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Are Portfolio Decisions Feeding Volatility?

By Brian Brugman and Martin Atkin Markets had been unusually calm until risk surged in late-August. Bigger portfolio shifts when volatility is rising may be magnifying the spikes, making markets harder to navigate. We think the answer is focusing on more than risk. It’s true that volatility has moderated a bit, but is still higher than it was before August, and policy makers have taken note of these sudden shifts in risk. In fact, it was one reason the U.S. Federal Reserve decided to hold off on raising interest rates in September. To avoid being whipsawed, investors should take a holistic view of their portfolios. The focus should be on more than risk signals – return signals matter, too. Reactions to Market Volatility Amplify It Our research indicates that risk factors – and oversimplified asset-allocation decisions based largely on volatility measures – can create a painful cycle. The very trigger that prompts an allocation shift away from equities is itself influenced by the resulting sale. And volatility begins to feed on itself. There’s evidence that more managers are making decisions based largely on changes in market volatility. We looked at allocation changes over time, based on the implied equity exposure across different mutual fund categories, examining both high-risk and low-risk environments. We found that reductions in equity exposure have become noticeably larger since the Global Financial Crisis of 2008 ( Display 1 ). In fact, the downward shifts for tactical allocation strategies have almost doubled in size. It’s not surprising that tactical strategies make adjustments, but the bigger moves today are notable. Even world allocation strategies, which largely left their equity allocations alone pre-crisis, have begun to make significant equity reductions. Our analysis also suggests that portfolio shifts aren’t just bigger than before, but they’re also happening faster when volatility rises. This helps make volatility spikes more pronounced. The August episode confirmed this: selling pressure due to a collective decision to de-risk likely made the first few days more severe. Before August 24, when risk was below average, the group of strategies we isolated for this analysis had an average overweight to equity of 9%. Shortly after the spike in risk, they were significantly underweight, averaging 15% less equity exposure than is typical ( Display 2 ). The Problem of Volatility Tunnel Vision One likely reason for the rush for the exits is that many risk-managed strategies exclusively use volatility gauges as a simplified trigger for making allocation changes. Because this systematic approach is so common, it creates significant selling momentum in equities when risk starts to rise and the signal turns red. This risk “tunnel vision” can lead to even sharper moves in the very metrics used to determine portfolio positioning. We don’t think these types of asset-allocation triggers are robust enough. It’s important to determine if a sudden change in the risk environment is temporary or long-lasting. That knowledge can make a portfolio manager less likely to make the classic mistake: trend-following and selling into distress at a market trough. A Holistic Process Must Integrate More than Risk Signals One way to tackle this problem is to include both expected risk and expected return across asset classes in quantitative analysis. It’s also important not to leave the fundamental judgement behind, and to consider how technical factors in the market impact the asset-allocation equation. All things considered, we think it makes sense to be modestly underweight equities in the current environment. Volatility is above average, but we think the initial spike may have been exacerbated by indiscriminate selling from risk-managed strategies. Stalling growth in emerging markets and falling commodity demand may not be as much of a spillover risk for developed economies as some investors may think. In turbulent times like these, the ability to be dynamic in shifting equity beta can be very helpful. And volatility is a valuable signal that helps inform that decision. The key is to make sure that the trigger for shifting beta isn’t overly sensitive to changes in volatility alone. The views expressed herein do not constitute research, investment advice or trade recommendations and do not necessarily represent the views of all AB portfolio-management teams. Brian T. Brugman, Portfolio Manager – Multi-Asset Martin Atkin, Head of U.S. Client Solutions – AllianceBernstein Multi-Asset Solutions Group; Investment Director – Dynamic Asset Allocation; and National Managing Director – Bernstein Global Wealth Management

