Dumb Alpha: The Ignoramus’s Guide to Asset Allocation
Modern finance constantly busies itself with the development of new, more sophisticated ways to manage risk and generate returns. These efforts, however, generate their own risks — for example, overspecifying a model or falling prey to data mining. On the opposite end of the spectrum are simple ways to invest that have a proven track record of providing superior investment outcomes. This article focuses on investment techniques that are so simple it is surprising how well they work, a phenomenon that Brett Arends of MarketWatch has called “dumb alpha.”
The Dumb-Smart Way to Think about the Future
Assume you are a middle-aged man with a receding hairline and an expanding waistline. In short, you don’t look like George Clooney — you look like me. Moreover, you need to finance your retirement with your savings. Creating a portfolio to build retirement wealth is no easy feat given the fact that retirement may be 20 to 40 years in the future. A lot can happen in that time: 30 years ago, Japan was on its way to overtaking the United States, China was a closed-up Communist country, Europe and North America had broken the spell of runaway inflation, and Brazil was a basket case. Who can say what the next 30 years will bring?
Luckily, you are well aware that it is nigh impossible to predict which investments will do well during the next three decades. And assuming this is true, there are only two logical ways to invest.
One possibility is to hold all your savings in cash or the safest short-term bills and bonds. The problem with this approach is that you will have a hard time keeping pace with inflation once taxes and other expenses are taken into account. And in some countries, like Germany and Switzerland, you even face what my colleague Sloane Ortel calls “unterest rates.”
The other possibility is to invest the same amount of your money in every asset class. This makes sense because you don’t know how stocks will do compared with bonds or real estate investments, or how Apple stock will do compared with Barry Callebaut. The simplest example of this naive equal-weighted approach would be a portfolio split 50/50 between stocks and bonds. Another approach would be to invest one-quarter of your assets in cash, one-quarter in bonds, one-quarter in equities, and one-quarter in precious metals. Similarly, instead of investing in a common stock index such as the cap-weighted S&P 500 Index, you could evenly spread your precious funds across all 500 stocks of the index.
The Advantages of a Naive Asset Allocation
As it turns out, this way of investing tends to work extremely well in practice. In their 2009 article “Optimal versus Naive Diversification: How Inefficient Is the 1/N Portfolio Strategy?,” Victor DeMiguel, Lorenzo Garappi, and Raman Uppal tested this naive asset allocation technique in 14 different cases across seven different asset classes and found that it consistently outperformed the traditional mean–variance optimization technique. None of the more sophisticated asset allocation techniques they used, including minimum-variance portfolios and Bayesian estimators, could systematically outperform naive diversification in terms of returns, risk-adjusted returns, or drawdown risks.
Unfortunately, naive asset allocation does not work all the time. Over the last several years, only one asset class generated high returns: stocks. So, a naive asset allocation will not keep up with the more equity-concentrated portfolios during such periods. But it is interesting to note how well a naive approach works over an entire business cycle.
Practitioners should compare their portfolios with a naive asset allocation to check whether they really have a portfolio that delivers more than an equal-weighted portfolio. You can create a better (“more sophisticated”) portfolio than the equal-weighted (“dumb”) one, but it is surprisingly hard to do. As a check, you can create an equal-weighted portfolio from the assets or asset classes used in your current portfolio. Then test whether the current portfolio is superior to this equal-weighted benchmark over time in terms of returns, risks, and risk-adjusted returns. If that is the case, congratulations: You have a good portfolio. If not, you should think of ways to improve the performance of your existing portfolio.
It is also pretty clear why this dumb alpha works. Within stock markets, putting the same amount of money in every stock systematically prefers value and small-cap stocks over growth and large-cap stocks. These two effects conspire to create outperformance.
There is a second effect at play, however. After all, the value and small-cap effect cannot explain why a naive asset allocation also works in a multi-asset-class portfolio. The key reason for its strong showing is its robustness to forecasting errors. Most asset allocation models, like mean–variance optimization, are very sensitive to prediction errors. Unfortunately, even financial experts are terrible at forecasting, and one follows forecasts at one’s peril. By explicitly assuming that you cannot predict future returns at all, an equal-weighted asset allocation is well suited for unexpected surprises in asset class returns — both positive and negative.
Since unexpected events happen time and again in financial markets, in the long run an equal-weighted asset allocation tends to catch up with more “sophisticated” asset allocation models whenever an event happens that the latter are unable to reflect. In other words, if the naive asset allocation outperforms a more sophisticated portfolio, it might provide a hint as to why this is the case. Are there too many risky assets in the sophisticated portfolio that directly or indirectly create increased stock market exposure? What are the implicit or explicit assumptions that led to the more sophisticated portfolio that have not materialized and have led to an underperformance relative to a less sophisticated naive asset allocation? In this sense, the naive asset allocation can act as a check to an existing sophisticated portfolio and as a risk management tool.
For more from Joachim Klement, CFA, don’t miss Risk Profiling and Tolerance: Insights for the Private Wealth Manager, from the CFA Institute Research Foundation, and sign up for his regular commentary at Klement on Investing.
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All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer.
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This idea has a lot of merit, and stands well assuming the size of the investment to be allocated is sizeable (perhaps $10 m +). For anything smaller, it pays more to avoid it: rather pick and hold specific companies in different industries, in the asset class better suited to those companies. Think NiPiLo (Nit Picking for the Long Term).
Why?
NiPiLo is not readily/widely replicable. Any latest proven market beating, shotgun effect (think “diversification”) strategies, if successful, are replicated and cease to be outperforming.
It is the only legal way to hold to information asymmetry to one´s advantage (one takes the time and effort to dig deep into the fundamentals of non public entities, gets a piece of the action, and holds on).
It does not ignore wider market fundamentals, yet drills down to a level that goes undetected by the bigger investors and investment managers with loads of money to invest, but not enough resources to cover small capital hungry entities.
Of course, this is not meant to replicate the Penny Stocks strategies of the ´80s and beyond, but a sound back-to-basics approach for smaller sized investment portfolios.
This article sort of fails to address the ‘elephant in the room’ question which is that of passive vs active management difference. Even within the equal-weighted portfolio (EWP) can an active strategy help? Or is the EWP founded upon passive indices?
I believe equal weighting should work just fine regardless of portfolio size. Certainly every approach goes in and out of style, and there are always new entrants to investing that experiment (and many that simply pick a reasonable allocation and leave it alone.) I use what you might call a variant of this approach, with equal weighted risk classes, plus a base of intermediate gov’t bonds. Over the past 40 years, this strategy has beaten the S&P by a significant margin, and has been slightly less volatile than a US 60/40 portfolio (and far less volatile than the S&P). Best of both worlds. Performance may be worse going forward, as ‘smart beta’ approaches may eat into some of this extra return, but it seems very likely to generate at least average returns at below average volatility going forward.