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Now May Be A Good Time To Invest In High Quality Stocks – Here’s Why
To someone like me who has a long-held belief in the efficacy of value investing, the idea of investing in “quality” seems counterintuitive. After all, what makes value investing provide excess returns if not the “yuck factor” that causes investors to underprice value stocks? On the surface, quality investing seems to be the opposite of value investing. However, many famous investors include some notion of quality in their investing criteria, including some value investors. Warren Buffett has cited good returns on equity, consistent earnings power, and low debt as elements that he considers, and is famous for saying that “it is far better to buy a wonderful business at a fair price than to buy a fair business at a wonderful price.” Over the past several years, academic researchers have been finding that quality matters, both as a stand-alone factor and in conjunction with other factors, particularly value. For example, in an influential paper entitled ” Quality Minus Junk ,” AQR’s Asness, Frazzini and Pedersen (2014) found that “a quality minus junk (QMJ) factor that goes long high-quality stocks and shorts low-quality stocks earns significant risk-adjusted returns in the U.S. and across 24 countries.” Their definition of quality involves quite a number of attributes, including profitability, growth, safety, and payout. In a widely cited 2012 paper , Novy-Marx found that a relatively simple measure of quality, gross profits to assets, provided “roughly the same power as book-to-market predicting the cross-section of average returns.” (Book-to-market is perhaps the most widely recognized value factor.) Kozlov and Petajisto (2013) describe high earnings quality as “one of the most robust long-term patterns documented in the literature (e.g., Sloan , 1996, and Fama and French , 2008).” Studying the period 1988 to 2012, they found that quality had a higher Sharpe ratio (0.69) than either value (0.56) or the market (0.25). Using a composite quality factor combining profitability, accruals, and leverage, they found that after controlling for market, size, and value (the Fama-French three-factor risk model), a long-short alpha of 7.8% per year was achieved. Impressive results. Theories to explain why high-quality stocks offer investors excess risk-adjusted returns vary. Novy-Marx describes quality investing as “the other side of value” in that both value investors and quality investors seek to acquire assets undervalued by other investors. Value investors count on the fact that the poor profitability of value firms tends to mean-revert to some extent over time. Quality investors count on the superior profitability of quality firms to persist, and profit from the fact that investors tend to underappreciate, and underprice, high quality firms. The growing popularity of quality as a factor is reflected in the success of several ETFs that use various measures of quality as the focus of their portfolio construction. Of those focused on the U.S. stock market, the largest and most liquid include: PowerShares S&P 500 High Quality Portfolio (NYSEARCA: SPHQ ) iShares MSCI USA Quality Factor ETF (NYSEARCA: QUAL ) Market Vectors Morningstar Wide Moat ETF (NYSEARCA: MOAT ) This paper will focus on SPHQ because, at least at present, it is my preferred quality factor play. While QUAL is the largest and most liquid of the three, it uses a sector-neutral index. Although in a sense that makes it a “purer” play on quality, in my opinion, by neutralizing the sector tilts that would otherwise result, the quality effect is somewhat diluted. MOAT takes its strategy from the Warren Buffett philosophy of buying companies with a “wide moat” that protects the corporation’s franchise value. This factor is a variation on quality, certainly, but I find that the underlying index upon which the ETF is based has not generated as much alpha (defined below) as that of SPHQ. My methodology for analyzing an ETF focuses on its underlying benchmark index, which often has a much longer history than the live ETF performance record. (I use only passively managed ETFs that adhere closely to their benchmark indexes.) By subtracting the expense ratio from the historical return of the index, I can create a set of pro-forma ETF returns that are an excellent representation of how the ETF would have performed back in time. This provides much more data with which to analyze the risks and evaluate the risk-adjusted returns of an ETF. This methodology is also particularly handy when an ETF changes its benchmark index, as SPHQ is planning to do. As of March 18, 2016, the underlying index for SPHQ will change from the S&P 500 High Quality Rankings Index (Bloomberg: SPXQRUT) to the S&P 500 Quality Index (Bloomberg: SPXQUT). This means that the actual live performance history of SPHQ is of limited value in predicting how it will behave in the future: the past performance of the new index is much more valuable. The “old” index is based upon the time-honored S&P Quality Rankings System, which has been around since 1956. S&P’s methodology document does not offer much detail, but simply states that the Quality Rankings System “attempts to capture the growth and stability of earnings and the dividends record” over a 10-year period, adjusted “for changes in the rate of growth, stability within long-term trends and cyclicality.” Got that? The obfuscation probably indicates that the actual details of the methodology have evolved over the past 60 years. The “new” index is much more transparent. The methodology document says that the new quality score “is calculated based on three fundamental measures, return on equity, accruals ratio and financial leverage ratio.” The