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MPT-A Tool, Not An Answer

Financial Advisor

By Scott A. MacKillop | March 30, 2012

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To build good portfolios you need the right tools and you must use them correctly.

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In 1952, The Journal of Finance published an article by 24-year-old Harry Markowitz that discussed a method for balancing risk and return in the construction of diversified portfolios. For years, financial advisors used Markowitz’s modern portfolio theory to build diversified portfolios for their clients. They were pretty happy with the results. Then came 2008.

To say that diversified portfolios didn’t perform well during the market meltdown of 2008 is an understatement. Most asset classes declined significantly in value during this period, dragging diversified portfolios right along with them. As a result, many advisors pronounced the death of the theory and called for its unceremonious burial.

But word of the theory’s death is premature. No one enjoyed the experience of 2008, but Markowitz’s theory was not to blame for our suffering. He never suggested that it would save us from a widespread market decline. Those that relied on it to do so did not understand it.

Modern portfolio theory is a tool, not an answer. It offers a recipe for building diversified portfolios based on assumptions about what will happen in the future. But it does not tell us very much about how to develop those assumptions, and it certainly does not guarantee that the portfolios we build will be immune to market declines. In fact, Markowitz tells us we cannot diversify away all risk.

Like most tools, it is only helpful if used properly. Unfortunately, it is often implemented in ways that blunt its usefulness, ways that were not prescribed or encouraged by Markowitz. These methods simply emerged as practitioners struggled to address issues that he did not address in his paper.

So let’s take a look at how the tool works and, more important, let’s explore some ways that it might be implemented to get better results. No matter how it is used, the theory cannot immunize our portfolios from declines in value. But by improving the way it is used, we can improve the likelihood that our clients will reach their long-term goals.

In the Doors song “Roadhouse Blues,” Jim Morrison sings, “The future’s uncertain and the end is always near.” This idea underlies modern portfolio theory. Markowitz assumes we will build diversified portfolios because there is no reliable way-at least in the short term-to predict the performance of each asset class. He suggests that even if we could, we would still prefer a diversified portfolio because we couldn’t stand the volatility associated with investing in a single asset class.

Next, Markowitz assumes that when we build diversified portfolios we will already know what assets we are going to use. He offers no guidance for what those ought to be other than to say that you can use either individual securities or what he calls “aggregates”-what we would call asset classes. He leaves open the question of what should go into the mix.

Many advisors today do not use a sufficient number of asset classes in their portfolios. This is understandable. Becoming familiar with new asset classes requires research, and new products emerge every day. Sorting them out requires effort, but that effort is worthwhile.

For example, the collapse in 2008 was widespread, but it was not universal. There were a few bright spots. Managed futures had strong positive returns. They would not have saved a well-diversified portfolio from losses that year, but they would have cushioned the blow.

“Thin-slicing” traditional asset classes into their component parts can also help. For example, long-term U.S. Treasury securities are often lumped into a more general domestic fixed-income category. But they are more negatively correlated with U.S. equities than the fixed-income asset class as a whole. Investors who had separated them in both 2008 and 2011 would have seen better results.

Markowitz also assumes that we will bring with us a set of expectations about the future returns, variances and covariances of the assets classes we use in our portfolios. He doesn’t tell us how to develop these, although he says we might use historical data as a starting place. He goes on to say that “better methods can be found.” He was right about that.

This is another area where the practices adopted by advisors have caused modern portfolio theory to fall short of its full potential. Most investors have never developed a solid process for reasonably anticipating future returns, risk and correlations. Instead, they have defaulted to the use of long-term historic averages. These averages often mask reality rather than reveal it.

If you have read Jeremy Siegel’s book, Stocks for the Long Run, you know that he went back to the early 1800s and determined that the long-term real rate of returns for stocks was about 7%. You also know that, year to year, the return of the stock market is almost never 7% or anything close to that. Even if you look at 10-year returns for stocks, their return is rarely close to 7%.

Long-term historic averages also don’t help investors anticipate volatility, like that seen in 2011. Volatility changes over time, just like returns do.

Correlations also change over time, and in a more treacherous way. Asset classes that appear relatively uncorrelated day to day become more highly correlated just when you don’t want them to-when markets are in a free fall. Long-term historic averages do not reveal those relationships.

