Excuses, excuses for poor performance
The investment industry believes the stock market is fairly efficient. They feel stock prices reasonably reflect fair value. The proof is said to be that if there were significant inefficiencies to exploit, the better investment managers would regularly outperform the indexes.
When I started investing, by a stroke of good fortune, I never learned about the EMH and the random walk. It would have put me off pursuing the approach I have followed. In fact, I barely was aware of it. When I did become aware of it, I never read up on it because it never had any intuitive appeal to me. I ultimately decided to find out more about it to see if I was missing something and perhaps learn from it.
I believe the EMH is fundamentally flawed. The stock market is more accurately described as a messy adaptive system. I like to use the expression Inefficient Market Hypothesis to make a rhetorical point.
Here’s the basic thesis: My view is that prices in the stock market are never a reliable guide to the fair value of a stock. Warren Buffett’s words in the 2008 Berkshire Hathaway annual report could not be clearer: “Price is what you pay. Value is what you get.” I emphasize the word reliable.
Let’s examine the evidence. A full on refutation of the EMH is contained in Andrew Smithers’ 2009 book, Wall Street Revalued, Imperfect Markets and Inept Central Bankers. (Smithers, 2009). Smithers is British and an economist by training. He has had a long career in investment management and currently runs a consultancy on international asset allocation.
In a forward to Smithers’ book, Jeremy Grantham, Chief Strategist and Chairman of Grantham, Mayo, Van Otterloo, now known as GMO, writes: “The EMH ruled the academic waves for 50 years, and for the majority of the time – say, 1968 to 1998 – it was found to be nearly impossible to get tenure or peer reviewed articles published in prestigious journals if you espoused views deemed heretical by the high church of ‘rational expectations!’ (Smithers, 2009)p.vii. Grantham takes pleasure in describing EMH as the ‘most expensive mistake – or simply the biggest mistake – in the history of finance.” (Smithers, 2009)p.vii.
Smithers’ thesis is based on comparing the long term growth of what he calls ‘corporate net worth’ and stock prices. His pictorial representation of this is a one hundred year chart showing the growth of corporate net worth at a relatively stable rate. The line slopes up from left to right at about the same slope. It has some minor squiggles. Superimposed is a chart of market prices based on an index which slopes upward from left to right at about the same slope but with much larger squiggles representing the volatility of the stock market. The more volatile chart of prices crosses the more stable chart of values only periodically. He depicts this in Chart 10 in his book. (Smithers, 2009)p.52.
US Non-Financial companies Net Worth and Market Value
I hate Smithers’ use of the term ‘market value’. What he means and what he is showing is market price. I count at most a dozen times between the years 1900 and the year 2000 when the lines for net worth and stock prices coincide. For the rest of the time, prices either exceed net worth or are lower than net worth.
A more recent graphic representation of the relationship between prices and intrinsic values is taken from the GMO November 2013 letter:
Real prices and fair value
The GMO graphic is described as being based on the Shiller model and Shiller’s calculation of historic fair value of U.S. equities. The calculation is based on an ex-post present value of future dividend stream approach.
Both of these graphics depict the fair value of the stock market as a whole. This is difficult to do. It is much easier to assess the fair value of an individual stock. This is done using discounted cash flow calculations along with subjective inputs.
The next figure is a chart taken from a current Morningstar report charting the price and fair value of Apple stock. Prices are the blue line and fair value the yellow line. In 2017 and the first half of 2018 the two lines track each other fairly well. At other times there is wide divergence and infrequent crossing of the lines.
The simple truth is that a divergence of even a few percent between price and fair value is a significant inefficiency.
One shouldn’t expect that recognizing the stock market as messy and inefficient will make investing any easier. Stocks may be seen as underpriced and even bargains but they may remain so for a very long time. Similarly, an overpriced stock or an overpriced market may remain overpriced for ages. As well, an underpriced stock may become significantly more underpriced over time, trying the patience of any investor.
The long term investor is not daunted by this. They expect that some stocks in their portfolio will be returning to fair value from being underpriced and that some stocks in the portfolio that have reached fair value will actually be on their way to being overpriced. These repricings may take place over the long term or they may happen quickly. At the same time some stocks in the portfolio will be repriced downwards by the market against the fundamentals. One hopes that the upward repricings will more than offset the downwards. This will be the case if the stocks acquired are stocks of superb companies bought with a sufficient margin of safety.
Even the vaunted ability of the stock market to react in a quick and efficient manner to news or new information is in question. Experience is a far better teacher of many things. In some ways the stock market is particularly inefficient even at digesting news. See Section 6.01 Reacting to news.
Investment professionals take comfort from the notion that market efficiency prevents them from outperforming the market. They have it wrong. It doesn’t take much of an edge to outperform the market. In a messy, inefficient market, investors are better off looking to control their own human frailties and take advantage of Mr. Market’s foibles to find alpha.
Eugene Fama has said that critics of the EMH hadn’t come up with a better model. I suppose Fama was looking for a model that was amenable to mathematical treatment and statistics. This may not be possible. This will come as a disappointment for the positivists of this world.
But Humans have been able to function in markets for thousands of years without mathematical models. I am not suggesting that statistics and mathematics could not be used to model the stock market. What I believe is that the models will have to be a lot more sophisticated than four factor models or whatever is the current state of the art.
Someone will use artificial intelligence to take on the market. The main problem is that computers may be good a dealing with risks but will have a hard time with uncertainty. There are a lot of things that count in investing that can’t be counted. Whatever they come up with we can be sure it will be a long way from a model based on coin flipping randomness. Or perhaps we just don’t need a model in the sense of a model that is capable of statistical or mathematical analysis.
In particular, Chapter 6 contains Section 6.01 Reacting to news, Section 6.02 Stock market as a complex adaptive system with feedback loops and Section 6.03 Feedback effects
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