The richest one percent of this country owns half our country's wealth, five trillion dollars. One third of that comes from hard work, two thirds comes from inheritance, interest on interest accumulating to widows and idiot sons and what I do, stock and real estate speculation. It's bullshit. You got ninety percent of the American public out there with little or no net worth. I create nothing. I own.
Capital Asset Pricing Mistakes: The Consistent Opportunities in Tail Hedged Equities
Chitpuneet Mann, Mark Spitznagel, and Brandon Yarckin
Abstract
The introduction of asymmetric beta to the CAPM framework can allow an investor to construct a portfolio with expectations well above the security market line. Incorporating asymmetric beta provides evidence of a mispricing in certain payoff profiles, namely tail hedged equities, that can be analyzed by using variants of the CAPM type of framework. CAPM based asset allocations are misspecified and ill-equipped to handle asymmetric returns.
Capital Asset Pricing Mistakes: The Consistent Opportunities In Tail Hedged Equities – Introduction
The Capital Asset Pricing Model is a fundamental building block with which investors make allocation decisions over time. Investment decisions are made based on risk-return constructs, and in this framework, CAPM, for the most part, has stood the test of time. Due to its simplicity, it is widely used when an equity investor wants to roughly estimate the expected returns of one’s portfolio.
We want to appraise the value of tail hedging within a CAPM framework, and thereby show the efficacy of tail hedging and the misspecificity of the model itself.
By using Harry Markowitz’s efficient frontier[1], one can roughly compare different asset classes based on their consensus expected returns and observed risk (mostly computed using standard deviation of asset returns). However, this measure of risk is fairly naive since it has been well documented that most, if not all, asset classes have non-normal, fat-tailed and often asymmetric return distributions. Asymmetric properties are not well accounted for in a mean-variance framework as they underestimate tail risk in negatively-skewed portfolios. Stress tests should thus be used, as they are critical risk estimation tools that transparently demonstrate vulnerabilities to large deviations that can impact long-term expected returns. (We recognize successful empirical research stating that multifactor models[2] can explain and predict investment returns, but they have similar limitations.)
Due to the principal-agent problem in the asset management industry, most money managers rationally have a propensity to use a negatively-skewed payoff distribution[3]. This kind of behavior, in aggregate, is also evidenced in the historical data, which shows significant losses for professional investors during the largest market downturns[4]. Most investors and asset allocators, in addition to these negatively-skewed positions, further view the returns of hedging strategies in a vacuum, rather than as a holistic part of their broader portfolio. Thus, they are likely to consider portfolio hedging programs to be a drag on their performance numbers and further undervalue them. We believe that these factors, among others, contribute to a market segmentation that creates an undervaluation in tail-risk hedges.
Assuming there are such opportunities in hedging tail risk, let’s evaluate how one can depict an asset class’s risk-return profile and see if using a fair proxy tail-risk hedging program could help investors better maneuver these not-so-uncommon market crashes. We use Markowitz’s efficient frontier type of framework to plot a ‘risk measure’ on the x-axis (which is the average semi-variance for three-year rolling monthly returns) and the corresponding asset’s annualized returns on the y-axis.
From Figure 1, we can safely ascertain that from a risk-reward standpoint, an investment in the S&P 500 Index plus short-term Treasuries could be considered a benchmark for validating a tail hedge argument. Thus, we choose a vanilla 60/40 portfolio — 60% invested in the S&P 500 and 40% in short-term Treasuries, rebalanced monthly. On the other hand, our tail-hedged portfolio consists of S&P 500 and out-of-the-money put options (specifically one delta which has a strike roughly 30-35% below spot) on the S&P 500. At the beginning of every calendar month, using actual option prices, the number of third-month options (with a maturity from 11 to 12 weeks, and also carrying over the payoff from unexpired options) is determined such that the tail-hedged portfolio breaks even for a down 20% move in the S&P 500 over a month. From practice, for scaling the payoff, we can safely assume that the S&P 500 options’ implied volatility, or IVol, surface would look similar to the one observed after the lows of the October 2002 crash (an observed in-sample data point for the backtest period).
