This year marks the 50th anniversary of Modern Portfolio Theory (MPT). The seminal work of Dr. Harry Markowitz on efficient portfolio construction was first published in 1952. This work, coupled with that of Graham and Dodd, separated the world of economics from that of finance and formed the foundation for investment decision making as we know it today. Let's examine what we've learned over the past half century, with an eye toward using this knowledge to make better investment decisions Ð to investing to win. MPT explains quite clearly that there are risk-return tradeoffs in the market. A few of these tradeoffs are efficient in that they provide the highest expected return for a given level of risk. Almost all individual securities and most combinations, or portfolios, of securities are inefficient. Efficient portfolios are expected to deliver superior risk-adjusted returns over time. Patience is not its own reward; creating efficient portfolios is. MPT further advises against putting all of your eggs in one basket because a well-diversified portfolio reduces risk better than stock picking. Good solid basic stuff. Over the past 50 years, we've learned many important lessons, most of which derive from these basic tenets.

Lessons Learned

One of these lessons is that investment policy, or asset allocation, is by far the most important determinant of investment results. In other words, determining the amount allocated among stocks, bonds, real estate, etc. is undoubtedly the most important decision an investor makes, and it's an unavoidable decision. MPT gives us a framework for making this decision. All one needs to know is how to measure risk and return and how to choose the appropriate risk-return tradeoff. Due to the limits of computer technology 50 years ago, Markowitz proposed volatility as a measure of risk, instead of the more difficult calculation of downside risk. But investment risk is not the same as volatility, as commonly used to construct the efficient frontier. Risk is failure to accomplish an investment goal, e.g., to keep what you've got, or to meet a future obligation. Volatility overstates risk because it assumes that high returns are just as risky as low returns. In addition, capital markets are not all that efficient, due in part to investor behavior, which was supposed to keep the markets efficient, but instead messes them up.

Another lesson we've learned is that active managers rarely earn their fees, especially after taxes, and that the majority of investors chase the infamous Òhot dot,Ó resulting in even worse performance. Studies have shown that the average investor in a typical mutual fund earns less than that mutual fund earns over time, because the investor switches in and out at precisely the wrong times. Further exacerbating this problem, the average mutual fund typically underperforms an appropriate passively managedÑand cheaper--alternative.

Let's examine how these lessons of the past half century have improved investment practices. First, it took about 20 years for the world to recognize and accept Harry's breakthrough, so not much happened for awhile. Then the next 15 years brought a flurry of innovations, and gave rise to the investment consulting profession. This brings us through to the end of the 1980's. Not much has happened in the ensuing 15 years. Much of what consultants deliver today is essentially the same as it was 15 years ago. Advice and guidance have not evolved much. Importantly, the lessons of the recent past have not made their way into contemporary investment portfolios.

How to Identify Skill

Similarly, investors can improve the odds of actually finding investment manager talent. Do managers have skill? Do you know who these skillful managers are? Are consultants personally invested with these managers? We've recently discovered that investment style is an important determinant of performance, ranking second only to investment policy, and that skill within a style tends to persist. Good growth equity managers continue to be good growth equity managers. Ditto for value. Unfortunately, we routinely confuse style with skill. Witness the mass firings of value managers just two short years ago.

We've also learned that value and growth go in and out of favor, so you can try to call the style turns, or avoid making the wrong call by maintaining style neutrality. Whichever choice you make, you'll want to employ managers with skill or, if you can't find skill, invest passively. The search for skill is enhanced by a new technology that first separates out style effects and then identifies the sources of the value added above style, otherwise known as performance attribution. In contrast to the attribution analyses developed 15 years ago and still widely used today, which promote the mistake of confusing style with skill, the new contemporary technology actually helps identify investment manager talent.

Once you've discovered talent, you need to allocate among these skillful managers in a manner that avoids making unintended style or sector bets. You've got to diversify while simultaneously capitalizing on the collective skills of the team you've assembled. This is key to success, to winning.

How to identify skill

We want to allocate among skillful managers to achieve the greatest upside potential above our MAR relative to the downside risk of falling below our MAR. First we want to find managers who have demonstrated an ability to beat their style-customized benchmarks on a risk-adjusted basis, as described in the previous section. Then we estimate how often each manager might be above our MAR and how far above. Table 1 demonstrates how this is done.

Fund Name	Lg Val	LT Gov	Inter Gov	R-Squared	U-P ratio	Ω-excess
Vanguard Windsor II	92	8	0	0.86	1.67	-3.00%
T Rowe Price Equity Inc	90	5	5	0.90	1.65	3.00%

Style analysis reveals Vanguard Windsor II behaves like a portfolio made up of 92% large value index and 8% long term bonds. So we construct a style benchmark with those percentages to measure the upside potential and downside risk for that fund. The upside potential ratio (U-P ratio) is 1.67, which means that this fund has 67% more upside potential than downside risk. Similarly, a benchmark of 90% large value, 5% long term bonds and 5% intermediate term bonds is created for T Rowe Price Equity Income fund. The T Rowe Price fund has about the same upside potential as the Vanguard fund (1.65 vs. 1.67) because they have very similar styles. The difference is that T Rowe Price Equity Income earned 3% more on average than it's style benchmark while Vanguard earned 3% less than its style benchmark. T Rowe has evidenced more skill. This risk-adjusted return above the style-customized benchmark is called an ÒOmega-excess returnÓ. This process is repeated for all mutual funds (or active managers) under consideration.

The second step solves for that combination of active managers and passive indexes that maximizes the overall portfolio's Omega excess return, while preserving the desired style profile, which is normally style neutral. This is accomplished with quantitative methods designed for this purpose that are mathematically sound. This is not a mystical procedure to guarantee success. It is a professional approach for managing uncertainty with respect to specific financial goals.

How to identify skill

If we use what we've learned over the past 50 years, with special attention to the recent lessons, we can succeed in investing. We can invest to win. The prescription is actually quite simple, and is summarized in the 2 pictures below:

1. Find talent by identifying those who appear to be winners in their style of management, and by confirming that the reasons for winning are consistent with the manager's people, process and philosophy. The first step finds the winners. The second step, confirmation of consistency, is the window to future success.

   

2. Allocate to that talent to maximize the probability of achieving objectives while minimizing the likelihood of regret.

   

These are not new approaches in concept, but they are certainly underutilized in practice. Perhaps these ideas are on the same 20-year slow track that Modern Portfolio Theory experienced. If so, this article is about 5 years before its time. Stay tuned. You may be hearing more about Modern Portfolio Technology.