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The O’Shares FTSE U.S. Quality Dividend ETF: You’re Dead To Me

Summary Mr. Wonderful Kevin O’Leary recently launched a dividend focused ETF. OUSA is a smart beta ETF with screening parameters focused on Quality, Value, and Yield. Is there merit in this fund, or should Kevin go take a hike? As a frequent watcher of Shark Tank, I was intrigued to find out that dirty-rich Kevin O’Leary, self anointed “Mr. Wonderful,” had developed a dividend ETF, the O’Shares FTSE U.S. Quality Dividend ETF (NYSEARCA: OUSA ). The fund is less than a month old, with onset of trading July 14. I wanted to determine if there was merit to the fund, or whether O’Leary is just throwing chum into the water to attract some attention. Kevin O’Leary OUSA’s online materials state that the fund is correlated to the FTSE U.S. Qual/Vol/5% Capped Factor Index, which focuses on “Quality, Low Volatility, and Dividend Yield.” OUSA’s tearsheet refers us to the FTSE web site for additional information relative to how index constituent are selected and weighted within the portfolio. There one can read all about the ground rules as well as a methodology overview . There is also a fact sheet summary available, for those interested in statistical gibberish. I was unable to find a complete list of current constituents. Portfolio The fund (as of July 14) is invested in 142 companies, both large- and mid-cap, with weighted average market cap of $152 billion. The average dividend yield is 3.2 percent. Here is a list of top 10 holdings as disseminated on July 14, complete with the common misspelling of Proct”o”r and Gamble: (click to enlarge) Images sourced from Oshares.com There was also a breakdown of industry exposure: (click to enlarge) Let’s compare the holdings to the SPDR S&P 500 Trust ETF (NYSEARCA: SPY ) ….and sector weightings…. Source: spdrs.com OUSA vs. SPY The funds share 6 of their top 10 holdings with one another. The main difference is in concentration. OUSA concentrates 38% of assets in the top 10 while SPY has about 17% of assets in the top 10. O’Leary’s fund is considered “smart beta” since it screens on basis of “Quality, Value, & Yield.” SPY is a plain passive index that we generally know the constituents of at all times. And while there is sector diversification, I don’t think I would characterize OUSA’s as “index hugging” in nature. For instance, SPY contains 17% exposure to financials. Presumably, according to graphs above, OUSA has less than 4% exposure. Generally when ETFs have somewhat similar allocations, the trump card could be the fee. Currently SPY charges .0945% annually while OUSA’s net expense is .48%, with a waiver in place until July of 2018. Since O’Leary is advertising a 3.2% yield on the underlying holdings, we can probably guess that it will actually pay out somewhere between 2.5 and 2.7% on a full year run rate. SPY sits somewhere around 2.1 percent. Let’s Make A Deal! If I were able to switch positions and grill O’Leary like he does the entrepreneurs that stand in front of his majesty, I’d hit him hard on the fee, because like him, I’m not overpaying and want good ROI. I’d inquire as to what makes this FTSE methodology so superior to a passive index like SPY. He’d probably respond that investors should only own stocks that pay dividends, which his fund does. About 1 in 5 S&P 500 stocks don’t. He’d probably also bring up the point that his fund concentrates in quality and low volatility, providing opportunity to not only realize a yield in excess of SPY, but perhaps total return as well. Plus one could also sleep better at night with OUSA than SPY. Maybe he’d have a point. Since I wouldn’t characterize this fund as index hugging in nature, maybe it has a good shot of providing portfolio alpha. But I’d remind him 75% of active fund managers can’t beat an index. Further, OUSA has no track record of success and doesn’t appear to be pulling in assets by the boatload as of yet. Perusing the top 10 holdings once again, I’d remind him that many of them have really stunk up the joint ( Exxon Mobil Corporation (NYSE: XOM ), Chevron Corporation (NYSE: CVX ), The Procter & Gamble Company ( PG), Apple Inc. ( AAPL)) over the less than a month the fund has been public. Of course he’d then remind me that the fund hasn’t fared any worse than SPY over the same time – which is basically true. But, I tell him I’d want a better deal to be a buyer. “You’re no better than SPY,” I’d tell him. Then I’d tell Mr. Wonderful to drop his fee, at which point he’d say, “You’re no better than an Italian hit man, Aloisi” and turn down the offer. As he turns his back to me I’d utter, “O’Leary, you and your OUSA are dead to me!” Disclosure: I am/we are long AAPL,XOM. (More…) I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article. Additional disclosure: Disclaimer: The above should not be considered or construed as individualized or specific investment advice. Do your own research and consult a professional, if necessary, before making investment decisions.