Mark-to-market fluctuations in the options position of the tail-hedged portfolio (i.e. giving back small unrealized gains) can cause its risks to be overstated by semi-variance. We can, however, overcome this limitation by using model-free stress tests.
Indexing, as I have written before, is a form of socialism, since capital is allocated not as it should be - according to its marginal return - but rather according to swings in the market capitalization of the underlying assets. It is hard to think of a more stupid way to allocate this scarce resource.
In this new world, the goal of every money manager is to achieve a performance as close as possible to the index against which he is benchmarked (see Indexation = Parasitism). As a consequence, the dispersion of results among money managers has become smaller and smaller over the years. Today you can even buy programs telling you how much IBM stock you should buy versus Johnson and Johnson in order to control your “tracking error”. As always in economics, there is what you see and what you don’t. What most people don’t see is how the spread of indexation has led to a collapse in the growth rate of the economy.
Building a portfolio is a very complex exercise. In a perfect world, one would start with the “expected” marginal increase in the return on invested capital of different investments. Once satisfied with a given position, one should try to ensure that the increase in the marginal return is not too correlated with other positions in the portfolio. The name of the game is to find assets with the same ROIC over the long run, but a negative correlation over the shorter term (for example, US shares versus. US government bonds over the last 20 years).
This aims at the Holy Grail of money management, which is to achieve a decent long term return, together with a low volatility of that return. As one can see, this involves a massively complex price discovery exercise, starting with an examination of the marginal variations of ROIC, followed by consideration of the prices at which one can buy the available assets, and finally ending with portfolio construction.
In such a world, one would expect the distribution of performances to be very wide. Indeed, a large dispersion of performances should reassure us that capital has been properly allocated. After all, not everybody can win the jackpot.
Alas, today’s world is not perfect, and this is not how capital is allocated. Instead capital is allocated according to the market capitalization of the assets under consideration. So nowadays, capital is directed to an investment if it outperforms. In simple terms, this means that capital is channeled to companies enjoying an increase, not in their ROIC, but in their share prices. In a world in which investments are made according to the marginal ROIC (i.e. the past), these two tended to overlap. As a result, indexation worked, but only as long as no more than about 5% of assets were managed by “free-riding” indexers.
Not in today’s world. Today indexing has become the dominant asset management style, and investments are dictated by market cap and changes in market cap; which is simply another way of saying that capital is now deployed according to momentum-based rules. This was very visible in 1999-2000, and is almost as visible today.
Intellectually, the old method of investment was based on a “return to the mean” approach. When the price movements of an asset became excessive compared to its expected ROIC, then one bought - or sold - the asset. Today, capital is allocated only according to marginal variations in the price of the asset. The more it goes up, the more money managers invest in it. The more it goes down, the less managers own.
A return to the mean methodology leads naturally to a stable, but moving, equilibrium. Momentum-based investing inevitably creates an explosive-implosive system, which swings wildly from booms to busts and back again. And if monetary policy is as silly as it has been since 2002, these swings will be even more pronounced.
The closer we get to a bust, the tighter the performance dispersion among money managers, as the poor fellows trying to manage efficiently and professionally lose their clients to benchmark optimization algorithms. I don’t have the necessary data, so cannot prove it, but I would not be surprised if a sharp fall in the dispersion of money managers’ results is a reliable warning that a bust is approaching.
The goal of every socialist experiment is for everybody to earn the same salary. In the world of money management, we seem to have achieved this remarkable ambition. Hurrah!
Of course, if everybody gets the same results, then no one is going to get fired for underperforming, which is great news for the people administering the capital (I hesitate to call them managers). But—and here is what we do not see—our capital is being massively misallocated, all the time.
People ask me why we have no economic growth. Why on earth do they expect economic growth in a socialist system?
