Efficient Market Hypothesis – News of it’s death might be premature

I’ve been reading countless attacks on the efficient market hypothesis, CAPM, and all the related derivativations that have come out of the ideas of rational decision makers and optimal pricing. The attacks vary, but seem to center on the current crisis as proof that mispricings occur and that the markets are in fact not efficient. Academia seems to have room now for the next model that will surely explain the previous bubbles, but in time, will also come under attack. Surprisingly, I want to offer a little defense of the tools that have come out of EMH…

As a portfolio manager, and specifically, a value-oriented portfolio manager, let me start by highlighting that I do not believe the markets are efficient. I believe there are opportunities to outperform. I believe that a lot of investors depended too heavily on EMH and got caught up in the theory.

That disclaimer aside, EMH gives investors a framework. Should we depend on it? Definitely not. But EMH gives us the language to discuss averages and some big picture ideas. For example, EMH would tell us that we should expect roughly 50% of the managers to outperform and 50% to underperform in any given time-period (leaving out some nuances of transaction costs and taxes – big nuances, for sure). Managers who now criticize EMH would like the public to believe that we live in Lake Woebegone, where all the children are smarter than average and all the money managers will be better than average. Simple math and logic should show us the fault in that logic.

In a survey of money managers, 85% believed that they were better than average. Let’s look at that statistic a bit more closely. Of the 85%, some will be right and some will be wrong. Of those that are right, some will be able to beat the average on purpose, and some will be able to beat the average by luck. Of the 85%, some will be wrong. We can assume that none will be wrong on purpose. There are also the managers in the 15% who do not believe that they will outperform the average. Some will be right. Some will be wrong, and indeed, perhaps because they know how math works, a higher proportion of them will be able to beat the average that the managers in the 85%. Now we’re really confusing ourselves.

The key question for investors then, is not whether the EMH is right or wrong, it is just a tool. The key question is whether an individual investor can predict which manager will outperform. If an investor believes that they have no predicitive ability, which, let’s face it, most people don’t, then investing in an ETF and subscribing to the EMH is probably a pretty reasonable option. If, however, there are process-oriented factors that grant some money managers a higher probability of outperforming, then investing in that manager can provide a higher expected return.

Some simple ways to outperform – yes, they exist. Let’s say your broker or financial advisor tells you to have a certain portion in stocks (already, this percentage probably came out of some tool based on Monte Carlo simulations and a direct descendent of EMH). Your broker then says to invest in an S&P 500 ETF. There are very simple ways to outperform the S&P 500:

1. Invest in an equal weighted weighted index rather than a cap weighted index.
2. Invest only in the “value” portion of the index, excluding “growth” stocks.
3. Invest in a small cap index instead.

Now your financial advisor or broker probably told you to put some in large cap, some in small cap, some in value, some in growth. In essence, you probably just replicated the market portfolio, and then you should just use a broad based ETF. Instead, investors need to use the tools and research that came out of the EMH, while recognizing their limitations, to make more informed investment decisions.

Asset Allocation, or Why Your Advisor is Failing You

Earlier this week, we posted a piece by James Montier on the Efficient Market Theory (EMT) and where it has led us astray. Let us now go deeper into the implications of EMT for financial advisors and clients.

            With EMT as our backbone, the advisory industry has been able to sell seemingly scientific – and certainly mathematical – approaches to asset allocation. Clients often fill out questionnaires or sit with advisors, discussing investment horizon, risk tolerance, liquidity needs, etc. Then the advisor goes into the laboratory and plugs in some characteristics into an off-the-shelf software or a home grown asset allocation model and comes out with an efficient frontier. Most programs also come out with charts, statistics, and qualifiers, such as “an 80% probability of achieving between $XX assets and $YY assets in 20 years”. In fact, here is one software packages description with the name omitted:

SampleAllocationModel is a state-of-the-art asset allocation and portfolio optimization software. It provides an investor with advanced tools to successfully tackle major problems of quantitative portfolio management: parameter uncertainty, nonnormality of returns and uncertainty in investor’s preferences. The analytical methods adopted include the Black-Litterman model, several Shrinkage Estimates, Robust Optimization, Walk-Forward Optimization, Target Shortfall Probability Minimization, and many others. At the same time, SampleAllocationModel is the only professional product in the market, affordable to individuals. It combines highly advanced and innovative analytics with a user-friendly, intuitive interface, perfectly suited to any level of expertise and experience.

It sounds incredibly impressive, and based on the EMT, this kind of product would certainly lead investors down the path of diversification between different asset classes along the efficient frontier. The implications of the EMT are not limited to individual investors and advisors. Large pension firms use the same methodology to achieve their efficient frontier and allocation. They use state of the art consulting firm to help them categorize, diversify, and hedge different risks. Just as importantly, the advisors love to use these models because it transfers accountability to “the market”, to “the long term”, to “anyone but me”. No advisor wants to leave out an asset class (citing diversification, but feeling like the asset might go up). In the end, however, Keynes was right when he stated, “It is better to fail conventionally than to succeed unconventionally,” and the EMT gave advisors the intellectual framework to fail conventionally.

The intellectual framework of the EMT rested three main elements: defining return as some “average return” over a long period, defining risk as volatility, and using historical correlations between asset classes. Let us start by critically examining these foundations:

            Every advisor warns clients that “historical returns are not indicative of future returns”. Yet, the models advisors utilize predict future returns based on historical returns. For most advisors, that actually seems appropriate, alongside their recommendations to invest in last years star mutual fund. Models rarely take into account forward looking return projections based on fundamentals. In statistics there is a saying to draw attention to the dangers of averages: if your head is in the oven and your feet are in a bucket of ice, on average, you’ll be fine. The reality is far from it. Using historical returns fails to consider limitations in the data, the disparity of returns, and factors influencing returns.

That’s where risk is supposed to come in. Risk under the EMT focuses on distribution. Assuming that returns are normally distributed (a false assumption), risk measures the standard deviations based on historical volatility (again, a false methodology). Risk should help clients and advisors minimize the chances of permanent loss of capital. It should help clients recognize that risk is often NOT rewarded. In fact, under the EMT, the more risk the better, just increase your investment horizon. The number of errors in these assumptions has been widely discussed, yet the asset allocation models used by advisors and consultants continue to look at volatility and risk in the same light.

            Lastly, we have correlation. Again, using historical correlations as stable (a false assumption), the EMT leads us to seek historically uncorrelated assets. In and of itself that’s fine, except that historical correlations fail to take into account the changing nature of correlation itself. This often happens just when you need diversification the most, such as in a down market when correlations often increase.

So where does that leave us? For starters, let’s recognize that the path we grew up on led us in the wrong direction. With this recognition comes the need for new tools. Asset allocation must move away from the “frontier” with an upward sloping trajectory (the more risk, the more return). Instead, valuation and price, confidence in NOT having exposure to overpriced assets, risk assessment based on permanent loss of capital and not on volatility, and a willingness to be critical and take a stand apart should drive our models and client interactions.

Montier “…how EMH has damaged our industry” (reprinted with permission)

In this excellent piece from last week, James Montier highlights some flaws in the efficient market hypothesis. More importantly, he outlines the some of the damage – that may take years to repair – caused by the ensuing mentality in the investment community. Beta and alpha debates should move over already. Risk is not volatility. This is a beginning of a trend that I’m seeing of late. The intellectual framework is actually shifting. Consulting firms to big pension funds are reviewing the idea of style boxes. Stagnant asset allocation is being reworked, with emphasis on higher allocations to undervalued assets. Benchmarking is changing. Indexing itself is changing. This piece is a good starting point.

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