Low Volatility And Momentum: Doubling The Market Return

Summary This series offers an expansive look at the Low Volatility Anomaly, or why lower risk stocks have historically produced stronger risk-adjusted returns than higher risk stocks or the broader market. While low volatility strategies are often an appropriate long-term buy-and-hold strategy, this article offers a strategy that uses a momentum signal to tilt towards higher-beta securities selectively. The alpha-generative strategy combines two market anomalies – Low Volatility and Momentum – to produce outsized returns. In recent articles, I have been authoring a fairly extensive examination of the Low Volatility Anomaly, the tendency for low volatility assets to outpeform high beta assets over long-time intervals. A Low Volatility strategy was one of five buy-and-hold factor tilts that I described in a previous series of articles. I believe that these buy-and-hold strategies to capture structural alpha are appropriate for many in the Seeking Alpha audience, but understand that some readers are looking for strategies that can generate even higher absolute returns. This article depicts one such strategy. Long-time readers know that two of favorite topics on which to author have been Low Volatility and Momentum strategies. This article combines these two strategies to produce a return profile that as the title of the article suggests has more than doubled the return of the S&P 500 over the past quarter-century. Before we delve into this strategy, we should first discuss the two components that drive this tremendous performance. Low Volatility Anomaly Regular readers know that I am currently authoring a multi-part series on the Low Volatility Anomaly. These articles include an introduction to the concept, a theoretical underpinning for the anomaly , cognitive and market structure factors that contribute to its long-run performance, and empirical evidence that demonstrates the outperformance of low volatility strategies across markets, geographies and long time intervals. In past articles, I have depicted the relative outperformance of Low Volatility strategies using the graph below which shows the cumulative total return profile (including reinvested dividends) of the S&P 500 (NYSEARCA: SPY ), the S&P 500 Low Volatility Index (NYSEARCA: SPLV ), and the S&P 500 High Beta Index (NYSEARCA: SPHB ) over the past twenty five years. The volatility-tilted indices are comprised of the one-hundred lowest (highest) volatility constituents of the S&P 500 based on daily price variability over the trailing one year, rebalanced quarterly, and weighted by inverse (direct) volatility. Source: Standard and Poor’s; Bloomberg The Low Volatility strategy contributes an important base component to this strategy that would have doubled the return of the market over the past twenty-five years, but we also need an element that pushes the strategy into riskier parts of the market when we can get paid for this tilt in the form of higher returns. Momentum Like the low volatility strategy, momentum strategies have been alpha-generative over long time intervals and across markets. Consistent with Jegadeesh and Titman (1993), which documented momentum in stock prices that have outperformed in the recent past over short forward intervals, the efficacy of momentum strategies have been widely documented. Academic literature has described excess returns generated by momentum strategies in foreign stocks ( Fama and French 2011 ), multiple asset classes ( Schleifer and Summers 1990 ), commodities ( Gorton, Hayashi and Rouwenhorst 2008 ), and my own studies on momentum in fixed income strategies and more recently the oil market . Academic literature offers competing theories on why momentum has generated alpha over long time intervals across markets and geographies. Proponents of market efficiency suggest that momentum is a unique risk premium, and the long-run profitability of these strategies is compensation for this unique systematic risk factor ( Carhart 1997 ). Behaviorists offer multiple competing explanations. In my previous series, I referenced both Lottery Preferences and Overconfidence as potential justifications. Studies contend that markets under-react to new information ( Hong and Stein 1999 ), which allows for the autocorrelations found in return series. Other behavioral economists contend that the disposition effect, or the tendency for investors to pocket gains and avoid losses, makes investors prone to sell winners early and hold onto losers too long ( Frazzini 2006 ), which could be further amplified by a “bandwagon effect” that leads investors to favor stocks with recent outperformance. Blitz, Falkenstein and Van Vliet (2013) offer an expansive summary of these explanations. The Strategy I am of the opinion that low volatility stocks should be a part of investors’ longer-term strategic asset allocation given that class of stocks’ historical higher average returns and lower variability of returns. In ” Making Buffett’s Alpha Your Own ,” I described academic research ( Frazzini, Kabiller, Pederson 2013 ) that broke down the Oracle of Omaha’s tremendous track record at Berkshire Hathaway ( BRK.A , BRK.B ) into two components – capturing the Low Volatility Anomaly and the application of leverage. If an allocation to low volatility stocks should be part of your long-term strategic asset allocation, then an allocation to high beta stocks must be done tactically with a short-term focus given that class of stocks’ lower long-run average returns and higher variability of returns. This view is borne out of the data underpinning the chart above. However, a temporary allocation to the High Beta Index in sharply rising markets can further boost performance. The High Beta stock index has typically outperformed in post-recession recoveries. How do we combine Low Volatility and Momentum? A quarterly switching strategy between the Low Volatility Index and the High Beta Index, which buys the leg that has outperformed over the trailing quarter and holds that leg forward for the subsequent quarter, would have produced the return profile seen below since 1990, easily besting the S&P 500 with lower return volatility. For a pictorial demonstration of the leg that would be chosen by the Momentum strategy, please see the exhibit at the end of the article. It is a very simple heuristic. The Momentum strategy buys either Low Vol or High Beta stocks based on the index that outperformed in the trailing quarter and holds that index for the subsequent quarter before re-examining the allocation once again. The results are striking. (click to enlarge) From the cumulative return graph above, one can see that $1 invested in the S&P 500 would have produced $9.04 at the end of the period (including reinvested dividends) whereas $1 invested in the Momentum portfolio would have produced $19.90. These are gross index returns and do not consider taxes. Readers envisioning employing momentum strategies should utilize tax-deferred accounts. Summary statistics of the trade are captured below: (click to enlarge) The simple quarterly switching momentum strategy would have produced a 13% return per annum over the long sample period. This 3.6% outperformance relative to the S&P 500 led to the cumulative doubling of the market returns over time. Note that while the Momentum strategy is riskier than the broad market as measured by the variability of quarterly returns, practitioners of this strategy would have been rewarded with correspondingly higher returns for this incremental risk. While I contend that a long-run, buy-and-hold tilt towards lower volatility equity is probably appropriate for many Seeking Alpha readers, this article demonstrates a momentum-based switching strategy that can help inform investors when to pivot towards higher beta stocks when they offer returns commensurate with their higher risk. Disclaimer My articles may contain statements and projections that are forward-looking in nature, and therefore inherently subject to numerous risks, uncertainties and assumptions. While my articles focus on generating long-term risk-adjusted returns, investment decisions necessarily involve the risk of loss of principal. Individual investor circumstances vary significantly, and information gleaned from my articles should be applied to your own unique investment situation, objectives, risk tolerance, and investment horizon. Exhibit: Returns of Low Vol, High Beta, Momentum, & Market (click to enlarge) Disclosure: I am/we are long SPLV, SPHB. (More…) I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

