Since 2008, you can't have an investment-related conversation without somebody saying that Modern Portfolio Theory (MPT) is outmoded, old-school or irrelevant in this New Age of investing. But usually that's about as far as the conversation goes. Advisors are paying more attention to the news, and to potential downside risk, and they're secretly hoping that some insight will help them steer their clients clear of the next major market downturn.
If we are indeed moving into a Post-MPT New Age of investing, then we're going to need something more substantial than better intuition and a closer read of the Wall Street Journal. Over the past four years, I've been collecting the most tangible, concrete post-MPT insights offered by professional investors – those that improve on the standard model.
Below are the five best New Age investing ideas I've heard so far:
Replace static risk and correlation measurements with dynamic ones
Jerry Miccolis, chief investment officer of Brinton Eaton in Madison, N.J., has an unusual background in our business: he was a Towers Perrin corporate consultant for 25 years and wrote a book on how corporations manage the business risk of their "portfolios" of products or subsidiaries: Enterprise Risk Management: Trends and Emerging Practices.
Enterprise Risk Management (ERM) is actually an outgrowth of modern portfolio theory, adapted and refined over the past half-century to fit the myriad management challenges of the business world. So when Miccolis switched careers to join an investment management firm, he was astonished to discover that MPT had not gone through a similar decades-long evolution in precision and sophistication. In particular, he found it odd that advisors would assign a single standard deviation number to each investment or asset class.
"Nobody in the corporate world would measure risk as a single static measure in a dynamic marketplace," Miccolis said. "In the corporate world, there is broad understanding that the degree of risk, and the nature of the risks, change as the marketplace changes."
Corporate managers and consultants monitor this ebb and flow of their business lines' volatility using GARCH models. The acronym stands for 'generalized auto-regressive conditional heteroscedasticity,' where you constantly sample the volatility of each individual component of the overall enterprise, and, at the same time, sample the rates of change to see how each is trending. The more sophisticated models will draw tentative conclusions about future risks. In either case, as a matter of managerial routine, business executives will compare those risks to the degree of risk they're willing to take on behalf of their shareholders. Whenever risk exceeds stomach for risk, they look for ways to take chips off the table.
In the investment world, Miccolis was surprised to learn, a comparable activity is regarded as heresy and market timing. The assumption is that you can't monitor changes in risk in the investment markets, but he believes this isn't true.
"We are learning that when market volatility rises, it tends to stay high – what some call volatility clustering," he said. If an advisor sees a rise in the VIX index after a period of relative calm, he might reduce allocations to risk assets.
The same reasoning can be applied to the other inputs in an MPT optimizer. Miccolis was surprised to learn that advisors measure the correlation of price movements between different assets (or asset classes) with a single number. A corporate manager with ERM training is naturally curious about how the correlations between different divisions or product lines will change over time, and what market conditions have, in the past, caused which kinds of changes – which Miccolis views as a perfectly natural thing to spend time understanding.
The 2008 meltdown, and the tech wreck before that, and virtually every other significant market decline have all shown that this "single-number approach" is not inclusively explanatory under all circumstances. In fact, the sudden unexpected rise in correlations as every risk asset plunges down the toilet is probably the biggest reason so many advisors are questioning MPT today.
ERM practitioners model correlations using structural models called copulas. "In non-mathematical language," Miccolis explained, "a copula is a way to capture the entirety of the relationship between two asset classes, during periods of market stress, and a variety of other conditions." To use a simplified example, we know that when equities are in a normal range of behavior, commodities don't move in lockstep with them. But when equities are plunging, we find a much closer relationship. This fluctuating relationship can be graphed, so you can see when the two are highly correlated and when the commodities are providing diversification benefits.
The output can take various forms; one is a scatterplot that shows that, in the past, when equities are in a range of delivering an annual return of 0% to 15%, commodities may be returning in the same range, following a very different return pattern. When equities are in the -20% range, you see commodities and equities moving together in the same direction.
A more complicated New Age Investment model would look not just at current returns and trends, but things that impact both investment categories, like global GDP growth, interest rates and inflation. Miccolis said that when you're attributing behavior to underlying economic conditions, the relationships among asset classes become easier to understand.
Interestingly, since Miccolis came out with his ERM improvements to MPT, a new software product has hit the advisory market which measures the historical, fluctuating correlations between a broad variety of different economic factors and virtually any investment you might include in a client portfolio. The program can even model real-time changes in correlations and the potential impact on client portfolios, and suggest less-risky (or less susceptible to current conditions) alternatives. MacroRisk Analytics , created by a team of widely-published economics professors, looks like the planning profession's answer to Miccolis' New Age Investing proposals.
Anchor dynamic asset allocation to a fixed risk posture
At a recent FPA "Experience" conference, Pinnacle Advisory Group, the Columbia, MD-based planning firm with roughly $1 billion under management, hosted a cocktail reception for conference attendees. How often do you see an advisory firm buying drinks for the other advisors at a national meeting?
