If you believe the efficient markets hypothesis, don’t follow this blog

In order to help you understand how to improve your investment returns, dear reader,  I wanted to rant on how academic economists, supposedly the bastions of rational thinking, independent of commercial bias, the smartest of the smart, created and promoted a completely irrational theory, causing millions of people to not even consider investing for fear of a random raw deal outcome. Blinded by their own dark assumptions, the well-meaning economists only saw what they wanted to see. This insidious theory has been responsible for many people not even considering investing, completely missing a much more effective source of income than mere savings accounts, as a result ending up much poorer than they could have been. I was once in this category, as a result of my mis-education, but now I see the light.

The efficient market hypothesis (EMH) nearly institutionalized defeatism. Fortunately, sensible investors have disregarded this particularly insidious intellectual plaything of academic economists. Nobody really defined it clearly, so it was difficult to prove or disprove in any form. As a result, it’s stuck in investors’ minds for a long time, regardless of the number of studies done on the topic. Even assuming it’s internally consistent and sound, the proponents base the EMH on a number of incorrect assumptions.

The EMH’s even become the source of existential angst of the entire asset management industry, as investment funds such as mutual or hedge funds do not provide any value if market returns really are random. It’s really time for the EMH to go the way of the Vanilla Ice flat-top haircut, as per Jim Carrey’s spoof below:

The real question for investors is not whether financial markets are theoretically efficient; the real question is how to make money in a jumpy and volatile, but somewhat predictable market. In my mind, the EMH only proves how easy it is to fall prey to your own biases and the tools you know well. What follows is a humble practitioner’s summary of the counterarguments against the EMH.

What is it exactly?

Good question. Nobody has really decided on one definition. You can see a comprehensive list of how the definition has evolved over time, i.e. how the goal posts have moved as papers have been published. U of Chicago economist Eugene Fama, the godfather of financial economics, contributed probably the most well known and cited articles defining the EMH, including Efficient Capital Markets: A Review of Theory and Empirical Work.  “‘A market in which prices always ‘fully reflect’ available information is called ‘efficient.'” In it, he suggests that you can test whether a particular market is efficient, based on the availability of information to investors.

  • Weak Form Efficiency: Using only the price history
  • Semi-Strong Form Efficiency: Using all publicly available information, such as financial statements, market analysis, etc.
  • Strong Form Efficiency: Assuming all information is known, including private information that hasn’t been released publicly.

The significant academic paperwork has explored whether this has been empirically true in different markets over different time frames, and the results are decidedly mixed. I’m not surprised.

Even at the level of the definition, it breaks down somewhat, as it doesn’t specify exactly how how you determine an asset is “efficient”. In order to figure out whether a particular instrument is priced “efficiently”, you need to have a sense of what it’s intrinsic value is, similar to the argument in fundamental indexing. As a result, the EMH on its own doesn’t really say much. The capital asset pricing model (CAPM) was favored by the original proponents of the EMH. All in all, it is a good start, but we need to keep in mind that this adds a number of other assumptions, such as fixed time frames which aren’t particularly helpful either.

Investors are merely anomaly chasers….according to defeatist EMH dogma

In his discussion with Russ Roberts on EconTalk, Fama arrogantly discounts EMH naysayers as pure anomaly chasers. What?!? Chasing anomalies has always been the point of both investing and trading. Even though financial markets are more efficient than others, they are far from being completely efficient. If you believe that a market is random, then anyone who tries to disprove you would be pesky and inconvenient.

Psychological biases play a big role. In momentum investing or trend following, you seek out a good stock that is atypically endowed with abilities or characteristics that will cause it to outperform. If you time you jump on the trend at the right time, timing your entry with price and volume signals, you are actually using supply and demand information for that particular stock.  Even our perception of volatility can be significantly influenced by fear, even though we think we are being rational, according to financial planner R C Peck. Buy low and sell high also produces consistent return, as it does in any other market.

Markets exist to be traded, regardless of whether you are talking about traditional wheat commodities hedging, or buying a loaf of bread at Wal-Mart. Prices fluctuate. While the speed of reactions is much faster in financial markets than at the grocery store, some investors are better than others at playing the probabilities. Claiming that it’s just pure randomness is just a cop out. You don’t need to really look for the anomalies. It even makes you look smart.