three fundamental ratios are defined as follows: • Return on Equity (ROE). This is calculated as a company’s trailing 12-month earnings per share divided by its latest book value per share. • Accruals Ratio. This is computed using the change of a company’s net operating assets over the last year divided by its average net operating assets over the last two years. • Financial Leverage Ratio. This is calculated as a company’s latest total debt divided by its book value. By the way, two of these three attributes, ROE and leverage, are the same attributes that QUAL uses in its definition of quality. The third QUAL attribute, earnings variability, makes it somewhat similar to the “old” S&P Quality Ranking. By using accruals as its third factor, the new SPHQ will be tied more closely to the work of Sloan (1996) among others, showing that investors systematically over-emphasize the accrual components of GAAP earnings and under-emphasize the cash components, which are much more sustainable. This may help explain why the historical alpha of the index (defined below) is so high. My analysis of the risk-adjusted returns for SPHQ’s new benchmark index starts by measuring the sensitivity of its returns to four risk factors that capture much of the risk common to most ETFs: Stock market risk (MKT), as measured by the S&P 500 Index Bond market risk (LTB), as measured by the 10 Year Treasury Benchmark Index Currency risk (DLR), as measured by the U.S. Dollar Index Commodity risk (OIL), as measured by the West Texas Intermediate Crude Oil Index Click to enlarge SPHQ’s new index goes back to December 31, 1994, but I need some history in order to estimate its risk factor sensitivities (often called betas) using exponentially weighted multiple regressions. Consequently, the graph above starts on December 31, 2000. Of the four risk factors, equity market beta (labeled MKT in red) is its only consistently significant risk factor sensitivity. Its historical equity market sensitivity has generally been between 70% and 100% (or a beta of .7 to 1.0) which is about as I would have predicted. The other three risk factors are not consistently significant, but interest rate sensitivity (LTB) does pop up occasionally. The next graph (below) tracks the cumulative return of SPHQ’s new index (in black), and disaggregates it into return due to each of the four risk factor sensitivities and residual return, which is what I call “alpha.” Most of the index’s return is explained by its equity market sensitivity (red), as expected for an index with a MKT sensitivity of 70% to 100%. (To calculate the return from MKT sensitivity, I multiply the index’s previous month-end MKT sensitivity times the monthly price return of the S&P 500. I use the same methodology for the other three risk factors.) The residual return (orange) is the total return minus the return from the four risk factor sensitivities. Residual return, or alpha, is what I want to maximize in my portfolios. Click to enlarge SPHQ’s new index has generated an average alpha of about 3.17% per year since 2000, with a standard deviation of 3.68%, and a return/risk ratio of 0.86. Those are very impressive statistics for a single factor portfolio. Even if my estimates of MKT beta are too low, using a MKT beta of 1.00 would still result in an average alpha of 1.88% per year. Most ETFs, and their benchmark indexes, have no discernible alpha: their return is entirely explained by risk factor sensitivities. Both the power of and the persistence of the risk-adjusted excess return for SPHQ’s new benchmark index are impressive. To be sure, there is a risk that some of the historical alpha is a random artifact of the time period tested. Also, there is some risk that the construction of the index was influenced to some extent by “what worked” over this time period. Even if the good people at S&P were only following the academic literature, the academic researchers themselves are no doubt somewhat guilty of “data snooping,” since that is a bias that no one can completely escape. Academic researchers read the research of others and are thus influenced by that information. However, S&P is applying the same Quality Index methodology not only to the S&P 500, but also to 15 other headline indexes around the world, which somewhat reduces the risk that it was unduly influenced by “what worked” for the S&P 500 alone. Also, based on my research, there seems to be no indication that the quality factor has become so popular that its valuation is stretched. (By comparison, for example, the low volatility factor seems to have been bid up to the point where some caution is warranted.) Finally, my research indicates that returns to the quality factor are positively associated with equity market volatility, which has been higher than average and may provide a bit of a boost to the return of the quality factor. Historically speaking, the later stages of bull markets have been good times to emphasize quality. In short, now may be a good time to invest in quality, and SPHQ is a good way to do it. Disclosure: I am/we are long SPHQ, QUAL, MOAT. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it. I have no business relationship with any company whose stock is mentioned in this article. Additional disclosure: My long and short positions change frequently, so I make no assurances about my future positions, long or short. The information contained in this article has been prepared with reasonable care using sources that are assumed to be reliable, but I make no representation or warranty regarding accuracy. This article is provided for informational purposes only and is not intended to constitute legal, tax, securities, or investment advice. You should discuss your individual legal, tax, and investment situation with professional advisors.
