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Expanding The Smart Beta Filter: Does It Help?

Summary iShares factor ETFs provide a source of well tested algorithms for factor-based stock selection. Previous examination of QUAL, MTUM and USMV have shown that this approach can produce actionable investing ideas. Can adding other, well-documented, factors improve the selective powers of this approach?. I continue to think about mining the iShares smart beta ETFs for investing ideas. In this article, I want to discuss expanding the source of data to include ETFs for risk premium factors beyond those I looked at previously. Let me start by reviewing some recent results from this exercise. My starting premise is that the set of ETFs offered by Blackrock iShares emphasizing individual risk-premium factors provides a rich source of securities that have passed their quantitative filters for the target factors. Previously I looked at three of these ETF focused on low volatility, quality and momentum factors. My goal was to find stocks that appeared in the holdings from more than one of these ETFs with the idea that such stocks have passed the MSCI index screen for more than one factor. I identified 14 stocks that occur in all three ( A Quest for the Smartest Beta ) and 60 more that occur in at least two ( Can We Find Smarter Beta From 2 Factor Portfolios? ). I found the results intriguing. First, The ETFs all beat the market, as represented by the SPDR S&P 500 Trust ETF ( SPY), as does the equal-weighted portfolio of ETFs. By analyzing a hypothetical portfolio, I was able to show that the 14 holdings from the set occurring in all three ETFs has soundly beaten all of the ETFs as well as the equal-weighted portfolio of the ETFs. This is fully documented in the second article referenced in the previous paragraph. Readers commented on my omission of two of the classic risk-premium factors and offered suggestions on incorporating them into the models. The missing factors, value and size, are, of course, important, and I’m going to look at how much, if anything, they add to the exercise as I go on. But first, let me digress here for a paragraph or two and consider why I felt these factors could, or should, be left out. Let’s start with the objective: It is to mine the quantitative algorithms of MSCI’s factor indexes for high-potential stocks. As I explained in the second article, I wanted to keep this exercise to a manageable number of funds and holdings. I thought three was optimal. Also, value and size are much less straightforward to deal with in this context. These factors form the basis for the traditional classifications of stocks: Value vs Growth and Large-, Mid-, Small-Cap. It’s the Morningstar style box. Value is variously defined and it’s not at all unusual to see the same securities turning up in growth and value funds from the same group. Size is easy, but pairs poorly with other factors depending on how one makes size cuts. By contrast, quality, momentum and low volatility are less rigorously defined (even considering the vagueness of how value is defined) and, in my view, more amenable to quantitative analysis that can produce unique, actionable results. So, I went with quality, momentum and low volatility. Quality is something I’ve been thinking about a lot, and I like the algorithm QUAL is using to define the factor (discussed here ). Momentum is another factor that can add serious alpha. I’ve been maintaining some momentum-based investing strategies in moderate-size portfolios using commission-free ETFs for several years to modest success. A problem with momentum is it tend to generate volatility and I’ve tried to modulate that in my own investing by adding a weighting for volatility (some day I may write an article on this). This reflects my appreciation for low volatility and the thinking that led me to include USMV in this project. The Factor ETFs All this is a bit subjective and intuitive, which is always something to guard against in an evidence-based approach, so I’ve decided to take readers’ advice and look at two more of iShares MSCI factor-index funds. I wanted to see if adding value and size to the analyses can improve the results. To this end, I’ll be deconstructing five ETFs looking for common holdings. The list of five, starting with the three considered earlier: iShares MSCI USA Minimum Volatility ETF (NYSEARCA: USMV ), iShares MSCI USA Momentum Factor ETF (NYSEARCA: MTUM ) iShares MSCI USA Quality Factor ETF (NYSEARCA: QUAL ) iShares MSCI USA Value Factor ETF (NYSEARCA: VLUE ) iShares MSCI USA Size Factor ETF (NYSEARCA: SIZE ) One problem right off the bat is the size of SIZE. At 636 holdings, it’s nearly four times the size of the next largest fund (USMV with 165). Perhaps