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Investing In A Stock Split ETF: 2 Is Better Than 1

How can you make money even in a market that’s gone sideways for most of the year, especially the last few months? One answer: invest in a cutting edge ETF that’s designed to stay “ahead” of the market, including one that’s been outperforming the market by a healthy margin this year. The USCF Stock Split Index Fund (NYSEARCA: TOFR ), pronounced “Two Fer”, is the very first ETF investing exclusively in stocks that split. On April 19, Barron’s and Lipper reported TOFR was up 5.62% year to date or more than five times higher than the rise of its category (1.06%) this year and 2.28 times more than the S&P 500’s 2.47% increase. And on May 6, investors who had invested in TOFR at the beginning of the year would have seen returns that were about four times better (4.03 times to be exact) than if they had invested the same money in the S&P 500; TOFR was up 4.31% vs.1.07% for the S&P 500, according to Barron’s and Lipper. It also was running almost five times better than its category, which was up just .88% this year. TOFR is currently in the #1 quintile rank YTD and in the top 2% in its category, according to Lipper . How does TOFR compare with other ETFs? While the fund has slightly lagged the Vanguard Dividend Appreciation ETF (NYSEARCA: VIG ), which was recently up 4.76% this year, it’s been beating the SPDR S&P 500 ETF Trust (NYSEARCA: SPY ) YTD by a healthy, four to one margin (4.31% vs roughly 1.00%). Since the fund’s inception in September 2014, its numbers do not look quite as impressive. TOFR had one really bad quarter (the fourth quarter of 2015), during which much of its previous performance was given back. TOFR’s 1.02% move higher trailed the S&P’s 7.04% gain by about 6 percentage points in that three month period. But since then, it’s bounced back well. In fact, if you take the cumulative return since TOFR’s inception, it’s up 10.89% vs. the S&P’s 7.66%. Like most investments, TOFR may underperform at times. However, over the long haul, the 20 year track record of the newsletter it’s based on is what makes TOFR compelling: it was recently up 719% vs. 185% for the Dow and 191% for the S&P 500 — a difference of nearly 4-1 over both the Dow and S&P 500 (3.89-1 to be exact for the Dow and 3.76-1 for the S&P 500). TOFR is part of USCF (United States Commodity Funds LLC) Investments, which manages nine EF funds with total recent assets of approximately $5 billion. (Its ETFs include the first commodity ETF based on crude oil launched in the U.S., which is the fourth commodity ETF of any kind launched in the U.S. USCF also manages the first natural gas based ETF, which is the most actively traded natural gas commodity ETF in the U.S.) TOFR’s concept is simple. It’s like someone asking: would you rather have one big scoop of ice cream or two smaller ones? Well, most people would feel that two scoops are better than one, especially if those two scoops somehow had the potential to grow even bigger and at a faster rate than the big one. It turns out that, according to TOFR principal and portfolio manager Andy Ngim, two shares are usually better than one. In fact, analysis shows that stocks usually tend to do well for 24-36 months after a company announces a split, so TOFR holds them for 30 months, which is smack dab in the middle of the 24-36 month period. An influential academic research study by David Ikenberry at Rice University, discussed in the April 22, 1996, issue of Forbes, reported that there is a measurable difference in a stock’s performance for up to three years after it splits 2 for 1 as opposed to those stocks that have not split. TOFR consists of 30 stocks that are equally weighted. “Each holding accounts for 3.33% of our portfolio,” says Ngim. The bottom line: no matter how big the stock is — Apple (NASDAQ: AAPL ) is included in TOFR and so is Nike (NYSE: NKE ), which split in December 2015 — the starting weighting is the same. “It’s a well-diversified group, covering small, mid-cap, and large-cap stocks,” adds Ngim. “There’s a value edge to the stocks comprising TOFR. A lot them pay dividends, so it builds in defensiveness.” A new stock is usually added every month to TOFR’s portfolio, which tracks newsletter publisher Neil MacNeale’s 2 For 1 Index. The popular newsletter has been published since August 1996. But what if there aren’t enough great two-for-one stock split candidates for MacNeale to consider? Since TOFR was launched, that’s only happened twice, including last month. I asked Ngim what happened during those times. “We follow Neil’s listings, so that’s what we did,” he explains. “During those two months, there were no changes to the portfolio, other than rebalancing all the holdings back to equal weight.” What about the future of stock splits? Does continued investing in them look rosey? “Like any investment, you’re going to get a surprise once in a while,” tells Ngim. “But many any of those surprises have been to the upside. And an upward trend has been continuing since 1996.” According to Ngim, the two-for-one remains the most common type of split, though some firms have been trying unconventional splits. “For example, Google recently did a nontraditional style split,” he says. “Newer companies seem to be more open in exploring nonconventional kinds of splits.” (In April 2014, when Google split its stock two for one, it also split into two companies, Google and its new parent, Alphabet. If Google had done a typical split, the would have doubled the voting power of their A shares (NASDAQ: GOOGL ) relative to their B shares, which would have diluted the founders’ voting power. The founders, such as Larry Page and Sergey Brin, and insiders, like executive chairman Eric Schmidt, who owned most of the Class B stock, didn’t want that, so they issued a new Class C (NASDAQ: GOOG ), whose shares do not have voting power.) Other firms have been waiting longer and longer to announce their splits. And some stocks never split, no matter how pricey they become. “For example, Berkshire Hathaway (NYSE: BRK.A ) hasn’t split,” says Ngim. The stock recently closed at a whopping $215,880 per share. 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.

