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Business Tech Invades CES
January 08, 2019 12:01 AM Eastern Standard Time
“The basic computational unit in quantum computing is a qubit, short for quantum bit. While a classical bit is always 0 or 1, when a qubit is operating it can take on many other additional values. This is increased exponentially, with the potential computational power doubling each time you add an additional qubit through entanglement. “
IBM CEO Ginni Rometty, who will be talking about “what’s next” for data and computing. She also will unveil the new IBM Q System One , billed as “the first fully integrated quantum computing system for commercial use.” Because it has to operate at a temperature “1,000 times colder than outer space,” in Rometty’s words, it’s not really ready for the average smart home. But it does open the door to experimentation at cutting-edge research facilities. On stage with Rometty this morning will be Vijay Swarup, who heads R&D at ExxonMobil and is using the IBM Quantum computer for global oil discovery projects.
ExxonMobil said today that it has signed a partnership agreement with IBM to advance the potential use of quantum computing in developing next-generation energy and manufacturing technologies. The new partnership was formally announced during the 2019 Consumer Electronics Show (CES) in Las Vegas.
LAS VEGAS–(BUSINESS WIRE)–
- Strategic commitment to advance joint research into quantum computing for energy
- ExxonMobil becomes the first energy company to join the IBM Q Network
- Technology could further enhance ExxonMobil’s own research and development capabilities
As part of the agreement, ExxonMobil becomes the first energy company to join the IBM Q Network, a worldwide community of Fortune 500 companies, startups, academic institutions and national research labs working to advance quantum computing and explore practical applications for science and business.
“The scale and complexity of many challenges we face in our business surpass the limits of today’s traditional computers,” said Vijay Swarup, vice president of research and development for ExxonMobil Research and Engineering Company. “Quantum computing can potentially provide us with capabilities to simulate nature and chemistry that we’ve never had before. As we continue our own research and development efforts in the areas of energy and chemical manufacturing, our agreement with IBM will allow us to expand our knowledge base and potentially apply new solutions in computing to further advance those efforts.”
Advances in quantum computing could provide ExxonMobil with an ability to address computationally challenging problems across a variety of applications, including the potential to optimize a country’s power grid, and perform more predictive environmental modeling and highly accurate quantum chemistry calculations to enable discovery of new materials for more efficient carbon capture.
“The advancement of new breakthroughs, coupled with the creative application of current technologies available to us from outside the energy sector, will be critical in addressing the dual challenge of producing energy to fuel economies and meeting consumers’ needs while managing the risks of climate change,” Swarup said. “Much of the success in our own ingenuity is facilitated by the innovation of others outside our industry, from three-dimensional printing to quantum computing. The many partnerships we lead or participate in around the world provide us with opportunities to exchange ideas and collaborate, applying our own unique experiences, knowledge and strengths toward a potentially successful breakthrough in lower-emission energy production or a more efficient manufacturing process.”
ExxonMobil’s partnership with IBM expands the company’s collaborative efforts with other companies and academic institutions that are focused on developing an array of new energy technologies, improving energy efficiency and reducing greenhouse gas emissions. The company currently works with about 80 universities in the United States, Europe and Asia to explore next-generation energy technologies.
About IBM Q
IBM Q is an industry-first initiative to build commercial universal quantum systems for business and science applications. For more information about IBM’s quantum computing efforts, please visit www.ibm.com/ibmq.
IBM Q is an industry first initiative to build universal quantum computers for business and science. Our cross-disciplinary team is developing scalable quantum systems, and potential applications for the technology we make available today. IBM Q quantum devices are accessed using Qiskit, a modular, open-source programming framework. A worldwide network of Fortune 500 companies, academic institutions, and startups use IBM Q technology and collaborate with IBM Research to advance quantum computing.
First, we would need millions and millions of extremely high quality qubits with low error rates and long coherence time for this to work. Today we have 50.
Second, there’s the bit about “faster than any known method on a classical computer.” Since we do not know an efficient way of factoring arbitrary large numbers on classical computers, this appears to be a hard problem. It’s not proved to be a hard problem. If someone next week comes up with an amazing new approach using a classical computer that factors as fast as Shor’s might, then the conjecture of it being hard is false. We just don’t know. \
The basic computational unit in quantum computing is a qubit, short for quantum bit. While a classical bit is always 0 or 1, when a qubit is operating it can take on many other additional values. This is increased exponentially, with the potential computational power doubling each time you add an additional qubit through entanglement. The qubits together with the operations you apply to them are called a circuit.
Today’s qubits are not perfect: they have small error rates and they also only exist for a certain length of time before they become chaotic. This is called the coherence time.
Because each gate, or operation, you apply to a qubit takes some time, you can only do so many operations before you reach the coherence time limit. We call the number of operations you perform the depth. The overall depth of a quantum circuit is the minimum of all the depths per qubit.
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He worked on models to help predict the movement of the Taiwanese dollar based on trade statistics and economic indicators — good experience for a future fund manager.
One Young Harvard Grad’s Quixotic
Quest to Disrupt Private Equity
By Richard Teitelbaum
Daniel Rasmussen went inside the machine and didn’t like what he saw.
Daniel Rasmussen makes trouble.
