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Addressing Long-Term Goals During Short-Term Volatility

Assumptions about future returns are made every day by a wide variety of investors. These assumptions are often based on annualized returns that can mask tremendous amounts of performance variation. For instance, a simple blended portfolio consisting of 55% U.S. large-cap stocks and 45% intermediate U.S. Treasury bonds delivered an annualized return of 8.5% since 1926. However, since the start of that year, in 20% of rolling 10-year windows, a 55/45 blended portfolio failed to achieve a return of even 6%. We believe that the next 10 years may be a period where returns to a passive buy-and-hold balanced strategy are likely to come up short. Investors facing this likely reality have three options: 1. Lower their long-term return assumptions Return assumptions should represent good faith estimates of the likely long-term return on investment. While a lower-return assumption may be necessary for those with unrealistic expectations, others should carefully evaluate their investment approach to determine if there is a way to increase the odds of successfully meeting their objectives. 2. Raise their target allocation to equities However, the greater expected return from stocks versus bonds is also accompanied by greater expected volatility. Greater volatility can result in greater drawdowns that can adversely impact the ability of some investors to meet more near-term objectives. 3. Embrace a flexible, active asset allocation strategy This may be the most realistic of the three alternatives. At any point in time, equity market returns are driven by one or more of the following factors: fundamentals, valuation, and sentiment. As active managers, we prefer a framework that seeks to identify regimes where the risk of sustained capital loss (i.e., a bear market) is high, or conversely market environments that strongly favor owning stocks. Such a framework also acknowledges that the market is likely to go through periods where neither regime is overwhelmingly likely. That last environment is where we find the U.S. stock market at the outset of 2016. While valuations are somewhat elevated, the U.S. economy remains far from overheating, and sentiment is anything but speculative today. In an environment such as this, investors can be rewarded by taking advantage of market volatility to increase their exposure to attractively valued and well-positioned markets/sectors/companies. Nevertheless, successful asset allocation is not just about what an investor owns, it also is about what one chooses not to own. Investors in passive strategies must own whatever allocations make up the index, regardless of the merit of those investments. This can prove disastrous when an index becomes heavily-skewed toward overvalued segments of a market. Valuations suggest that over the next 10 years, a static asset allocation approach is likely to fail to meet the long-term return targets of many investors. The reason is simple – starting valuations both in equity and fixed income are not priced to deliver the returns that history has led investors to expect. In a low-return world, investors can ill-afford to operate without what we believe is the most effective tool for increasing the likelihood of achieving their long-term return objectives: an active approach to asset allocation. History suggests that the volatility of the opening trading days of 2016 is hardly unprecedented. Active asset allocation provides investors the opportunity to respond to these developments and shift the odds of long-term success more in their favor.

Smart Beta Strategy: Aces Australian Scrutiny

Paul Docherty, a senior lecturer at Newcastle Business School, University of Newcastle, in Australia, has studied the performance of the factors that underlie smart beta portfolios within the equity markets of that country. On the basis of a long time-series of data, Docherty has concluded that four such factors “all generate positive abnormal returns” in those markets: value, momentum, low vol, and quality. Diversifying across these four factors is the smart way to make use of smart beta , he thinks. The other factor in the usual list of five is size . Since Rolf W. Banz’ work in 1981 , there has been speculation that small firms generate greater return than do larger firms, after controlling for risk. But Docherty can’t find evidence for this in Australia. After accounting for illiquidity and transaction costs, the remaining “size effect” is insignificant. “Not an investable anomaly,” he says. This is in accord with recent international findings. But with the other four smart-beta factors? Value refers to the book-to-market ratio. This is also known as the HML ratio, from the phrase “high minus low”, given the Fama-French argument that companies with high book-to-market ratios (value stocks) outperform those with low ratios (growth stocks). Docherty mentions that there are several other ways to measure “value” aside from book-to-market. One might use the P/E ratio, for example, or compare cash flow to price. But book-to-market “is the superior proxy for value in the Australian equity market.” The HML ratio has had a good run over most of the sample period Docherty employs, beginning in 1990, and its cumulative returns across time are impressive, but it’s important to observe that “there is an evident reduction in the gradient of the cumulative returns in recent years.” Performance of the WML factor in Australia Mean St. Dev. T-Strat Sharpe Ratio Hit Rate Max Drawdown 1991-2015 1.29% 5.19% 4.27 0.25 63% -19.96% 1991-1995 0.31% 3.53% 0.68 0.09 53.3% -7.98% 1996-2000 1.15% 5.28% 1.68 0.22 65% -19.96% 2001-2005 2.61% 5.12% 3.95 0.51 71.7% -8.51% 2006-2010 0.89% 6.53% 1.06 0.14 61.7% -13.68% 2011-2015 1.37% 4.80% 2.15 0.28 64.9% -13.41% (Source: Docherty, “How smart is smart beta investing?” Table 3.) Moving on… the momentum factor (or “winner-minus-loser”, that is, WML) is the best-documented anomaly of the traditional five. Docherty cites a recent study by Vanstone and Hahn that reports that “the capacity of momentum investing in Australia is sufficiently large in dollar terms to support its practical implementation as an investment strategy.” Low vol has been under discussion as a factor in above-normal returns since a seminal paper by Black, Jensen, and Scholes in 1972. The notion of a low vol premium by definition implies that the actual security market line is much flatter than the one predicted by the Capital Asset Pricing Model. Significant Drawdowns Docherty’s data indicates that the mean monthly return on the vol factor in Australian markets is 1.45%, the highest monthly return of any of the five factors he looked at. Both the vol factor and WML share one drawback – both have seen significant drawdowns. The max drawdown for the vol factor in Australia over the covered period in 25.56%. Then, there is quality , or quality-minus-junk (QMJ). As in all fields, “quality” in the realm of capital assets is a tricky thing to define. As Docherty understands it, the term refers to asset growth and accruals (negatively) as well as to corporate governance and profitability (on the positive side). Quality, as so understood, has “relatively modest returns compared with other smart beta factors,” he finds, but it does provide a hedge against downturns in broad market movements. What is most intriguing about Docherty’s numbers is that the correlations among the factors he discusses “are quite low and, in many cases, negative.” Given this situation , the real question is not whether smart beta is smart (it is) or which factor is smartest (that depends on where one is in the business cycle, and other matters), but what mix of the four (or, if one wants to continue including size, what mix of the five) factors is optimal.