Smart Beta And The Portfolio Construction Puzzle

The portfolio puzzle The Rubik’s cube has become a popular metaphor for the marketing teams of ETF providers. With good reason. For each client there’s a portfolio construction puzzle to be solved with building blocks, representing geographies, sectors, asset classes, factors and styles. There has been rapid expansion from providers of ETFs tracking main-market indices, with the largest institutional providers capturing the lion’s share of flows, owing to their ability to deliver on four key ETF governance criteria — consistency, liquidity, transparency and, of course, price. This means that ETFs for main market cap-weighted indices are increasingly commoditized. After all, there doesn’t seem to be anything overly smart about replicating market beta, other than the smartness of saving on fees relative to ‘closet-tracker’ active funds. Traditional cap-weighted index investing is a preference: either out of philosophy or necessity. Innovation Means Smarter? Hence R&D of institutional investors, index providers and ETF manufacturers alike has focused more on “smart beta.” This has triggered a slew of innovation – both superficial and substantive. At a superficial end, age-old alternative weighting strategies (e.g. value indices that screen stocks for low book values, or dividend-weighted indices) have been re-branded as being “smart.” In these cases, for “smart” read “non-market-cap weighted.” In fairness, this rebranding is part of broadening of alternative weighting strategies that are factor-based. More substantively, research programs such as EDHEC-Risk Institute’s Scientific Beta have been instrumental in promoting fresh thinking in the field of both factor-based and risk-based smart beta strategies. Factor-Based Approach As a result, providers are focusing on making building blocks smarter. Instead of relying on the ‘traditional’ factor of market capitalization for index inclusion, smart beta indices (and related ETFs) look at alternative factors: book value, dividend yield, volatility, for example. In that respect, the FTSE Russell 1000 Value Index launched in 1987 is probably the oldest factor index on the block. More recent factor indices are stylistic: Both iShares (Oct-14) and Vanguard (Dec-15) have launched global equity factor ETFs focusing on liquidity, minimum volatility, momentum and value. The sophistication of factor-based index construction will continue to increase with the increase in data availability and computing power. Risk-Based Approach Portfolio strategists meanwhile can apply quantitative rules-based approaches to portfolio construction, creating static or dynamic asset allocation strategies from a growing universe of both cap-weighted and alternatively weighted index tracking funds. These strategies — such as maximum Sharpe, minimum variance, equal risk contribution and maximum deconcentration — offer an alternative to the standard but troubled single period mean variance optimization (MVO) approach. MVO’s limitations The single-period MVO approach remains the traditional bedrock of very long-run investing in normal market conditions where the sequence of returns does not matter. However it runs into difficulty in the short-run when markets are non-normal and sequence of returns matters a lot. So unless you are a large endowment with an infinite time horizon, or perhaps can afford to invest for yourself and your family without ever needing to withdraw any capital, relying entirely on the MVO approach for asset allocation gives false comfort. For cases where there are constraints that challenge the MVO model – due to multiple or limited time horizons, expected capital withdrawals, risk budgets, and unstable risk/return/correlation profiles of asset classes (collectively known as real life) — portfolio construction requires a smarter, more adaptive approach that observes, isolates and captures the reward from shifting risk premia over time. Risk-based portfolio strategies attempt to achieve this and are designed to offer a liquid alternative approach to investing that is uncorrelated with traditional single-period MVO strategies. What’s the Problem to Solve? Whether assessing factor-based ETFs or risk-based ETF strategies, at best these new developments all seem very smart. At worst it’s just a bit different. However, as ETFs get smarter and the strategies that combine them become more sophisticated, there’s a risk that the key question in all of this gets lost in an incomprehensible barrage of Greek. The key question for portfolio managers nonetheless remains the same. What client outcome am I targeting? What client need am I trying to solve? For portfolio strategy, whether using a discretionary manager that relies on judgment, or a systematic rules-based approach that relies on quantitative inputs, the key client considerations remain return objective, time horizon, capacity for loss and diversification across asset classes and/or risk premia. Broadening the Toolkit A portfolio strategy has little meaning without an objective that focuses on client outcomes. Factor-based ETFs and risk-based ETF portfolio strategies offer an alternative or additional set of tools to help deliver on those outcomes, in a way that is systematic, liquid and efficient. 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. Additional disclosure: This article has been prepared for research purposes only.