As an undergraduate at Harvard University nine years ago, one of his professors described evolution as common wisdom.
“The only people who don’t believe in Darwinian evolution are evangelicals in the Midwest,” the professor scoffed.
“Is that statement based on fact or anti-Christian bigotry?” Rasmussen asked.
The outraged professor berated Rasmussen and was restrained by a neighboring colleague, who rushed into the classroom to investigate the commotion.
This wasn’t the only professor to face Rasmussen’s blunt questions. Friends say it’s nothing personal. “He likes stirring the pot,” according to Alex Cushman, a squash partner, and former colleague.
These days Rasmussen is making trouble for another vaunted community: the private-equity industry, which he claims isn’t generating the returns that pensions, endowments, and sovereign wealth funds assume it will.
Armed with his own empirical research, plus copious studies and data, Rasmussen points out that private-equity returns are trailing public indexes of late. Their results are far more volatile than big investors believe, or the industry itself claims. And, he argues, the ability of firms like KKR & Co., Carlyle Group, and Blackstone Group to overhaul and improve efficiencies at the companies they buy — taken as an article of faith — is largely illusory. “This is, after all, the leveraged-buyout industry, and not the operational wizard-genius industry,” he says.
Rasmussen, 31, worked at Bain Capital, the elite private-equity firm, for four years. Now he warns that the industry is overpaying for companies. “Public equity is a much better exposure,” he says. To the chagrin of some, Rasmussen claims he can replicate private-equity-style returns with carefully screened public companies. In 2014, while still a graduate student at Stanford University, he started a hedge fund firm to do just that. Verdad Advisers — though tiny at $80 million and run from his living room overlooking Seattle’s Puget Sound — is posting some head-turning results.
Over the past three years through March, Class A shares of Verdad’s flagship fund returned an annualized 16.3 percent, versus 7.9 percent from the Russell 2000 Value Index. The $40 million fund holds 40 cheap, debt-ridden small-capitalization stocks from around the world. Rasmussen, following two years of research with colleagues, launched a second iteration of the private-equity replication strategy in 2017, the Verdad Japan Fund. Its Class A shares returned 22.3 percent over the nine months through March, compared to 14.8 percent for the Nikkei 225 Total Return Index.
Walking into the Harvard Club’s wood-paneled dining room in midtown Manhattan, Rasmussen cuts an imposing figure. He is 6-foot-1 and weighs 200 pounds. His dense head of curly auburn hair has been described as a Danish Afro. He and his two partners — Nick Schmitz, 35, a Rhodes Scholar, ex-Marine, and Verdad’s Washington, D.C.-based portfolio manager, and Brian Chingono, 31, a native Zimbabwean and the Boston-based research director — are all in a good mood as they settle down for coffee and iced tea. It’s been a successful day of drumming up funds. “We have a lot of investors writing small checks,” Rasmussen says. “We want a diversified investor base.”
Rasmussen’s efforts to disrupt the private-equity business that once nurtured him come as industry giants are facing major headwinds. Returns are lagging, with the Cambridge Associates US Private Equity Index trailing the Russell 2000 over the past one-, three-, and five-year periods through September. Unspent capital committed to private equity hit $962 billion last June, according to PitchBook Data, and the average deal price was 10.6 times cash flow in 2017, versus 7.7 times in 2009, says data provider LCD, a unit of S&P Global Market Intelligence.
None of this augurs well for future returns. Rasmussen has been sounding the alarm in television interviews, at conferences, and in articles, such as the recent American Affairs piece “Private Equity: Overvalued and Overrated?”
“The great postcrisis private-equity gold rush is on, fueled by cheap debt and enthusiastic investors,” he wrote in the February 20 article. “America is in the grips of a speculative frenzy.” The article argues that recent-vintage private-equity funds will likely return close to nothing — and has set Wall Street talking.
Whatever the issues facing private equity, Verdad itself has plenty of challenges. Trafficking in a limited number of small-cap value stocks almost always means serious capacity constraints. “There’s only so much money you can put to work in your best ideas,” says Alex Bryan, Morningstar’s director of passive-strategies research. An asset class like small-cap value stocks is cyclical, adding to the likelihood of sharp drawdowns. And there is potent sector risk, though Rasmussen caps industry exposure at 10 percent of assets. “A lot of the values are in real estate and financial services,” Bryan says.
The number of companies Verdad can invest in is shrinking. From 2010 to 2016 the number of listed North American, European, and Central Asian stocks declined more than 23 percent, according to the World Bank. “His investable universe halved in 20 years,” says Andrea Auerbach, head of global private investment research at Cambridge Associates. When the market for small, cheap, and leveraged stocks tanks, Verdad runs the risk that investors will flee when able. (The funds have rolling three-year lockup periods.) “The key to earning that return is that investors have to stay in with you,” Auerbach says.
Wearing a blue blazer, green patterned tie, and checked button-down shirt, Rasmussen pours a cup of coffee at the Harvard Club as diners filter into the dimly lit room. Methodically, he acknowledges, in turn, the various challenges facing Verdad. He expects to close the Verdad Leveraged Company Fund to new investors at $300 million, and the Japan Fund at $200 million.