A Walk In The Woods: Evaluating Investment Strategies For The Long Haul
A Walk in the Woods , the book by Bill Bryson and movie starring Robert Redford and Nick Nolte, is a humorous yet insightful account of two novice hikers who set out to through-hike the Appalachian Trail. The endeavor parallels that facing many investors: setting out on what seems an almost implausibly long adventure with very little first hand knowledge of the challenges they are likely to encounter along the way. The parallels between hiking and investing extend further. In both cases, the participants receive all kinds of advice and are sold all sorts of things that turn out being either of dubious value or entirely counterproductive. Two guidelines stand out that apply as much to investing as to hiking. One is that fees are like gear in your pack – too much stuff that isn’t very useful can really slow you down, but some of that gear is really useful. Another is that the environment changes over time – which implies that different gear is appropriate at different times. Investment strategy is an extremely important decision for investors. The three main approaches of active, passive, and smart beta (also known as factor investing) each has advantages and a deserved role for certain situations. Too often, however, the pros and cons of each are overly simplified and applied dogmatically with little consideration given how conditions might change over time. While active management as a whole has performed poorly, that poor performance has not been universal as many assume. Research over the last several years reveals that the underperformance is not so much a structural issue with active investing as it is an endemic problem with the industry. It shouldn’t be surprising that active portfolios that are fairly concentrated, that charge reasonable fees, and that focus on inefficiently priced asset classes tend to perform better. In other words, active management is far from a futile exercise, but it does depend on the judicious use of “gear”. Critics who are completely dismissive of active management miss the reality that there are a number of excellent managers. Indeed, it defies common sense that given examples of exceptionalism in every realm of human endeavor, that there would be none in the field of active management. It is right to be skeptical, but not to be dismissive. A big part of the challenge for active investing is the cost/benefit tradeoff of its fees and this is exactly why passive investing has been such an attractive alternative. Indeed, passive investing today provides a far better way for people to gain exposure to the market than the main option available thirty years ago of buying a couple of individual stocks. No doubt, passive investing has been a useful addition to the amalgam of investment offerings. That said, the lower fees of passive investing relative to active do not provide an apples to apples comparison and are understated in an important sense. More specifically, Research Affiliates notes that, “Collectively, an active manager’s very important role is to increase market efficiency by identifying mispricing.” In doing so, active management actually provides a socially useful service in the form of price discovery by effectively making sure that market prices are fairly accurate. Without the efforts of active investors, there would be no natural forces to prevent prices deviating wildly from intrinsic values. As things currently stand, the costs of the service of price discovery accrue solely to active management clients, but the benefits accrue to passive management clients. Kenneth French (2008) studied these costs and found, “From society’s perspective, the average annual cost of price discovery is .67% of the total value of domestic equity.” This non-trivial cost accounts for a big chunk of the difference between active and passive fees. Indeed, it’s been a great deal for passive investors: it has been like having your hiking companion carry the tent, all of the food, and any shared gear for both of you, with no reciprocity. In addition to the traditional approaches of active and passive investing, a “third way” approach, often referred to as smart beta (factor investing), has become increasingly popular. The smart beta approach attempts to capture the best of both the active and passive approaches by facilitating low costs through automated selection processes and excess returns by leveraging finance theory and research. One well known “factor”, for example, is “value” and a recent favorite is “high quality” (usually determined by gross profitability). Smart beta is a legitimate concept and there is good reason to expect future developments in this area. Two threads of theory are relevant here. One was developed over twenty years ago by Kenneth French and Eugene Fama. Their research showed that returns could largely be described by the three factors of beta, size, and value in what is commonly referred to as the ” three factor model “. The implication for investors is that higher returns can be realized by increasing exposure to smaller stocks and to cheaper stocks. The economics of this quantitative approach have improved substantially as the costs of commissions and computing power have fallen relative to the costs active managers incur for doing fundamental research. Another thread of research pioneered by Research Affiliates argues that many indexes can be improved by weighting their constituents by variables other than that of market capitalization. Cap weighted indexes (such as the S&P 500), the argument goes, overweight the most overpriced stocks and underweight the most underpriced stocks, and therefore make systematic valuation errors. Their research shows that simply making random errors, as opposed to systematic ones, improves performance by about 2% per year. While this body of research certainly provides a valid foundation for some kind of smart beta (factor investing) approach, the investment