Smartening Watson: IBM Supercomputer Bolsters Cybersecurity Job Gap

Skynet isn’t becoming self-aware, but IBM ‘s ( IBM ) supercomputer, Watson, aims to become more aware … of cybersecurity attacks. To combat a growing number of Black Hats and a shortfall in their counterpart White Hats — the company says forecasts see as many as 1.5 million unfilled cybersecurity positions by 2020 — IBM was set early Tuesday to announce a year-long project with eight universities to smarten Watson. Watson is already filtering Big Data to bolster cancer research, create learning tools and improve business operations. The next frontier? Teaching Watson to scour the 80% of unstructured online data to suss out cyberthreats. IBM’s security operations center (SOC) already receives 20 billion pieces of raw data per day detailing potential cyber mischief, says Caleb Barlow, IBM Security vice president. On average, companies spend $1.3 billion annually, or 21,000 hours, chasing false positives. “Some can be mundane, like a user was locked out after 10 password tries,” Barlow told IBD. “Or, we could get data about an ATP (advanced threat protection) attacker. … It’s not a matter of looking for the needle in the haystack. It’s a matter of a looking for the needle in a stack of needles.” Enter Watson On Unstructured-Data Front Watson is capable of digesting structured data, Barlow says. He likens it to a paramedic responding to a car accident. Watson can take the vitals, but it cannot look for the crack in the windshield where the victim hit his head (unstructured data). It’s the difference between analysis and insights, Barlow says. Humans can do both, but the sheer volume of data is overwhelming. “Security data is in unstructured data — blogs, wikis, articles, white papers, presentation notes,” he said. “How do we take that experiential data, data we can only get from a human and apply that to this challenge?” First, IBM will team up with students from California State Polytechnic University, Pennsylvania State University, Massachusetts Institute of Technology, New York University, University of Maryland, University of New Brunswick, University of Ottawa and University of Waterloo. There will be 200 IBM staff members and students working on the project. “The partnership between IBM and Penn State is an ideal opportunity for our students to experience the kinds of bleeding edge knowledge management that will drive technology in the next century,” Penn State professor Patrick McDaniel said via email. “At the same time, it is a wonderful chance for Penn State to showcase its exceptional student engineers.” Under instruction from IBM experts, the students will process 15,000 documents per month including threat intelligence reports, cybercrime strategies and threat databases. Watson will slowly begin to learn that unstructured data. It’s almost childlike, Barlow says. “You have to sit down with Watson and explain the language,” he said. “Then, we go through, ‘Here, you were right,’ or ‘Here, you were wrong.’” The difference is that Watson won’t forget, he says. Still, a human analyst remains necessary to respond to developing attacks — whether that’s blocking the hacker, watching malware inside the network or plugging holes. “Watson is not replacing the analyst,” he said. “But if I can get Watson to ask all those questions and prioritize that, I can be asking millions of questions (to suss out legitimate cyberattacks) I would not be able to ask otherwise.” Demand Outstrips New Talent That’s more valuable than finding the needle, Barlow says. More than 10,000 security research papers and 60,000 security blogs are published each year and each month, respectively. The National Vulnerability Database has received reports of 75,000-plus software vulnerabilities. Coupled with that, varying reports place the current paucity in cybersecurity skilled employees at 200,000 to 1 million. It was a huge topic at the RSA Conference in February in San Francisco. But it’s not that students aren’t interested, Barlow says. “Universities have shown me their growth statistic,” he said. “It’s a hockey stick. Their challenge is, they are running out of facility space.” The problem is immediacy. Twenty years ago, cybersecurity wasn’t at the forefront of IT concerns. They, today there aren’t enough skilled professionals. The chief information security officer (CISO) is newest entrant to the C-Suite. “These are not skills people have historically had,” Barlow says. “It’s IT-centric computer science skills. It requires a collision of those traditional computer science skills with forensics and investigative skills.” He added: “No matter how aggressively universities turn out new talent, they won’t be able to meet the demand.”