Verdad and the strategy it is based upon are indeed volatile, a feature of the asset class. “In 2008 our Japan strategy would have had a 32 percent drawdown and the U.S. strategy would have had a 62 percent drawdown,” he says. His job is partly to educate and forewarn investors so they stay the course, as he did in March with a research note detailing the history of steep losses in leveraged equity — and providing data to warn against attempts to market time.
The firm is exceedingly unlikely to ever pose a threat to private equity. “We’re not going to be a large part of the market, ever,” he says. “If the Abu Dhabi Investment Authority wanted to deploy $20 billion, we couldn’t do that.”
Nevertheless, Rasmussen’s growing media profile and incendiary American Affairs article definitely have Wall Street taking notice. “The headline of the article is sensational and tries to scare people away from private-equity investing,” says Mark Yusko, founder of hedge fund investor Morgan Creek Capital Management, in an email. As Yusko sees it, “Public markets (particularly indexes) are far more dangerous today.” Still, Yusko has referenced Rasmussen favorably in his quarterly letters, comparing him to the fighter pilot Maverick in the movie Top Gun. Others say Rasmussen is only stating publicly what many in the high-fee business say among themselves. “There is a sense that returns are not going to be as robust as they have been in the past,” according to Colin Blaydon, a professor and director emeritus of the Center for Private Equity and Entrepreneurship at Dartmouth College’s Tuck School of Business. Blaydon says Rasmussen’s analysis ignores the pockets of opportunity that may exist for private-equity funds targeting, say, microcaps or sectors like energy. Rasmussen appreciates the back-and-forth. “What I do is very controversial, so I want to show them how it works,” he says.
Daniel Rapalye Rasmussen makes for an unlikely renegade. Raised amid power and privilege in the Georgetown neighborhood of Washington, D.C., his father, Garret Rasmussen, a prominent antitrust lawyer, was a Harvard classmate of Mitt Romney, the politician, and former Bain Capital partner. His mother, Jean, is a homemaker. All of the Rasmussen siblings excel professionally — “a package deal,” as one family friend calls them. The older brother, William, worked as a journalist before joining Brunswick Group, the high-powered public relations firm. Lisa, Dan’s younger sister, is a portfolio manager at the $2 billion Ewing Marion Kauffman Foundation in Kansas City. Robert, his younger brother, works in private equity.
It was at the elite St. Albans School that Dan Rasmussen first displayed his penchant for challenging the status quo. “He was an intellectual standout,” says Ted Eagles, chairman emeritus of the history department and a mentor to Rasmussen. At the time, classmates were routinely involved in incidents involving alcohol and cheating, he says. The school administration, engaged in a fundraising effort, ignored the incidents or doled out punishments with favoritism. In a series for the school paper, Rasmussen took the administration to task for failing to enforce the standards it promoted. School administrators pressured the paper not to publish his work. “Maybe it showed an early preference for rules-based systems rather than discretionary judgment,” Rasmussen quips.
Some St. Albans classmates shunned him. In a bathroom stall, graffiti read: “Do you want to kill Dan Rasmussen?” There were two boxes to select from, “Yes” and “No.” Within two years the head of the upper school had resigned. Eagles says he thinks Rasmussen’s series contributed. “There’s no doubt that he has remarkable integrity and he expects it of institutions to which he is loyal,” he says.
From there it was off to Harvard, second varsity lightweight crew, and more run-ins with authority, including with the professor of evolution. Before his senior year, Rasmussen landed a summer associate post at Bridgewater Associates, the world’s largest hedge fund firm. Its rules-based, quantitative investment style appealed to him. He worked on models to help predict the movement of the Taiwanese dollar based on trade statistics and economic indicators — good experience for a future fund manager. “I’ve always believed in rules that govern behavior,” says Rasmussen. “That was a seductive idea.” He also took to heart Bridgewater founder Ray Dalio’s relentless efforts to educate investors, often in person and through the firm’s daily economic note, Daily Observations.
Harvard president Drew Gilpin Faust taught Rasmussen in her weekly seminar on the U.S. Civil War, and encouraged him to embark on a book project, building on his senior thesis. The topic was an obscure chapter of pre-Civil War U.S. history — an early 19th century slave rebellion in Louisiana that was the largest of its kind, but largely ignored by historians. With few secondary sources like books or histories to work with, Rasmussen traveled the bayous of Louisiana, collecting financial documents, court transcripts, church records, and newspaper clippings. “I built a database that tracked every slave,” he says.
Rasmussen used Google Maps to assess the time required for the rebellion to spread from plantation to plantation, pulling together a gripping narrative of the doomed insurrection, which led to the deaths of more than 100 slaves. The result was American Uprising: The Untold Story of America’s Largest Slave Revolt, which received generally positive reviews. “Breathtaking,” wrote historian Henry Louis Gates Jr. in a blurb. Rasmussen graduated Harvard summa cum laude, winning the school’s top undergraduate award.
He was one of three analysts hired by Bain Capital directly out of college in 2009, the first time the firm had brought in new grads at that level. It was a fraught moment for finance. The mortgage-fueled crisis had triggered the deepest recession in generations. In addition to bankruptcies and government bailouts, doomed leveraged buyouts were groaning under impossible debt loads.
After a brief training period, Bain set Rasmussen to work.