industry has outdone itself the last few years by unveiling an enormous array of factor investing approaches to an investment audience ravenous for low fees and better performance. The recent paper put out by Research Affiliates entitled, “How can ‘smart beta’ go horribly wrong?”, provides some excellent research to help evaluate the recent proliferation of factors. Perhaps the single most important message from the paper is that the impressive results attributed to many of the new factors reveals more about the industry’s willingness and ability to mine data than it does about important new factors. More specifically, the authors found that, “factor returns, net of changes in valuation levels, are much lower than recent performance suggests.” In the case of high-profit companies, for example, they found, “When we subtract the returns associated with the rising popularity, and therefore rising relative valuation… the gross profitability factor loses more than 90% of its historical efficacy, delivering 10-year performance net of valuation change of just 0.39%.” In other words, “Many of the most popular new factors and strategies have succeeded solely because they have become more and more expensive.” While evaluating the costs and benefits of the three main investment strategies is a formidable task in its own right, investors in it for the long haul shouldn’t stop there. As the factor evidence highlights, things change over time and this absolutely holds true for the relative merits of investment strategies. John Authers highlights this point well in the Financial Times : “Using data from the past 25 years, Mr. Jones found a strong positive correlation between recent performance and buying decisions, in equities and bonds, for all of the classes of asset owners he looked at.” In other words, at the group level, everyone is a trend follower! In an important sense, this insight is frightening, but it also provides a useful warning: investment strategies may be just as subject to “inefficient pricing” as their underlying assets. It’s worth considering how such inefficiencies might get resolved. In the case of passive strategies, investors have been enjoying the benefits of efficient price discovery without having to pay for it. Insofar as the free ride persists, there is every reason to believe that investors will continue to jump on the passive bandwagon. The consequence of such trends will be to erode, over time, the ability of active investors to keep market prices fairly efficient. As this continues to happen, it is fair to expect that pricing efficiency will decline to a point where sufficient opportunities emerge for a smaller group of active investors to earn attractive returns over their costs, and that such excess returns will come at the expense of passive investors. In short, the free ride for passive investors may well be a one time gig. Smart beta too has had a very good run over the last few years but much of that appears to be temporal as well. As Research Affiliates notes, “We find that the efficacy of a factor-based strategy or a factor tilt (included by many under the smart beta umbrella) is strongly linked to changes in relative valuation, that is, whether the strategy is in vogue (becoming more richly priced) or out of favor (becoming cheaper).” Thus, since “Value-add can be structural, and thus reliably repeatable, or situational – a product of rising valuations-likely neither sustainable nor repeatable,” for many recent factors, the evidence points to situational and unsustainable. As a result, the authors conclude that “it’s reasonably likely a smart beta crash will be a consequence of the soaring popularity of factor-tilt strategies.” The Research Affiliates authors don’t uniformly disparage factors, however. Rather, they recognize that, “For the past eight years, value investing has been a disaster with the Russell 1000 Value Index underperforming the S&P 500 by 1.6% a year, and the Fama-French value factor in large-cap stocks returning -4.8% annually over the same period.” Largely as a result of that poor past performance, they find that the old Fama-French factor of value is currently “in its cheapest decile in history,” and therefore an attractive factor. Finally, the prospects for active management are mixed. On one hand, there are far too many active managers and far too many that charge fees greater than the benefits received. As a result, it is reasonable to expect the numbers to shrink. It is distinctly possible, and perhaps even likely, that as the active herd gets culled, so too will ever increasing opportunities emerge for efficient and focused active managers that aren’t “carrying too much weight” to take advantage of the overshoot of passive and smart beta strategies. A general lesson from all of this is that since the relative attractiveness of different investment strategies changes over time, it doesn’t make sense to take a dogmatic view towards them. Combined with the reality that each strategy has its own particular strengths in certain situations, it also makes little sense to think of any one strategy as being mutually exclusive of the others. The bottom line is that it makes the most sense to remain flexible. Further, there are two more specific lessons to consider in selecting investment strategies. One is to make sure that you get a good return from the fees that you pay, i.e. that you get a good “bang for the buck”. The other is that it makes sense to monitor changes in the environment that may warrant a different approach. Some of what passes as an “advantage” to one investment strategy in one situation may very well end up being a transient factor that can hurt you in the future. Your journey will be easier if you have the right “gear” (in the form of the right investment strategy) for each environment. Click to enlarge Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it. I have no business relationship with any company whose stock is mentioned in this article.