as a consequence, it adds little value to the analysis, although, despite having 636 holdings, it is the least correlated with the broader market of the five ETFs. (click to enlarge) Pay particular attention to the last column in that table. SIZE is the least correlated with SPY, much lower than I would have anticipated. Note too, that VLUE is less correlated with SPY than any of the other three ETFs. I’ll start by looking at the performance of these ETFs and ask if the two new additions look likely to add any value. (click to enlarge) For the past year, they have lagged the previously considered three. But this has not been a good year for value stocks, and SIZE may add an advantage from that low correlation coefficient that will only become evident when it becomes an important variable. Deconstruction the ETF Portfolios As I did previously, I downloaded the full holdings of each of the ETFs into a spreadsheet and analyzed all five for stocks that appeared in more than one of the funds. Here’s a summary of the results. As anticipated, it quickly gets unwieldy. Only a single stock is in all five funds, and there are 20 that appear in four of the ETFs. Beyond that, there are too many to be useful for my purposes. What’s interesting is the 14 stocks that formed the basis of the earlier analysis by occurring the holdings of QUAL, MTUM and USMV, are all included in the 21 four- or five-fund stocks here. Thirteen of the 14 occur in either VLUE or SIZE; only one is in both. So, if we take the top 22 stocks here, i.e. those occurring in at least four funds, we have added eight to the previous list. So far, so good, we have increase our candidate pool; but not excessively, it’s still a manageable number. Here, for the record, are the 22 stocks with the 14 from MQLV set in italics: Axis Capital Holdings Ltd (NYSE: AXS ), Accenture Plc (NYSE: ACN ), Ace Ltd (NYSE: ACE ), Arch Capital Group Ltd (NASDAQ: ACGL ), Assurant Inc (NYSE: AIZ ), AT&T Inc (NYSE: T ), Chevron Corp (NYSE: CVX ), Chipotle Mexican Grill Inc (NYSE: CMG ), Chubb Corp (NYSE: CB ), Eli Lilly (NYSE: LLY ), Home Depot Inc (NYSE: HD ), Nike Inc Class B (NYSE: NKE ), O’Reilly Automotive Inc (NASDAQ: ORLY ), Partnerre Ltd (NYSE: PRE ), Reynolds American Inc (NYSE: RAI ), Sigma Aldrich Corp (NASDAQ: SIAL ), Starbucks Corp (NASDAQ: SBUX ), Target Corp (NYSE: TGT ), Travelers Companies Inc (NYSE: TRV ), United Health Group Inc (NYSE: UNH ), Visa Inc Class A (NYSE: V ), WR Berkley Corp (NYSE: WRB ). The first entry, Axis Capital, is the single name in all five ETFs. Sector representation is dominated by Financials and Consumer Discretionary, but it is more diverse than the set of 14 derived from three ETFs. (click to enlarge) Here is how these 22 stocks are allocated among the ETFs. As we see, all are in SIZE. SIZE is therefore acting as a binary filter to select among funds that are in three of the four funds but do not pass the size-factor filter. This is potentially a useful filter. USMV holds all but one, so it’s a similar filter. VLUE is a stronger filter. Less than half the funds are in VLUE’s holdings. I find this interesting and would have expected a result like this from MTUM, which only misses four, none of which is likely to be mistaken for a momentum stock in the current market. As I refine my thinking on this whole exercise, I have to spend more time considering how VLUE affects results. Portfolio Analysis As previously, I wanted to see the results of this filtering process. There is only one record to analyze. The funds rebalance at the end of May and November and, to my knowledge, do not publish past index allocations. Thus, there is only one analyzable record, that for the current cycle which is about 5 months old. We can see how various permutations of these results have fared since the last rebalance. I ran analyses on Portfolio Visualizer for equal-weighted portfolios comprising the following with the coding I’ve used in the tables: Five ETFs: 5ETFs EW QUAL, USMV, MTUM: 3ETFs (QVM) EW Stocks present in holdings of at least 4 of the ETFs: VQMVS(4+) VQMVS(4+) stocks in QUAL and MTUM only: QxM VQMVS(4+) stocks in QUAL and VLUE only: QxV VQMVS(4+) stocks in MTUM and VLUE only: MxV I pulled out the last three sets because USMV and SIZE were doing little more than serving as a final filter for the other three ETF holdings’ overlaps, so I thought it useful to see how those components were contributing to the results. Here are those results. (click to enlarge) As we can see, the five ETFs as an equal-weighted portfolio beat SPY, but lagged the subset of three ETFs. Let’s not forget, however, that this is only a five-month result. Longer term results can show benefit to holding all five factor ETFs, or at least four of them. For