It Is Not Possible That Valuations Matter Only At The Margins

By Rob Bennett You will often hear people say that valuations matter only at the margins. That is, valuations matter when prices are very high and when they are very low. Outside of that, it is okay to ignore the effect of valuations. I see this as dangerous thinking. My view is that either valuations matter or they do not. If they matter, they always matter. If they don’t matter, they never do. I am not able to make sense of the idea that valuations matter in some circumstances, but not in others. The first point that needs to be made is that there is a practical sense in which the claim that valuations only matter at the margins is true. Stocks generally offer a significantly better long-term value proposition than other asset classes. So, when stocks are priced at only a bit more than their fair value price, they remain a good investing choice. In a practical sense, then, a high stock allocation makes sense until the overvaluation reaches such a point that the mispricing is extreme. The problem is that there is no one valuation level at which stocks are transformed from a good choice to a bad one. Stocks are a little less appealing when the P/E10 level is 18 than they are when the P/E10 level is 15. And they are, of course, even less appealing when the P/E10 level is 21. And then even less appealing when the P/E10 level is 24. And even less appealing when the P/E10 level is 27. What is the investor to do? When does he lower his stock allocation, and by how much? It’s tricky. Stocks became a bit less appealing when the P/E10 level rose from 15 to 18, and then again when it moved from 18 to 21, and from 21 to 24, and from 24 to 27. But as the PE10 level moved from 15 to 27, the feedback being received by the investor was all positive. The risk of owning stocks was becoming greater. The investor should have been lowering his stock allocation in an effort to keep his risk profile constant. But at the moment when the P/E10 value reached the insane level of 27, the investor who failed to lower his stock allocation as the P/E10 value moved to 18, and then to 21, and then to 24, and then to 27 was feeling good about those decisions. So he was left disinclined to changing it much, even when prices had gone to “the margins” of 27 and above. What Jack Bogle says about this is that investors should not change their stock allocations in response to price increases. But if they feel that they absolutely must change their allocation at the margins, they should not lower them by more than 15 percent. Bogle has never explained how he came up with the 15 percent figure. I use the historical return data as my guide. The data shows that stocks are likely to offer an amazing long-term return when prices are at low levels or at fair value levels, and then the long-term return drops and drops as prices continue to rise. The data shows that most investors should have been going with a stock allocation of about 80 percent in the early 1990s and about 20 percent in the late 1990s and early 2000s. That’s a change not of 15 percentage points, but of 60 percentage points. Bogle’s recommendation is off by 400 percent, according to the 145 years of historical data available to us today. How many people know that? People don’t know how dangerous it is to own stocks when they are selling at high valuation levels, because most advisors buy into the idea that valuations matter only at the margins. If you only consider valuations at the margins, you are missing out on most of the story of how the mispricing of stocks derails investor retirement plans. Stocks don’t suddenly become dangerous when the P/E10 value hits 27. They are virtually risk-free when the P/E10 value is 15. Then, they become more risky at 18. And more risky at 21. And more risky at 24. And more risky at 27. Unfortunately, the growing risk is a silent one. Stocks are far more risky when the P/E10 value is 21 than they are when it is 15. But years can go by before that risk evidences itself in portfolio destruction. Valuation risk plays out the way that cancer risk plays out for people who smoke three packs of cigarettes each day. Heavy smokers often “get away” with their behavior for decades before they contract a disease that kills them. However, the deep reality is different from the surface one. Someone who smokes three packs of cigarettes each day from age 16 to age 66 and then dies at age 67 from lung cancer was not avoiding the risk of smoking for 50 years; he was avoiding only the practical consequences of taking on a risk that would one day cause him to pay a terrible price. Disclosure: None.