Making Sense Of Long-Term Returns

By Michael Batnick, CFA All advisers face the same challenge: How can we best help investors understand what sort of long-term returns they can rationally expect? This is an extremely important topic. It forms the basis of Social Security projections, pension estimates, and determining how much a household needs to save to retire comfortably. What’s often absent from a discussion on stock returns is the many ways in which returns can be measured. There are a lot of questions: What is the appropriate time period? Does one year make more sense than three years? What about a rolling return versus an annual return? When do we start measuring? Should we include the Great Depression or look at post World War II numbers? If you can’t see the importance of this conversation yet, it may be time for a quick reminder. Let’s go over a couple of different ways that we could measure the return of the S&P 500 Index. Remember as you’re reading this that it’s our job to make sure investors understand these nuances. Price Return vs. Total Return If you invested one dollar in the S&P 500 in 1928 (no, this was not possible at the time), it would have been worth ~$109 by the end of August 2015. If you were to measure the total return, however, that $1 jumps from $109 to $3,362! Nominal Return vs. Real Return It’s always important to account for inflation. If we do that, our $1 invested in 1928 becomes $342 in 2015. Compounding at 6.8% after inflation is still an impressive long-term return, even if it is just a tenth of what the total return looks like before inflation is accounted for. Average Return vs. Compound Return The S&P 500 (total return) has averaged nearly 12% a year since the mid-1920s, however, investors’ wealth would have compounded at just under 10%. The reason there is such a large gap between arithmetic and compound returns is because the 12% average returns are not earned in a straight line. There were years like 2008, when the index fell 37%. Once stocks lose 37%, they need to gain 58% to get back to even. As we often find ourselves explaining to the investing public, there are major differences between average annual returns and the returns of any individual year. In the chart below, you’ll notice that the average return of 7.5% (price only) was rarely seen in any one year. Only about 5% of the time did investors generate returns even close to the average. S&P 500 (Price Only) Perhaps a better way to present this data is the distribution of returns. S&P 500 Distribution of Annual Returns (Price Only) This can provide investors with a better idea of what the range of possibilities is. Expecting an average return of X% over a 20-year period is one thing, but being prepared for the outlier years and surviving them is something else entirely. And, of course, these outlier years can happen one after another. How does it change the way that you look at the world if you learned about markets during a year when they performed terribly? It’s a helpful exercise to break returns into different time periods to demonstrate the life-cycle experience an investor might have had. The chart below shows “bull” (green) and “bear” (red) market regimes throughout history. S&P 500 (Log Scale) People born in 1900 would probably count the Great Depression as the formative experience of their investing life cycle. It’s hard to imagine that living and working through it would not leave an indelible impression. Although every period in history is unique, one thing we can say with certainty is that bull and bear markets are permanent features of investing. Take a look at the returns in the table below. In the last 90 years, there were several periods of time when investors’ wealth compounded at very low rates. Pointing to average historical returns is little comfort to investors in the depths of a protracted bear market. Likewise, when markets get overextended, people tend to throw caution to the wind, learning nothing from history. Of course, we have to consider the reliability of the data itself. In an eye-opening paper published in The Journal of Investing, entitled ” The Myth of 1926: How much Do We Know about Long-Term Returns on US Stocks ?” Edward McQuarrie looks at the Center for Research in Security Prices (CRSP) database , which many argue is the gold standard for historical stock returns. He writes: “1) The CRSP time frame, which begins in 1926, excludes more than 50% of the historical record of widespread, large-scale stock trading in the United States, which goes back almost 200 years; and 2) for more than 50% of its time frame, the CRSP dataset excludes the majority of stocks trading in the United States, especially the smaller and more vulnerable enterprises. Putting these two facts together, we may say that CRSP provides comprehensive price series data for less than 20% of the total US stock trading record, aggregating across time period and type of stock.” McQuarrie shares some interesting insights about the way we think about historical stock returns. While not suggesting that the CRSP has failed in its due diligence, he makes the point that there are listing requirements that have undoubtedly omitted stocks from the database. We have seen that different starting periods and different ways of measuring returns can have significant implications for investors. So what if anything can we conclude and suggest to our clients? Here are a few things to remember: Past performance is absolutely not predictive of future results. Data can be manipulated! Sticking with an investment plan during a bad year (or a series of bad years) is what will make them successful. The results of diversification are predictable even if the results of an investment are not. Having a command of these issues and laying them out for our clients beforehand will make for a much more enlightening – and realistic – presentation. Disclaimer: Please note that the content of this site should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute.