this we do have a longer record. The full record is still limited as the youngest fund only dates to July 2013. From July 2013, equal-weighted portfolios, rebalanced semiannually, of combinations of five, four and three of the ETFs turned in the following performance results. (click to enlarge) Removing either SIZE or VLUE added return and reduced maximum drawdown. Removing both, i.e. going to only QUAL, MTUM and USMV, as previously considered, improved both metrics. Volatility did increase slightly, but in all cases it remained lower than the S&P 500. These results indicate that there has been no advantage to adding VLUE or SIZE to a factor-based ETF portfolio. I’d like to say this validates my decision to use only MTUM, QUAL and USMV in my analyses, but the fact remains that the data set is too limited to draw such a conclusion. Let’s return to the previous table – and our main topic – and see how stocks filtered from the ETFs on the basis of their presence in four or more funds fared. Over the past five months, the combined ETFs returned 1.40% CAGR for all five, and 5.75% CAGR for the MQLV three. A portfolio of the 22 stocks found in four or more ETFS 29.67% CAGR and did so with a max drawdown of only -3.35% vs. -6.52% for the better performing of the two ETF portfolios. Separating out the component ETFs we see that the combination of QUAL an MTUM added a remarkable level of value, far outpacing a combination of either of the two factors with value as represented by VLUE. Yet again, I must emphasize the limited data available. But the results certainly begin to suggest that these ETFs, especially MTUM, QUAL and USMV, are attractive sources for filtered lists of stocks that rank strongly for risk-premium factors which can be further filtered for having been selected by the quite different quantitative criteria by multiple funds.

The Free Lunch Of Factor Investing

Factor investing is a hot topic among the folks in the business of designing better investment mousetraps. So rather than focus on individual stock picking, this approach recommends that you invest in an index that’s weighted towards all specific characteristics (“factors”) shared by groups of stocks that make them more likely to beat the market. These include factors such as momentum and value. By doing so, factor investing combines the low costs and simplicity of indexing with the additional possibility of “beating the market.” Researchers have looked at dozens of factors that appear to outperform the mainstream, broader market-weighted indexes. A handful have proven to be meaningful. These findings have also been responsible for the launch of dozens of factor-based exchange-traded funds (ETFs) in the last five years or so. Value Value investing has a long and storied tradition in investing, going back to the legendary Ben Graham. As outlined in his classic work, ” Security Analysis ,” measures such as the price-to-book ratio (the firm’s share price divided by the value of its assets minus its liabilities) and the price-earnings ratio are the most basic ways for measuring value. Stocks with low valuations have tended to beat those with high valuations over time. In the United States, the cheapest 30% of large- and mid-cap stocks (based on price/book) have outpaced the most expensive 30% by approximately 2.5% annualized from 1927 through May 2015, according to data cited by Morningstar. From its inception in March 2006 through May 2015, the Guggenheim S&P 500 Pure Value ETF (NYSEARCA: RPV ) outpaced the market-cap-weighted S&P 500 Value Index, which tracks the cheaper half of the S&P 500, by 2.8% each year. Morningstar ranks it as a five-star fund. It is down 7.79% year to date. Size The small-cap effect – the tendency for smaller stocks to outperform large-cap stocks – is also a well-known tenet of modern finance. As such, it has been studied by academics and practitioners alike for decades. The higher performance of small caps comes at the cost of higher volatility. Overall superior performance may be due to exceptional returns from a few outliers rather than from smaller companies as a whole. And small caps can underperform broader markets for years at a time. But if you’re looking for better performance over the long term, small-cap stocks are the way to go. Invest in small caps by, say, ranking them by revenues, and you have the basis for some impressive outperformance. The RevenueShares Small Cap ETF (NYSEARCA: RWJ ) is comprised of the same securities as the S&P Small Cap 600 but weights the stocks according to top-line revenue instead of market capitalization. Morningstar ranks it a four-star fund. It is down 4.80% year to date. Momentum Momentum investing is a dirty word for fundamental investors schooled in Ben Graham’s