“I loved the people I worked with,” Rasmussen says. “Bain still has that Mitt Romney culture. People are conservative, genteel — I mean that in a positive way.” During his first year, he worked on Bain’s $3 billion buyout of Worldpay, a European payment processor that was part of beleaguered Royal Bank of Scotland Group. Bain was paying eight times the company’s earnings — a crisis-era bargain, thanks to severely depressed cash flows.
Ultimately, after more than £1 billion ($1.4 billion) spent on technology and other outlays, Worldpay generated over seven times Bain’s investment, becoming one of the firm’s most successful buyouts of the decade. “The deals I worked on seemed to be doing well,” says Rasmussen. “Private equity seemed to work pretty well.”
One fateful assignment changed his view.
In 2012 he was attached to a five-person team led by Andrew Balson, a managing director. The Bain buyout vehicle started in 2006, Fund IX, was not meeting partners’ expectations. Indeed, pro forma numbers showed it returning as little as 1.1 times the money invested. Data showed the fund in the bottom third or fourth quartile by performance compared to rival funds. Balson’s team, including Rasmussen, worked for four months reviewing 1,700 transactions between 1999 and 2010. These included not only Bain’s deals but also those of its top 20 competitors. Rasmussen built the database, and Balson presented some of the results.
The good news was that Bain had a lot of positive things going for it, according to a copy of the report obtained from a private-equity investor. The firm was picking superior companies, for example. But they were in the wrong industries, either cyclical ones or those experiencing a price-multiple contraction, meaning the price at which Bain would exit was lower than expected.
Bain’s investment process was flawed, according to the report. For example, for a prospective target to pass muster, the firm required a projected internal rate of return of 25 percent over the life of the investment. That was a common projected IRR. “The first thing I noticed was this massive dispersion of returns,” Rasmussen says. Bain would generate seven or eight times on some of its investments, but with others, zero, and the number that hit the 25 percent return bogey was infinitesimally small. The upshot was thousands of man-hours wasted modeling investment outcomes because the forecasts were inevitably wrong.
There was another surprise. The single best predictor of future returns had nothing to do with the amount of leverage employed, operational changes, company management, or even the underlying soundness of the business. The driver of superior returns was the price paid by the private-equity firm — companies purchased at a lower ratio of price to earnings before interest, taxes, depreciation, and amortization tended overwhelmingly to outperform.
The cheapest 25 percent of private-equity deals based on price-to-Ebitda accounted for 60 percent of the industry’s profits. Cheap buys made good investments. “With the inexpensive ones, there’s a margin of safety,” Rasmussen says.
The firm’s touted skills for selecting companies, arranging financing, and improving operations proved to be a mirage. Instead the best private-equity deals relied on a simple formula — “small, cheap, and levered,” as Rasmussen puts it. He expected the study to prompt major changes at the firm. “Now that we have the data, how do we change our behavior?” he wondered.
Top management was unconvinced. “The idea that their models were useless or worse than useless was not embraced,” Rasmussen says. “It was extremely controversial.” Management was not going to shift to inexpensive deals exclusively. “They wouldn’t take it to the extreme — just don’t do expensive deals.” And so he was left again to stir the pot, unsuccessfully. “My ideas on size, leverage, and cheapness were never going to be accepted,” he says.
Bain Capital issued a statement to Institutional Investor in response to Rasmussen’s concerns. “Bain Capital has an established track record of delivering superior returns to investors, and our funds have significantly outperformed the public markets. The demonstrated capability to improve the operations and performance of our companies, built over the last 34 years, is a critical part of our strategy and success. Mr. Rasmussen was a junior member of our team during his employment without full insight into our investment process or operational value add.”
Rasmussen had an idea where his insights might be appreciated: the Stanford University Graduate School of Business. Rasmussen had his eye on one accounting professor in particular — Charles Lee, a former research chief at Barclays Global Investors, the big quantitative firm that BlackRock acquired. Lee teaches a course called Alphanomics on the economics and skills behind active management in public-equity markets. Students learn to develop stock screens, assess valuations, and select securities for buying or short-selling. Of Rasmussen, Lee says, “He kind of knew what he wanted to get out of being here.”
Rasmussen and Harvard friend Chingono’s thesis, “Leveraged Small Value Equities,” was informed by what Rasmussen had learned at Bain. If the best-performing private-equity deals were based on the purchase of small, cheap companies, could Rasmussen and Chingono mimic that superior performance by creating portfolios of publicly traded stocks with similar characteristics?
Screening for size and price had been used for decades to capture small-cap and value premiums. Because much of the private-equity outperformance depended on paying down substantial debt, however, the pair would need to find an intelligent way to introduce leverage into the process. Ultimately, they decided on three screens. The first measured how much leverage a company employed. The second measured its track record of paying down debt. And the third gauged improving asset turnover, a way to assess a company’ growth trajectory.
Using a University of Chicago database, Rasmussen and Chingono looked at U.S. stocks between 1965 and 2013. Portfolios of the top 25 stocks as per the five screens returned 25.1 percent annualized during that span. They beat the average stock by a startling 11.7 percentage points.
Rasmussen had found the formula upon which to build a firm. “We propose that value investors have something to learn from the barbarians at the gate,” the pair wrote, “and our research points to the ways in which leverage enhances a small-value strategy.”