Markets can stay irrational longer than you can stay solvent

The key real world assumption which the EMH tries to avoid, is that people are not rational. Barry Ritholz from The Big Picture summarizes:

My own short but devastating critique of Fama’s EMH, which according to Siegel, “states that the prices of securities reflect all known information that impacts their value.” That assumes that there is nothing in the price that is non-informational in nature — no emotion, no panic, no greed. That is simply wrong. It is the fundamental failure of EMH.

People are far from rational beings, whereas the EMH tries work from the assumption that they are. It would be theoretically convenient for economists if people were machines, but the world would be an insufferably boring place. This lack of rationality leads to bubbles, distortions, followed by illiquidity. Ritholz continues in a different post:

The entire profession took a theory that had some value to it, and extrapolated it to the point of magical thinking. …Classic economic belief systems could not appropriately anticipate in advance or even identify in real-time what was happening with the Residential RE/Housing market. They failed to see the Great Recession coming or even the market collapse.

Because the theory’s results diverge so far from how investing actually works, its usefulness is questionable. It doesn’t explain either how this does work, or even how it should work.

Just because a distribution looks random, doesn’t mean you can ignore patterns

In a famous debate between value investor Warren Buffet and academic finance professor Michael Jensen, Buffet pointed out that that there are clear patterns characterizing some of the outperformers. Specifically, value investors were often above average performers.  Moreover, Buffet had learned his chops working for Benjamin Graham, the co-author of Security Analysis, along with a number of peers.  This experience helped him and his former co-workers under Graham’s tutelage to outperform typical market returns consistently. This was true even though they were investing in different stocks. You could easily infer this stock picking skill was clearly transferable, and not just random luck. Here is a sample of traditional value investors’ returns:

Investor No. of Yrs Nr of years Annualized return S&P/Dow return
Buffett Partnership 13 29.50% 7.40% (Dow)
Walter Schloss 28 21.30% 8.40%
Tweedy Browne 16 20% 7%
Bill Ruane 14 18.20% 10%
Charlie Munger 14 19.80% 5.00% (Dow)
Pacific Partners 18 32.90% 7.80%
Perlmeter Investments 18 23% 7% (Dow)

Source: http://www.stockopedia.co.uk/

In value investing, you look for anomalies in the form of bargains, except that instead of clipping grocery coupons you are looking for stable cash flows. Debating with bargain hunters and calling them “anomaly chasers” is ludicrous. While it is increasingly difficult to time the moment to buy, a long-term value investor essentially “exits” the market once they find a great dividend paying cash machine. If you buy a dividend stock cheap, you will get a stream of dividends very inexpensively.

The same phenomenon happened in the global macro hedge fund space, at the Tiger fund, which followed an investing style similar to value investing when trading stocks. Julian Robertson, the founder of Tiger, effectively started a “school” of hedge fund managers. His former employees spun off and created successful value-based global macro hedge funds, continuing to significantly outperform indices and benchmarks, including those of global macro funds and typical stock indices. This story, along with detailed performance histories of both Robertson’s Tiger Fund and the Tiger “Cubs”, is detailed in Sebastian Mallaby’s More Money Than God.

While it may be true that the stock market’s overall return distribution is roughly log normal, jumping to conclusions about randomness is  premature. A log normal distribution could just as well be the result of skill, genetic predispositions, or any number of other reasons why. It requires a bit more analysis.  Don’t mix causation with a distribution’s statistical properties.

Buy and hold has no market timing “sweetener”

Most of the original literature analyzing the EMH only looks at traditional mutual funds. Mutual funds were historically designed as “buy and hold” products. You buy the fund, you hold it for may years when it (in theory) outperforms the market, and then you sell it in order to fund something uber-meaningful, like your kid’s college education or your own retirement. The key component driving much of this was the time value of money, where the dividends and returns over time would grow significantly. It was also a product most people want, so that they think they have the “personal investments” box ticked, without actively having to think about it much. All in all, it’s a perfect dream for anyone not really interested in investing, which is most of the world.

Depending on when you buy more of a particular security, you can get a return similar to that of an option. Purely by timing the purchase or sale of your stocks, you can significantly increase or decrease your returns. For example, if you put more money into stocks at the beginning of a long-term market uptrend, this will significantly increase your risk and return exposure. There are a number alphabet soup terms behind this phenomenon, such as constant proportion portfolio insurance (CPPI), option based portfolio insurance (OBPI). Here is a comparison of the two strategies.  Another example is a constant mix strategy, where you hold constant the proportion between stocks and bonds in a portfolio, selling the better performing asset class in order to buy the worse performing asset class of the two. This does not require options or derivatives at all, but allows you to change the returns distributions based purely on when you buy and sell specific assets.