number-crunching culture of fundamental analysis. Somehow it reeks of short-termism and superficiality of technical analysis. It also seems to question the validity of the efficient market hypothesis. That may well be true. But in the short run, recent performance tends to persist. Winners over the past six to 12 months tend to continue to outperform over the course of the next several months while those that have underperformed often continue to lag. And the momentum effect hasn’t gone away even though it was first published in academic literature in 1993. Momentum’s outperformance in 2015 is particularly impressive. The iShares MSCI USA Momentum Factor Index ETF (NYSEARCA: MTUM ) tracks the MSCI USA Momentum Index and consists of stocks exhibiting relatively higher momentum characteristics than the traditional market-capitalization-weighted parent index, the MSCI USA Index. It is up 5.61% year to date. Low volatility Perhaps the most puzzling among the major factors behind outperformance is the claim that stocks with less volatile share prices seem to deliver higher long-term returns than more volatile ones. This flies in the face of both accepted finance theory and common sense – that more volatile (risky) stocks should deliver higher returns. Still, analysts and academics have confirmed that the effect is real and applies in markets around the world. This has yet to be confirmed in practice, however, as low-volatility ETFs in the U.S. market have yet to exhibit much of any kind of outperformance versus the S&P 500. The iShares MSCI USA Minimum Volatility ETF (NYSEARCA: USMV ) seeks the investment results of an index composed of U.S. equities that, in the aggregate, have lower volatility characteristics relative to the broader U.S. equity market. It is up 2.79% year to date. Quality Perhaps the least surprising of these factors is that “high-quality” stocks seem to do better than lower-quality ones. Quality is measured by factors such as low levels of debt, stability of earnings and high returns on equity. Strong competitive advantages make these firms slightly less sensitive to the business cycle than lower-quality firms. In a recent study, “Quality Minus Junk,” Cliff Asness of AQR found that stocks with high and growing profitability, high payout rates and low market volatility and fundamental risk historically outperformed their less-advantaged counterparts. High-quality stocks have, indeed, outperformed the S&P 500 over the past five years, if only slightly. And it may be even more surprising that they have outperformed the ultimate high-quality stock investors’ vehicle, Berkshire Hathaway (NYSE: BRK.B ) (NYSE: BRK.A ), by close to 2 to 1. The iShares MSCI USA Quality Factor ETF (NYSEARCA: QUAL ) seeks to track the investment results of the MSCI USA Sector Neutral Quality Index composed of U.S. large- and mid-capitalization stocks with quality characteristics as identified through certain fundamental metrics. It is up 2.22% year to date. Thanks to the vagaries of the markets, not all of these strategies will outperform each and every year. As a group, some strategies may underperform for years. But studies suggest that in the long run, stocks with these five factors have comfortably and consistently beaten the broader market and in different stock markets around the world. So what’s the secret behind the success of factor investing? On the one hand, higher returns may come from taking on higher risk. Studies have shown that value, momentum and size have all beaten the standard MSCI World index, but at the cost of taking on slightly more risk. Indeed, that’s also where you see the biggest outperformance. But with other factors, that explanation doesn’t hold. Quality has delivered outstanding returns at lower volatility than the wider market. Quality companies are intuitively less risky: they are more likely to survive economic downturns. The same applies to low-volatility stocks. So lower risk should yield lower returns. The secret may lie in the world of behavioral finance and Mr. Market’s mood swings. Investors may prefer the excitement of a new and novel story. That’s why they undervalue both quality companies and low-volatility stocks. They just seem dull. Whatever the reason, factor investing today offers investors a reasonable chance to earn market-beating returns with little effort. But free lunches in investing don’t last, especially as such simple strategies keep on winning. Excess returns eventually will vanish. Investors will drive up the valuations of these stocks to the point where they can no longer outperform. But for now, the size of factor funds makes them too small to matter. Until then, enjoy your free lunch.

Which Low Volatility ETFs Will Protect Your Portfolio?