“His thesis is that debt is not necessarily a bad thing,” says Lee. “Small companies that are leveraged and can pay back the debt are pretty good bets.”
The Verdad Leveraged Company Fund got off to a rough start, including a drawdown of more than 30 percent amid a plunge in crude oil prices in its first year. Since then the largely quantitative process has been delivering. It begins with a universe of 15,000 equities in developed markets around the world. Every month Verdad’s algorithm finds roughly 500 that appear small, leveraged, and cheap. The 150 most attractive stocks, based on the five characteristics spelled out in the paper, are then culled from the broader group. A risk model removes about 25 for reasons like poor credit quality, the equivalent of being rated C or lower. Heavily shorted stocks are also jettisoned. “The shorts are smart,” says Rasmussen. “There’s something bad about the company, or may be.”
In the final stage of the quantitative process, an algorithm predicts the likelihood that a company will be able to pay down its debt, and those deemed unlikely get cut. The algorithm has a 65 to 70 percent success rate.
At this point Rasmussen and Schmitz start to exercise their fundamental skills, combing through annual reports and other filings, looking for information the screens aren’t designed to catch. “We’re looking to eliminate false positives,” says Rasmussen. “The cash may be a one-time event. It looks good but the CEO just got put in jail.” They write old-fashioned six- to eight-page research reports for each of the 40 names, providing both their quantitative and fundamental insights. Ultimately, each quarter Verdad typically trades out five names and adds five.
“We’re looking for reasons to say no,” says Rasmussen. “We’re not optimists.”
Verdad is always looking for ways to build on its initial research. In 2015 the firm began back-testing its screens on Japanese equities. Historically, Japanese small-cap stocks have had little correlation with the S&P 500, making them attractive for diversification. Debt is virtually free in Japan, given government interest-rate policies, and both the government and banks discourage bankruptcy.
Rasmussen launched the Japan Fund in June 2017, and the result has been far less downside volatility compared to its older, global sibling. The fund returned 17.2 percent over the last half of 2017.
Back-testing now is underway on European stocks, according to the founder.
The promising start for Verdad’s funds raises the question of what Rasmussen will do when their success is validated. Nobody seems to think small-cap stock management is his ultimate goal. “He’s going to have a very interesting career and life in which his success in investing is just a facet,” says Terry Considine, a real estate executive and an investor in both Verdad funds. “He has an opportunity that’s much broader.”
Rasmussen says he expects to remain focused on Verdad. “I don’t have a next career plan. I love what I do.”
Whatever unfolds, Rasmussen won’t follow the well-trodden path, say friends like Alex Cushman. “He embodies that kind of character who goes against the grain.”
Now, with a glass of wine, scan over the other spectrum:
Smart beta has become the E. coli of institutional investing!
By Richard Wiggins
Smart beta may be state-of-the-art, but it has also become the E. coli of institutional investing. There are at least 300 published factors, with roughly 40 newly discovered factors announced each year. Industry-aligned benchmark providers like MSCI, FTSE Russell, Barclays, S&P Dow Jones, and others create mountains of research and indexes supporting these found factors. So they must be real, right? The fund management industry’s brightest idea of the past few years is to soup up index returns by ranking companies not only by size and value, but also by other properties — or factors — like quality, profitability, volatility, and dividend payouts.
If you buy into this, then you’ve determined the starting point of a conversation but botched the story and the conclusion.
Researchers Eugene Fama and Kenneth French introduced their classic three-factor model, consisting of market risk, size, and value, in 1993. Nowadays indexes are investment products in and of themselves. Firms get paid if a manager wins a mandate benchmarked to one of their proprietary indexes, so is it any surprise that these indexes are proliferating at an astonishing rate? It’s been a benchmark bonanza: EDHEC-Risk Institute’s ERI Scientific Beta offers more than 4,200 smart-beta indexes. Major index providers have become factor cheerleaders, prominent fund providers have created products based on those factors, and leading investment consultants have endorsed it all.
The sales pitch is good: Factor returns are cyclical, thus uncorrelated multifactor approaches can smooth out the dry spells. The value effect, for example, returned nada for a 20-year period, from about 1951 to 1971. In the absence of a definitive method of factor timing, the prudent approach is to diversify across multiple factors.
There is no Holy Grail investment style that will outperform in all market environments. And the notion of using something in combination with something else always has a good feel to it. If you love value, then you must really love value + quality. And if you like combining two risk premia, then a quad strategy must be twice as good. Factor cocktails should be more powerful than stand-alones, and blending pro-cyclical risk-on factors (e.g., value) with defensive factors (high quality, low volatility) alleviates business cycle exposure. Shake it all together — bada boom, bada bing — to reduce risk, increase diversification, and get a higher return stream.
Bob’s your uncle.
