies. Just look at Apple’s stock performance during the final quarter of 2018. It started the quarter at $56.99 a share. By December, with no material changes in the company, with no huge loss of capital or evidence of sales slowing or anything – ANYTHING – to do with the underlying company whatsoever, it closed on Christmas Eve at $36.71, down nearly 36%. One year later, the stock is trading at $72.48 a share – DOUBLE from one year prior. And on the 10th of December 2020, as I write this article, what is Apple trading at? $123.24 a share, up 70% from less than a year ago, up over 235% from Christmas Eve two years ago. And you’re trying to tell me that this market is efficient, that somehow this is supposed to just average out and make sense and eventually the world will just “catch up?” How many years will that take? Or perhaps the position is that I have just cherry-picked a situation – I would counter that even in just that time frame alone, there were many, many mispriced positions, ones with even better numbers that what I have just described here, and this is just one episode. Or maybe, perhaps, the reactionary and emotional behavior humans have, combined with the reactionary and split-second behavior algorithms have, are feeding into one another and creating large forms of inefficiency not modeled effectively by the bell curve. And what if there are enough situations where contemplation, fundamental analysis, risk-reward management, tax efficiency, and patience outplay the behavior I’ve just described?
At what point do you gather the number of anecdotes, bundle them together, and conclude that Fama and his Nobel-winning friends are living in a world of mathematical fantasy with little to no regard for the dynamics associated with these living, breathing organisms of businesses? How many times can a situation be chalked up as an outlier, especially one involving literally one of the most market-cap rich companies in the history of the world? At some point, you have to look at this and conclude as Buffett has – “mostly efficient, but not entirely,” and play accordingly. The way I have chosen to play accordingly with our investment strategy is in two key behaviors – the two clearest ways in which the lemmings of the automated 80% of the market does not consider and/or does not act by:
1. Deeply analyzing the fundamentals of investments, selecting investments that promote growth and thought leadership, that provide an attractive risk-reward value, with as many ways to win as possible while also avoiding qualities that either threaten the underlying value of the investment or do not provide sufficient risk relative to reward.
2. Moving at a glacial pace with respect to investment decisions by making measured, calculated, informed decisions based on broad swaths of information and avoiding decisions based on daily, weekly, monthly, and even quarterly measurements of performance.
Charlie Munger, vice chairman of Berkshire Hathaway has a saying that “you’re smart and I’m right, so eventually you’ll agree with me.” I do think that over time, the market will at times appreciate in the same way the positions we take, particularly times of difficulty/duress. By actively measuring the risk-reward we are taking in the pursuit of growth, while maintaining a long-term view of what we invest in, I believe we emerge with two distinct advantages. First, I believe we capture more growth because we are not in any way attempting to “time the market” with respect to our investment outlook – I believe I understand the potential upside for what we are investing in, but entirely concede that I do not know when and/or if that will be realized. And second, I know we avoid tremendous cost being frittered with respect to transactional fees and taxes (these aspects are measureable, finite, and certain).
Going back to the question at the beginning of this article, about how the market and investing today compares with investing in the market 100 years ago, here’s what I have to say. 100 years ago, people were buying and selling positions with a lack of access to information. Today, people are buying and selling positions in spite of having access to information. The inefficiencies today are different from the inefficiencies in the past, but I would argue that while trading looks flashier and more sophisticated now, the same fundamental gaps in analysis remain. The behaviors look all too similar, and with that I believe opportunity is still alive and well for the value-oriented, thoughtful, empirically driven investor.