8 Questions That Should Be Keeping Buy-And-Holders Up At Night

By Rob Bennett Set forth below are eight questions that should be keeping Buy-and-Holders up at night. 1) What are the top ten changes that have been made in the Buy-and-Hold strategy as a result of Shiller’s “revolutionary” findings? Yale Economics Professor Robert Shiller showed in peer-reviewed research published in 1981 that valuations affect long-term returns. That “revolutionary” (Shiller’s word) finding changed everything we thought we knew about how stock investing works. If valuations affect long-term returns, stock risk is variable rather than fixed; that means that we can reduce risk by taking valuations into account when setting our stock allocations. Shiller’s book exploring this finding in depth was a national bestseller. He was awarded a Nobel prize for his work. Given the importance of this advance in our understanding of how stock investing works, one would have expected that the Buy-and-Holders would have made scores of changes to their strategy to reflect the new understanding. Can the Buy-and-Holders identify even ten changes? Can they identify even one? 2) Why was there no reaction from the lead promoters of Buy-and-Hold when Brett Arends of the Wall Street Journal wrote that they are “leaving out half the story” of how stock investing works? I have been writing about the dangers of Buy-and-Hold for 13 years now. So I was encouraged when I saw the Arends article saying that to ignore the effect of valuations on long-term returns is to leave out half the story of how stock investing works. I was amazed to see the article go down the memory hole without generating comment (except by me). Arends could be wrong. But, if he were, it would be in the interests of the Buy-and-Hold advocates to point out his mistake. Why did no one do this? 3) Why has there been no clear explanation of the errors that were made in the Old School safe-withdrawal-rate studies? I pointed out the error in the famous “4 percent rule” in May 2002. I got a lot of flak from Buy-and-Holders for doing so. But 13 years later just about every major publication in the field has run an article noting that the 4 percent rule is not backed by the historical data and that it would be dangerous for retirees to continue to follow it. How was this mistake made? Why did it take so long to discover it? What can we learn from the mistake? 4) How was Shiller able to predict an economic crisis that began in September 2008 in a book published in March 2000? I am the only person in this field who has blamed the economic crisis on the heavy promotion of Buy-and-Hold strategies (the idea that investors don’t need to lower their stock allocations when prices reach insanely dangerous levels caused the out-of-control bull market of the late 1990s and the loss of the $12 trillion of pretend wealth created by the bull market caused consumer buying power to constrict enough to cause hundreds of thousands of businesses to fail). Except for Shiller. Shiller has not said in the wake of the 2008 crash that Buy-and-Hold caused the economic crisis. But he did predict the loss of trillions in pretend wealth in Irrational Exuberance , a loss that he suggested would likely take place late in the first decade of the new century. How did he know? And why have others not drawn the obvious conclusion that, since Shiller’s investing model was the one that predicted the crash and the economic crisis, it has earned credibility in the eyes of fair-minded people? 5) How did Bogle come up with his rule that investors never need to lower their stock allocations by more than 15 percentage points no matter how high stock prices go? A regression analysis shows that the most likely 10-year annualized return for an index-fund purchase made in 1981 was 15 percent real. In 2000, it was a negative 1 percent real. An 80 percent stock allocation makes sense in the former circumstance. A 20 percent stock allocation makes sense in the latter circumstance. That’s a change of 60 percentage points, not 15. Bogle’s number is off by 400 percent. 6) Why do Buy-and-Holders become so emotional when their claims are challenged? I have been banned at over 20 investing discussion boards and blogs. It is a common experience for me to receive apologies from the site owners who ban me in which they note that they believe that my work has great value and that they consider me one of the most polite and warm posters on the internet. They say that they are banning me solely because their Buy-and-Hold readers demand it and because they don’t want to lose the business brought by these followers of a purportedly research-based strategy. Huh? Why would followers of a research-based strategy be upset by challenges to their beliefs? Wouldn’t they see such challenges as a way to confirm and thereby strengthen their convictions? 7) Why was Wade Pfau not able to find a single peer-reviewed study showing that long-term timing doesn’t work or isn’t required? I worked with Academic Researcher Wade Pfau for 16 months. Wade holds a Ph.D. from Princeton. He performed an in-depth search of the academic literature trying to identify a single study showing either that long-term timing (changing one’s stock allocation in response to big valuation shifts with the understanding that it might not produce benefits for ten years or longer) doesn’t work or isn’t required without success. Could it be that, contrary to the core belief of the Buy-and-Holders, one form of market timing always works and is always 100 percent required for investors seeking to keep their risk profiles roughly constant? 8) Is there any reason to believe that price matters any less in the stock market than it does in every other market known to humankind? Price is what makes the car market run. Price is what makes the banana market run. Price is what makes the sweater market run. Price is what makes the grass-seed market run. How can we be so sure that price does not matter when buying stocks? If large numbers of the participants in these other markets became convinced that it was not necessary to take price into consideration when making purchases, it would cause them to collapse. Could that be why we have been seeing so much turmoil in the stock market in recent years? Disclosure: None