→ When Added up, Facts Are Lies
The virtues of diversification have been drilled into the heads of financial professionals and novices for the past 50 years. As a group, we’re primed to become enamored of the idea of capturing multiple risk premia. But that overlooks the fact that these factors often cancel each other out — they’re contrabets. It’s not easy or efficient to combine them. Adding multiple engines backed by opposing theories in a single portfolio introduces drag because negatively correlated factor investments effectively bet against one another. Value has a well-established negative correlation to momentum: When a stock’s price declines, it becomes more “value-y,” but it also becomes antimomentum. Momentum strategies look for stocks that are going up, so a stock’s weight in a momentum-tilted portfolio will decrease at the same time that its weight in a value-tilted portfolio will increase. Combining the weightings of individual factor indexes — i.e., 50 percent momentum plus 50 percent value — will at times result in reduced exposure to both target factors.
Crosscurrents abound. Quality and profitability look very similar to each other and a lot like growth, so when you add them to value, you’re moving back to neutral because value stocks more often than not are closer to the junk end of the quality-versus-junk spectrum. This is just another way of saying that value stocks are the opposite of quality stocks. Size is anti momentum. Profitability and investment are slightly long momentum, which makes them frenemies. Quality portfolios have negative market, value, and size exposures, leading this new factor to pretty much cancel out everything in the original model. We find ourselves like the White Queen in Through the Looking Glass, believing six impossible things before breakfast.
→ It’s Just More Frosting on the Same Cake
There is substantial pairwise overlap among smart-beta descriptors, so owning more than one factor is often a doubling up (crossover) of bets. Emphasizing quality companies accesses the low-volatility anomaly indirectly. In fact, adding low volatility, quality, high dividends, or profitability is pretty much the same thing. Intuitively, this makes sense: Companies with stable share prices often have the mature, steady operations that are a hallmark of regular distributors of cash. And a dividend itself can damp volatility, because the rising dividend yield that comes with a falling price can bring in buyers.
The momentum factor can be something of a chameleon because it inherently chases returns wherever they may be coming from. In June 2016 the overlap of stocks between the momentum and low-volatility factor indexes reached more than 69 percent. It’s not uncommon to discover that quality, momentum, and minimum-volatility strategies are all buying the same stocks. They’re brothers from other mothers. We’re measuring the same thing twice but calling it something different, so investors trying to capture everything are overallocating to co-lineal and redundant risk factors.
Founded on colliding philosophies of investment valuation, smart beta is a modern superstition. Accounting for factors that look similar and others that cancel each other out, diversified-factor approaches look like a bowl of mush; they vary little from the broader index out of which they were created. It is analogous to plan sponsors picking active managers for every square in the Morningstar style box, and then — shock of shocks — having the composite look and behave like an index fund. Even though a total stock market fund owns both small-cap and value stocks, it has exposure to only one of the drivers of returns — beta. The total stock market fund holds small stocks but has no exposure at all to the size factor. This seeming contradiction confuses many investors. It’s true because small stocks provide a positive exposure to the size effect, whereas large stocks provide a negative exposure to it. That puts the net exposure to the size factor at zero. The same is true for value stocks, which are the opposite of growth by construction.
It’s silly, akin to double-majoring in psychology and reverse psychology. Gumming the strands of theories and countertheories into a single nut cluster isn’t a great idea because the truths recoil from each other: North negates South and East neuters West. For investors worried about market beta exposure, picking a side reduces that risk. Picking all of them invites it.
Making stocks simultaneously pass all filters at once won’t work either, because individual factors’ time variation in returns differ. Momentum is like watercress: ready for harvest about 14 days after it’s sown. But value is like snap beans, which take nine or ten weeks to mature. Forcing all into one basket and rebalancing (“harvesting”) at the same time creates a whole new set of issues.
The main marketing test for these all-in-one products is academic research. Studies prove concept, and proof sells product. But few people appreciate how weak the statistical support really is. “Smart beta” is the catch-all term for funds that use statistical hypothesis inference testing (that spells SHIT, by the way), which relies on historical regressions and the resulting p-values. This approach is in the process of being discredited. A methodological crisis occurring in science has swept up investment finance as well. Researchers across disciplines have found the results of many experiments difficult or impossible to reproduce, even by the original experimenters themselves.
In 2016 the American Statistical Association published an extraordinary document. The “Statement on Statistical Significance and P-Value” reiterated that “a p-value does not provide a good measure of evidence regarding a model or hypothesis.” It cannot answer the researcher’s fundamental question: What are the odds that a hypothesis is correct? A worldwide consortium of scientists known as the Open Science Collaboration advocates abolishing the use of p-values to determine statistical significance. At least one journal has decided that it will no longer publish the metrics. It’s been a wake-up call. Most published research based on statistically significant findings is false. This is a jarring breach of faith — like a child discovering, in his father’s drawer, the Santa Claus suit.
The whole thing really started to stink when a Cornell University professor proved the existence of extra-sensory perception (ESP). That’s when a fault line opened up and the scientific community took notice. Obviously, there was something weird in the woodpile. What had gone wrong? In a word: computers. For every fact there is an infinity of hypotheses and false discoveries that grows proportionally with the number of tests. The availability of huge data sets and inexpensive computing power allowed researchers to let the PC run overnight trying thousands of combinations and report only the ones that “worked.” Sound practice dictates that you announce what you think will work and then test it. To work backward is called “p-hacking,” and it is so widespread throughout science that many published results are false positives. For example, you might p-hack to the discovery that wet roads cause rain.