Pinnacle was touting its outsource investment management services, and the company's chief investment officer, Ken Solow, was explaining his firm's unique brand of tactical asset allocation to advisors who were mostly in the "rely-on-intuition-and-read-the- Wall-Street-Journal -more-closely" camp. I had the impression that most of them walked away with a drink in their hand and no idea whatsoever what he described.
Solow's version of New Age investing starts with five model portfolios whose benchmarks are so uncomplicated that your average grade school student could understand them. At the lowest end of the volatility spectrum, the Dynamic Conservative portfolio is benchmarked against a mix of 20% S&P 500 index, 80% Barclay's Global Bonds index. From there, you move up to Dynamic Conservative Growth (45/55), Dynamic Moderate Growth (60/40), Dynamic Appreciation (75/25) and Dynamic Ultra-Appreciation (100% equity).
Around these core strategic models, the firm practices tactical asset allocation in three dimensions. Pinnacle can move in and out of different industry sectors in what appears to be a classic sector rotation methodology, looking at changes in real wages, credit conditions, home sales and jobless claims, manufacturing indices, money supply, TIPS spreads, the yield curve and currency movements and mortgage delinquency rates. The company also looks for market trends using a variety of moving averages and comparisons of macroeconomic drivers. Finally, the investment team looks at valuations compared with historical averages.
However, instead of being tactical around the asset classes – moving from a 60/40 to a 50/50 or 70/30 mix depending on market conditions – Pinnacle focuses on managing the volatility of the portfolio against its benchmarks. Thus, the Dynamic Moderate Growth portfolio, regardless of the actual investments that the management team ultimately assigns to it, must never exceed the volatility of a 60/40 mix of the indices. The Dynamic Appreciation portfolio can stray from the 75/25 asset mix in many directions, but it must not stray from the benchmark's beta.
The Pinnacle team measures how well they meet this constraint in a variety of ways. In the simplest test, the portfolio's beta is compared over the past year, rolling forward each week, with the benchmark's beta. Another test looks at the contents of each portfolio today, and calculates what the beta would have been had the portfolio owned that exact mix of assets over the previous 12 months. Pinnacle also measures the r-squared of the portfolio against the benchmark.
Similar information is taken over rolling 36-month periods since inception, providing a longer-term look at whether the volatility constraints are working. Finally, an automatically-generated chart compares each Pinnacle portfolio's average and maximum peak-to-trough bear market declines with the benchmarks.
Most top-down dynamic asset allocation decisions represent a bet that some specific thing will or will not happen. The bet is made by the advisor but its consequences are borne by the client. This creates business risk (when the portfolio return deviates from benchmarks on the downside) and adds return risk that the clients may not have realized they were assuming.
Imposing a volatility constraint on the portfolios allows the Pinnacle investment team a broad flexibility to invest according to their convictions in assets and asset classes that might be very different from the benchmarks, in very different percentage allocations, and still not subject themselves and their investors to a greater degree of risk.
Diversify by risk factors rather than asset classes
Mark Taborsky, formerly of the Harvard and Stanford endowments, also former manager of PIMCO's Global Multi-Asset Opportunity fund and Global Multi-Asset funds, now managing director at BlackRock, believes that the typical reliance on asset class correlations to measure and control downside risk is beginning to look quaint in light of the data that larger firms are now able to process. "We learned in 2008 that there is equity risk in many of the credit markets, private equity and even in securitized real estate," Taborsky said. "What if we could actually look at all the asset classes and say, what are the risk factors within each one? Could we break it down and actually consolidate all of those risk factors at the portfolio level, and think about the portfolio in terms of risk factors rather than asset classes?"
For instance? Emerging market and developed market stocks may respond very differently to currency movements. Depending on the movement, domestic stocks are likely to respond differently from stocks in various foreign countries. Large-cap domestic stocks may be affected differently from small-caps. In fixed income, different holdings will respond differently to changes in credit-spread duration. Higher-yield corporates are impacted by factors that also impact stock prices; Treasuries are not.
During his stint at PIMCO, Taborsky's team was tracking 240 different risk factors across various subsets of six or seven traditional asset classes. However, in the real world, commodity exposure, duration, equity risk, economic changes and various currency and interest rate factors outweigh most of the others.
The New Age investment manager can measure these risk factors directly, regardless of what asset class they happen to be associated with, and look for how they change under different market conditions. Of particular interest is what happens in a fat tail or black swan environment. When the markets enter a crisis, Taborsky said, the first response is a general rush to cash, which causes liquidity to fall. The return due to illiquidity, which is often positive, suddenly becomes a big negative number as people put a high premium on being able to move to the sidelines. Then riskless assets, like long-duration Treasury bonds, rally as yields fall to zero. Yield curves steepen when central banks cut rates and the market anticipates that the rates will go up in the future. Funding currencies like the yen and the dollar appreciate as hedge funds unwind the carry trade.
These events can be modeled, the risk factors can be applied in whatever proportion or degree you want and modified as conditions change. But perhaps more interestingly, you add a great deal of flexibility to the investment selection process without changing the way the portfolio behaves. An advisor can define an overall target allocation to each risk factor, and then decide which assets, and in which proportion, are most underpriced, which risk factors are most undervalued, which securities are most favorably positioned in the current market economy or perhaps (if it's a stock) which are simply best-managed. Rather than a 50/30/15/10/5 portfolio composed of asset classes, you build a portfolio of eclectic securities whose overall risk factors add up to the same total.