A better way to approach correlations is to look at them during the times that matter most-during periods when the markets are moving strongly in one direction or the other. By disregarding the periods when the markets are just bumping around, you eliminate much of the noise from long-term historical averages.

Once you develop a framework for establishing return, risk and correlation expectations that are truly forward-looking, your portfolio allocations will change over time to reflect your changing expectations about the future. If you have no framework, buying and holding will suffice, though it is not the best approach.

I am not advocating market timing here, which is worse than buying and holding. But there are sound ways to develop long-term expectations about the various asset classes. Most are valuation-based. Some involve macroeconomic overlays. Don’t confuse these with market-timing schemes, which should be avoided at all costs. The hall of fame for market timers is an empty room.

Modern portfolio theory has also disappointed practitioners who pick the wrong managers. The standard practice is to develop an asset allocation strategy with indexes for each asset class, and then pick “best-of-breed” managers for each slice of the asset allocation pie.

How do we select these superstar managers? Often it is done by categorizing each one in a style box and then assessing his or her skill relative to a single index. When managers commit the sin of “style drift,” they are shown the door and the next victim fills the vacated pie slice.

It’s no wonder investors can’t find consistent managers. You can’t find them using these tools.

As it turns out, good managers don’t pay much attention to style boxes, style drift or benchmarks. Why would they? Their job is to pursue opportunity wherever they find it. Of course, some managers pay attention to style drift-because they have learned they will be punished if they stray from their mandate. This may be excellent business-building practice, but it is not good investment practice.

Professor Russ Wermers from the University of Maryland looked at the style drift issue and found that most active mutual fund managers pay little attention to it. He also found that manager skill is not limited to one style box. In fact, managers who drifted more actually had better performance. A skilled manager can find good stocks in any style box.

A similar problem exists when it comes to using single index benchmarks for measuring manager skill. If managers don’t pay any attention to style boxes and the best managers seem to be associated with high levels of style drift, then why do we think that comparing managers to a single index will tell us very much about how skilled they are?

Professors Martijn Cremers and Antti Petajisto from the Yale School of Management found that the more a manager’s holdings departed from a single index benchmark, the more likely the manager was to outperform the index. This is not surprising. Benchmarks are arbitrary collections of securities that do not tell us anything about where opportunity exists.

Punishing managers for style drift is silly for another reason. The logic behind it is that style drift disturbs the asset allocation strategies that we have crafted. But if we acknowledge, as we must, that the inputs we use to create those strategies are never exactly on target, then we must also acknowledge that demanding from managers a slavish adherence to our asset allocation strategies is an exercise in form over substance.

Skill does exist in investment management, just as it exists in every other human endeavor. But it is relatively rare. Identifying it before it is demonstrated is not easy. And it is very hard to distinguish from luck in many cases. But it can be done.

We use returns-based style analysis to create custom benchmarks for each manager we evaluate. It was developed independently by both Bill Sharpe and Gary Miller, the founder and CIO of our firm. There are other tools as well. Style boxes and single-index benchmarks are not among them.

How you combine managers in a portfolio is at least as important as finding good managers in the first place. The legendary football coach Knute Rockne said: “The secret is to work less as individuals and more as a team. As a coach, I play not my 11 best, but my best 11.” This is how we should approach building portfolios.

Likewise, most advisors think building portfolios means bringing together a collection of star performers rather than building a team. This is not a good idea. On any given day, if you pick a group of best-of-breed equity managers to fill out your asset allocation pie, they are likely to have similar characteristics. When these traits cycle out of favor, your managers are likely to underperform together.

At the conceptual level, the answer to this problem is simple. You have to consider how managers may perform together in the future when you put them together in a portfolio. On a practical level, this is easier said than done.

We have developed a computer program that can consider literally millions of possible combinations of managers until it finds the one we think will be the best in the future. In essence, it is a super-duper manager blender that helps us develop the best team, not the best collection of managers. Even if you do not have a tool like ours to work with, you should give serious thought to how the managers you combine in portfolios will complement one another and work together as a team.

Modern portfolio theory is far from dead, but we must recognize that it is a tool, not an answer. If we want the tool to give us good answers, we must continue to improve our inputs and the way we use the information the theory gives us.

Scott A. MacKillop is the president of Frontier Asset Management, a firm that constructs and manages portfolios for financial advisors and their clients. He is a 36-year veteran of the financial services industry.