→ Requiem for the Small-Cap Premium
All of this is academic, of course. Literally. I point this out because a funny thing happened on the way to the bank. Ever since the groundbreaking small-cap/size study (which had a p-value of 1 percent) was conducted at the University of Chicago and published — the factor hasn’t worked. Small-cap is the granddaddy of factor premia, but in recent decades it has been a major disappointment, lagging both in absolute returns and on a risk-adjusted basis (Fig. 2). Ken French found that the annualized mean return spread for small-caps over large-caps exceeded 7.5 percent for approximately 90 years, but it has been virtually nil since 1983. To be sure, there have been periods in which the smallest stocks have come out on top, but there has been no consistent pattern. A repeat of the 1981 study using all historical data available today would not conclude that there is a small-firm effect.
The original factor models aren’t working, so some folks are trying to resurrect them by introducing new factors. The quality dimension, for example, resuscitates the small-firm effect, but we’re just plugging holes in old dissertations. The great factor debate has been overstated from the start; it was never 100 percent true because there’s very little resemblance between live long-only factor funds and the long-short academic portfolios that make the majority of their theoretical returns from shorting illiquid stocks that would be impossible to short in real life. Launched in 1978, the Russell 2000 Index is arguably the earliest factor product and the most commonly referenced U.S. small-cap index. Would it surprise you to learn that since the inception of this index through the end of 2017, a 39-year period, it has underperformed the S&P 500? So much for the small-cap effect.
It hasn’t worked in the broad scope of time, and it hasn’t worked recently. Even more damning is the markedly inferior performance of the Russell Microcap Index. Contrary to the theory, the smaller stocks have gotten, the worse they have performed. It is not complicated. The effect just is not there.
Likewise for the value effect. Outside the original 1962–1981 period — during which the value premium concept was born of large-sample back tests — there is no significant evidence of a value premium. The largest investment fund with “value” in its name is the Vanguard Value Index Fund, with $44 billion in assets and, since inception 25 years ago, a losing track record to the S&P 500.
What caused the market to diverge from the classic theories? Methodological errors, to some extent, but there might be more to it. Empirical evidence has become promotional currency, derived through the biased studies of vested interests. Most of these new factors are coming from product literature, but on closer scrutiny some of the research is dodgy, some is complete bunk.
Take low volatility, for instance (Fig. 4). This relatively new theory apparently contradicts the financial tenet linking higher risk to higher returns, which is supposedly what the capital asset pricing model is all about. Is the low-volatility effect true? Well, yes and no. Mostly no. The key is selecting 1968 to begin the study. From 1929 to 1968 returns and volatility related positively. In 1968 everything reversed, and high volatility stocks began underperforming low-volatility stocks. Every result is a temporary truth
→ Confidence Tricksters
It’s a Casaubon delusion; there is no transcendent truth. P-hacking makes it easy to get plausible-sounding studies to “work,” so allow me a moment to abandon the moral high ground here and roll my eyes at the suggestion that cultural diversity really improves investment returns. The latest batch of studies by McKinsey & Co., the Clayman Institute, Credit Suisse, MSCI, and others claim that greater gender diversity at senior leadership levels leads to more perspectives, which lead to better decision-making such that companies with strong female leadership see better performance than those without. There’s an SPDR SSGA Gender Diversity Index and a SHE exchange-traded fund.
I would like to acknowledge that I once thought Evelyn Waugh was a woman and that George Eliot was a man. And yes, I can see the appeal of melding a socially responsible mission — addressing the social issue of the gender gap in corporate America — with a factor-based approach, but I’m totally not buying it. The sales literature fails to note that the Pax Ellevate Global Women’s Index Fund, launched in 1993, has averaged an annual gain of 1.1 percent, below both the MSCI World Index’s average annual gain of 3.78 percent and the S&P’s average gain of 6.4 percent. Touchy topic, backlash guaranteed, but I recommend you view things as they are, not as they ought to be.
Recently, there’s been a flurry of flighty studies supporting socially responsible investing because it purportedly outperforms in the long run. I’m not sure how to reconcile such research with the fact that we all know that alcohol and cigarette stocks absolutely kill it. Tackling gender and telling people they’ve adopted an invalid belief system aren’t going to win me any friends, I recognize that. But doesn’t anybody care anymore about the integrity, transparency, and unbiasedness of science?
It pays to dig into the facts because most people care not to do so. We live in an age of “truth decay.” The Oxford English Dictionary proclaimed “post-truth” the word of the year for 2016. The original smart-beta factors aren’t working, and the science behind it is known to be flawed. But nobody’s telling the average investor, because there’s no profit in it. There is a symbiotic relationship between the fund industry and the financial media: The industry needs the media to talk about and help flog its products, and the media needs advertising revenue and something to write about.
And yes, you should be skeptical of my skepticism.
Richard Wiggins works as a strategist at a large corporate pension fund. He authored this article independent of his employer.
Let’s begin :
- 36% Of All Web Traffic Is Fake
- “Happiness” comes in a variety of packages
- Without work, life is rotten, but when work is without a soul, life dies.
- Protectionism is a predictable consequence of paper-money inflation.
“Robots” are buying ads generated by other “robots” visiting sites, and the buying bots are unable to distinguish the shady bots from legitimate human traffic.,,,,oops….