Build portfolio durability with scenario planning
Stephen McCourt, of Meketa Investment Group in Boston and San Diego, says that before the 2008 market meltdown, most institutional managers were not very different from the more sophisticated RIAs. They looked at historical mean returns and correlations, and used some version of mean-variance optimization to create a diversified portfolio at or near the efficient frontier.
What's changed? Starting in 2009, McCourt and his firm began replacing their mean-variance models with a process that takes into account the full spectrum of possible investment regimes. This can be as simple as drawing a graph whose vertical axis represents high and low inflation, and the horizontal axis represents low and high economic growth. This creates four different, very broad economic conditions, each of which would favor very different types of portfolios. Across the top, you have economies with, respectively, above-average growth accompanied by below-average inflation; and above-average growth accompanied by above-average inflation. Across the bottom you have an economy that exhibits below-average growth with below-average inflation; and an investment regime that features below-average growth combined with above-average inflation.
To his surprise, McCourt found that over the past century, the U.S. economy has spent roughly equal amounts of time in each of the four boxes. This allowed him and his staff back-test what a variety of different mixes of assets would have done under each of these very different economic regimes.
The firm has labeled a fifth economic scenario as "crisis." "About 4% of the periods we looked at fell into periods which exhibited a shock to the economy and the capital markets that caused asset prices to behave in unpredictable ways," McCourt explained. "During these crises, which included the last three months of 2008, the only assets that you would want to own are Treasury securities and insurance."
Creating all-weather portfolios is equally uncomplicated – you include assets that thrive in each scenario: TIPS, floating-rate bonds and commodities for the high-inflation, low-growth economic conditions; real estate and natural resources for the high-inflation, high-growth periods; investment-grade bonds and cash for the low-inflation, low-growth markets, and public/private equity and high-yield bonds for the low-inflation, high-growth economic time periods. Then you look at what that portfolio would have done in each economic regime, and if you feel confident that you know the current regime, you tweak the allocations to increase the beneficial exposures.
Create "quality" portfolios out of index subsets
Patrick Geddes, partner and chief investment officer with Aperio Group in San Francisco – formerly chief financial officer and director of quantitative research at Morningstar – recently showed an audience at the Northern California Regional Conference how a number of portfolio managers (including Aperio) are using an interesting variation on the "dogs of the Dow" investment approach. Instead of investing in the most underpriced or underperforming components of the S&P 500, they look for a subset that is defined in more attractive terms.
Geddes cited recent studies by Jeremy Grantham which indicated that (broadly labeled) "quality" companies outperform the market. "Quality" is first defined by profitability, which Geddes said is actually very close to a low P/E or value play. The second criterion is earnings variation; a tilt toward more stable companies raises performance. The others are lower-than-average leverage, which provides a performance kick during the loud pop of market bubbles, and lower historical volatility of the stock price.
Some of the largest asset management firms are looking at similar definitions of "quality" companies, and Geddes told the audience that their strongest similarity is their focus on lower-beta, lower-volatility stocks. "The research shows that if you look at long-term individual stock returns on a risk-adjusted basis," he said, "lower-volatility companies had higher returns – which is a complete anomaly in CAPM terms." (The best explanation of this research can be found in Advisor Perspectives, here and here.
Toward the end of his presentation, Geddes showed his audience a comparison of four different approaches to overweighting "quality" in client portfolios: one by Grantham/GMO; a Vanguard dividend-appreciation ETF (VIG); a portfolio created using S&P's quality rankings; and a portfolio that Geddes created at Aperio using the generic Grantham definitions of quality. All of them showed a lower earnings variation and higher earnings yield than the market as a whole. Most importantly, all of them have delivered much lower volatility than the market as a whole – which is fundamentally what clients are asking for post-2008. Using back-testing, Geddes found that they achieved higher geometric annual returns than the S&P 500 index, from which the component stocks had been selected, with lower standard deviation and beta.
Someday, when automobiles float above the ground and tourists visit domed cities on the moon, some or all of these New Age investment concepts will be as common as rebalancing software is today. All of them appear to be more sophisticated than the 60-year-old MPT/mean-variance approach to building asset class target allocations and rebalancing regularly. They all use more data and computing power than was available in the days when Harry Markowitz was writing his seminal paper, and most importantly, they are all grounded in real-world observations and the goals of managing downside volatility under conditions of uncertainty.
Beyond that, each of these New Age Investment concepts make for interesting conversation whenever somebody at an industry conference tells you smugly that MPT is outmoded – and then offers no viable alternative except intuition, hope and the Wall Street Journal.
Bob Veres'sInside Informationservice is the best practice management, marketing, client service resource for financial services professionals. Check out his blog or subscribe to get the Fee Samples report at: www.bobveres.com. Or check out his Insider's Forum Conference (September 17-19 in Dallas) at www.insidersforum.com.
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