Stock markets world-wide have been in turmoil over the past few weeks. While panic selling was initially triggered by currency devaluation in China, anemic global growth and uncertainty related to rate hike by the Fed, have added to investors’ concerns. Low-volatility ETFs are designed for investors who want exposure to stocks but do not want to take on too much risk. These products have become extremely popular over the past few years since historical performance revealed that low-risk stocks have rewarded investors with higher return than high-risk stocks as well as the broader markets over long-term, in all the markets studied. This outperformance suggested that that investors actually misprice risk. Did these low-volatility ETFs deliver on their promises during the past month, which by some measures, has been the one of the most volatile on record. Now may be a good time to revisit these products and see whether they deserve a place in investors’ portfolios. And, while a number of products are available to investors, there are significant differences in their strategies and investors should understand them properly before investing. There are more than 30 low- and minimum-volatility ETFs available to investors, focused on different styles (large/mid/small cap), geographical regions (U.S./Developed/Emerging/Europe/Japan) and strategies (low/minimum volatility/volatility weighted/risk weighted etc.). In this article, we focus on the two ultra-popular U.S. large cap low volatility ETFs – the iShares MSCI USA Minimum Volatility ETF (NYSEARCA: USMV ) and the PowerShares S&P 500 Low Volatility Portfolio ETF (NYSEARCA: SPLV ) . Here’s a snap shot of these two ETFs and the SPDR S&P 500 Trust ETF (NYSEARCA: SPY ). Yield Expense Ratio Beta Standard Deviation (Annualized)* 1 Month Return 1 Year Return Upside Capture Ratio (3 Y)** Downside Capture Ratio (3 Y)** USMV 1.96% 0.15% 0.78 10.44% -5.99% 6.27% 84.38 71.72 SPLV 2.50% 0.25% 0.80 11.55% -6.45% 4.71% 80.25 72.81 SPY 2.10% 0.09% 1.00 12.37% -6.93% -0.10% 99.75 100.76 *Calculated from daily price returns for the past 3 years **Source: Morningstar Approach to Managing Volatility SPLV holds 100 stocks from the S&P 500 Index with lowest realized volatility over the past 12 months, which means SPLV takes into account volatility of individual stocks to arrive at the low- volatility portfolio. The index is rebalanced quarterly. USMV holds 163 stocks that, in the aggregate, have lower volatility than the broader U.S. stock market. The underlying index uses Barra Optimizer to build a portfolio with the lowest absolute volatility, taking into account, variances of individual stocks as well as covariance of all stocks, with a certain set of constraints. In simple words, this ETF uses correlations between stocks in addition to volatility of individual stocks in arriving at the portfolio. The index is rebalanced semi-annually. Performance Did low volatility ETFs provide some comfort to the portfolio during wild market swings? It seems that they did deliver on their promises. During the one month period ended September 11, when the market was very unstable in the wake of China growth concerns, low volatility ETFs fell less than the broader market. And over the past one year, when the broader market returns were almost flat, both these ETFs had much better performance. Further, both the ETFs had lower volatility compared to the broader market. Looking at risk and returns, USMV had better performance compared with SPLV. One of the reasons is USMV’s significantly higher allocation to Healthcare-which has been the best performing sector among all S&P sectors over the past few years. Over the past three years, USMV and SPLV had upside capture ratios of 84.38% and 80.25% and downside capture ratios of 71.72% and 72.81% respectively. These ratios show how much these ETFs gained and lost compared to the S&P 500 index, during periods of market strength and weakness. So, when the market was rallying, USMV was able to capture 84.38% of the upside but when the market went downhill, its losses were limited to 71.72% of the broader market’s decline. In simpler words, with low volatility strategies investors sacrifice some upside but protect themselves from a lot of downside. Preparing for Higher Rates While the Fed has been priming the markets for its first rate hike in almost a decade, it now appears that they may keep the monetary policy unchanged this week, in view of ongoing turmoil in global markets. Investors, however, should be prepared for higher rates now since with improving labor markets, the Fed may not hold off a rate hike for a long time. They should keep an eye on their allocations to rate sensitive sectors. Locking at the interest rate sensitivity of the two products, both are currently largely focused on sectors that tend to perform well in rising rates environments and have rather low exposure to Utilities and Telecom sectors that are quite rate sensitive. SPLV has 35% of assets invested in Financials, 15% in Industrials and 11% in Healthcare. However, SPLV’s 22% allocation to Consumer Staples may hurt its performance when rates rise. USMV has invested 20% of its asset base in Healthcare, 18% in Financials and 15% in Information Technology sectors. For investors concerned about rising rates, PowerShares recently launched the PowerShares S&P 500 ex-Rate Sensitive Low Volatility Portfolio (NYSEARCA: XRLV ) , which is worth a look. This ETF holds 100 stocks from the S&P 500 index with low volatility characteristics, and removes stocks that historically have performed poorly in rising interest rate environments. The Bottom-Line Looking at the two ultra popular ETFs in the space, it appears that USMV has beaten SPLV, with higher returns and lower volatility. Further, USMV is cheaper than SPLV. Overall, both ETFs are effective tools for reducing overall portfolio risk and improving risk-adjusted performance over longer term. At the same time, investors should remember that these strategies underperform in strong bull markets. Link to the original post on Zacks.com