36% Of All Web Traffic Is Fake
by Dylan Love
Just over one-third of Web traffic is fraudulent, the Wall Street Journal reports, and robots are to blame.
The fake traffic comes from botnets that click on shady sites which have been created solely to generate false page view impressions, gathering advertising dollars for site owners in the process. The scheme works because advertisers only pay for their ads to appear on a site, and not specifically for their ads to be seen by real people.
From the WSJ:
The fraudsters erect sites with phony traffic and collect payments from advertisers through the middlemen who aggregate space across many sites and resell the space for most Web publishers. The identities of the fraudsters are murky, and they often operate from far-flung places such as Eastern Europe, security experts say. (read more)
Money can’t buy happiness... or so the saying goes. But it can buy plenty of things that directly contribute to your happiness. Of course, whether that means a new Prada bag or fifth of Jim Beam depends on a variety of factors. And unfortunately for some of the more high-end “luxury brands,” happiness may be going out of style.
“Happiness” comes in a variety of packages, depending on the consumer’s preferences.
by Marc Faber
I recently attended an event where one of the speakers suggested that investors should buy “happiness stocks,” examples of which include luxury goods companies such as LVMH (Moët Hennessy Louis Vuitton), L’Oréal, Prada, and Tiffany (he also extolled high-end pleasure boat manufacturers), as well as Nestlé (because it manufactures and distributes chocolates). According to this consumer goods expert, people all around the world are trying to buy happiness, and these companies are suppliers of “happiness goods.”
Personally, I find this concept of “happiness stocks” quite bizarre, as everyone has a different concept of what makes them happy, depending on their socioeconomic status. Low income earners might consider themselves happy if they have enough money to buy food, pay their rent, purchase other necessities of life, and have something left over to buy cigarettes, booze, candy, movie tickets, lottery tickets, consumer electronics, clothing, etc. ( read more )
WITHOUT WORK, LIFE IS ROTTEN, BUT WHEN WORK IS WITHOUT A SOUL, LIFE DIES.
The Monthly Market Commentary
Lucy Kellaway argues in the Financial Times that the idea so beloved by “the cheesier half of corporate America, that employees are somehow part of the family is one of the most delusional metaphors of modern corporate life.”
I have to say that I completely disagree with Miss Kellaway’s views about “families” and workplace “fake families.”
I was fortunate because I always had a close relationship with my co-workers, and all my superiors were always most courteous toward me, my wife and my daughter. In fact, they always went out of their way to support and help me. This, despite the fact, that I was probably their most “difficult” employee. But my bosses took my unpleasant character in stride and told me smilingly that if I were not “difficult,” they would not have hired me in the first place. ( read more )
Protectionism is a predictable consequence of paper-money inflation, just as is the impoverishment of an entire middle class.
Managing an Unmanageable Monetary System
by Ron Paul
Today’s economic conditions reflect a fiat monetary system held together by many tricks and luck over the past 40 years. The world has been awash in paper money since removal of the last vestige of the gold standard by Richard Nixon when he buried the Bretton Woods agreement — the gold exchange standard — on August 15, 1971.
Since then we’ve been on a worldwide paper dollar standard. Quite possibly we are seeing the beginning of the end of that system. If so, tough times are ahead for the United States and the world economy. ( read more )
Pushing Toward The Final War
by Paul Craig Roberts
Does Obama realize that he is leading the US and its puppet states to war with Russia and China, or is Obama being manipulated into this disaster by his neoconservative speech writers and government officials? World War 1 (and World War 2) was the result of the ambitions and mistakes of a very small number of people. Only one head of state was actually involved–the President of France. ( read more )
Hollow Men, Hollow Markets, Hollow World
by Ben Hunt of Epsilon Theory
~ Apocalypse Now ~
| Kurtz: | I expected someone like you. What did you expect? Are you an assassin? |
| Willard: | I’m a soldier. |
| Kurtz: | You’re neither. You’re an errand boy, sent by grocery clerks, to collect a bill. |
If you talk to a professional in any walk of life today, whether it’s technology or finance or medicine or law or government or whatever, you will hear a similar story of hollowness in their industry. The trappings, the facades, the faux this and faux that, the dislocation between public narrative and private practice … it’s everywhere. I understand that authenticity has always been a rare bird on an institutional or societal level. But there is something about the aftermath of the Great Recession, a something that is augmented by Big Data technology, that has made it okay to embrace public misdirection and miscommunication as an acceptable policy “tool”. ( read more )
Why We Are Plagued With Drivel Masquerading As Financial Reporting
by David Stockman
One of the evils of massive over-financialization is that it enables Wall Street to scalp vast “rents” from the Main Street economy.
As is well-known, the “Bloombergs” at the center of the bubble finance casino are so immensely profitable that they generate the equivalent of a drug lord’s surplus— which, in turn, funds the extensive apparatus of financial information and news production that comprise the Bloomberg empire. But at the end of the day, Bloomberg News LP is only a vertically integrated representation of the entire infrastructure of bubble finance. Reuters, the Financial Times, CNBC, Dow-Jones/News Corp and Inside Mortgage Finance are all part of the food-chain by which the bloated financial sector maintains and services itself. ( read more )