The same logic can really be extended to any asset by any investor. If someone has a well thought out and tested heuristic for timing trades, they can expect to beat a pure buy and hold strategy. A good example of this was market timing “hedge funds”. They invest long-only, typically in the stock market, only when they thought it would go up. Overall they tend to have better returns than “buy and hold” mutual funds which only tweak exposure weights to specific stocks  in order to outperform an index.

(Note to self: Finally, I used some of my CAIA study materials for something useful.) 😉

With proper exits, even on a largely random distribution, you can make money

Buy and hold, particularly how it is presented in the EMH literature, is also a very simplistic approach to investing for another reason. It oversimplifies investing into picking one fund, assuming 100% of you available funds go to that fund for the entire duration of the investment, and that you hold on to the fund, until a predetermined date far into the future. In the buy and hold approach, you do this even if you are losing massive amounts of money in that particular fund. In some ways, this research assumes people will irrationally hold an investment that is clearly losing them money for an indefinite amount of time, even though they can sell and buy something else at any given point in time. While I’m guessing the intention was to allow the researchers to compare alternative choices, this is not a rational approach to maximizing gains in a semi-random context like the stock market.

In Trade Your Way to Financial Freedom by Van Tharp, legendary trader Tom Basso of Trendstat describes how this works:

Tom was explaining that the most important part of his system was exits and his position sizing algorithms. As a result, one audience member remarked, “From what you are saying it sounds like you could make money consistently with a random entry as long as you have good exits and size your positions intelligently”. Tom responded that he probably could. He promptly returned to his office and tested his own system of exits and position sizing with a “coin flip”-type entry….Tom’s results showed that he made money consistently, even using $100 per contract for slippage and commissions. We subsequently duplicated those results with more markets.

Van Tharp even goes further, sardonically claiming that entry based on something completely unrelated to trading, such as phases of the moon or dreams, can be profitable, as long as both position sizing and exit strategies are very good. While this may not necessarily be published academic work, the hypothesis testing was probably rigorous.

In my opinion, position sizing and exiting is the metaphorical line in the sand, i.e. where you move from “analysis” to “trading”. Analysts may have really deep understand of a particular company, but this doesn’t mean they will know exactly how to the most money from it. This depends on having a specific approach to buying and selling, to market timing and position sizing, and to having the sense to execute well independently of the security’ fluctuations.

Is Fama a modern-day Thomas Malthus?

Thomas Malthus was one of the more colorful personalities in the history of economic thought. In his most famous work An Essay on the Principle of Population, Malthus came to the terrifying conclusion in 1798 that the world’s farming land mass is fixed, but that population was growing exponentially. According to Malthus, this would result in massive famine, wars, and strife.Thomas_Malthus

Fortunately for all of us, he was dead wrong. He made an assumption about the state of technology. This would have only happened, if farming technology did not evolve at all. Instead, the rapid advancements in mechanization, fertilizers, and the techniques employed by agribusiness today created a situation that most countries produce a surplus of food. The US, for example, produces roughly 3x what it needs, with the remainder being exported.

Technology has caused similar “tectonic” shifts in financial markets as well. In the 19th century, the Rothschild family built their wealth based on the fact, that they used pigeons to carry information about market sensitive information around Europe. Rothschild famously profited in London, when he heard that Napoleon was defeated at Waterloo before other market participants. In the early days of Wall Street, savvy traders used the telegraph and later the telephone to learn about the mispricing of particular cross listings of stocks on other exchanges, in order to pocket arbitrage profits. Today, embedding software in chips like FPGAs and GPUs allows certain traders to beat their competition by being able to react 100x faster, and algorithmic traders are increasingly approaching the speed of light.

While assuming technology is fixed may be convenient theoretically in order to understand market dynamics, Fama and EMH proponents are losing touch with how markets work. As a result, their findings are only relevant in a theoretical context which is functionally different from everyday trading realities.

Parting Thoughts

“There is an old joke, widely told among economists, about an economist strolling down the street with a companion when they come upon a $100 bill lying on the ground. As the companion reaches down to pick it up, the economist says ‘Don’t bother — if it were a real $100 bill, someone would have already picked it up’.” —Lo and MacKinlay

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