For fun, Curtis Macnguyen likes to run along the seafloor in 15 feet of water, carrying a boulder.
He does it offshore from his house on the blue-watered Kona Coast of Hawaii’s Big Island, Bloomberg Markets reports in its May 2015 issue, not far from similar spreads owned by Michael Dell and buyout kingpin George Roberts.
Macnguyen, 46, is a hedge fund manager. An old-school hedge fund manager. His methods are what you’d expect from a guy who carries rocks underwater: lots of hard work, almost no big sprints, and steady progress, all under pressure.
Macnguyen brings his A game to everything, and has since childhood, when he bet on Trivial Pursuit and Pictionary with his six brothers. He has a tennis court in his backyard in the Brentwood neighborhood of Los Angeles, where he hits against local pros. Mats Wilander, winner of eight Grand Slam titles, came for a few sets in March.
Macnguyen’s golf handicap is 6, and he never plays without a little money on the line. A wager, even a small one, makes him step up his game. He recently lost $100 to Matt Kuchar, ranked No. 14 in the Official World Golf Ranking. He just built a gym—Tuscan style, like his house—so he could do a workout recommended by Marcus Elliott, a doctor and biomechanist who trains the best players in the National Basketball Association.
“Every guy who’s really successful at anything wakes up and says, ‘How can I do this better?’” Macnguyen says. (He’s Vietnamese, but his name sounds Irish. It’s pronounced like McWin.) He’s sitting on a covered patio at his house on a bright November day sipping iced tea made by a private company he’s backing. For an hour before, he hammered table tennis shots at a former national champion from South Korea (and Playboy model) named Soo Yeon Lee. He loves pingpong because it gets him in the zone—that rarefied state of total concentration where time vanishes and maximum ability emerges. “You’re out of your body, watching yourself,” he says, “and you can get any ball that comes in.”
Macnguyen is every bit as intense at Ivory Investment Management, the $3.5 billion hedge fund firm he founded in November 1998. Through the end of 2014, his Ivory Flagship Fund returned 346 percent, or 9.7 percent a year. That’s twice the 139 percent delivered by the Standard & Poor’s 500 Index.
Curtis Macnguyen says table tennis, more than any other sport, gets him in a zone of pure concentration.
Benjamin Rasmussen/Bloomberg Markets
Even more impressive: Because Macnguyen hedges his bets by balancing long and short positions, he had, on average, about one-fifth of investors’ money exposed to potential losses. The S&P 500 is 100 percent exposed, by definition. When the market fell during those years, he either made money or lost very little. And when it rose, his portfolio often rose much more.
Macnguyen’s methods have made him rich. He likes Hawaii so much that he and a group of investors bought 873 acres (353 hectares) of oceanfront land that they’re developing. He gets there from Los Angeles on his very own Gulfstream G450.
But that’s not enough for Macnguyen. He could own every white-sand beach in the Pacific and not be content. Lately, he’s been pretty ticked off—with himself. A person could look at his track record and conclude that his best years are behind him. And that is just not acceptable.
In 1999, its first full year of operation, Ivory Flagship returned 28 percent, compared with 21 percent for the S&P 500. Even better, when the index fell 9 percent the next year, Macnguyen made 17 percent.
Investors who didn’t love him already should have swooned in 2008. The market plunged 37 percent that year, and Ivory Flagship fell just 7.6 percent. When the rebound came in 2009, Macnguyen was ready. Investors had been pestering him for a new fund that would take more risk, and he obliged with the Ivory Optimal Fund, now his largest. It jumped 28 percent that first year, compared with 26 percent for the S&P 500.
Then something changed. In 2010, Ivory Flagship lagged the index by 13 percentage points. In 2011, he lost 3.6 percent in Flagship while the market rose 2.1 percent. Ivory Optimal did worse. His mojo was missing in action.
“I never kicked a dog or smashed a computer or even yelled at anyone,” Macnguyen says. “I was just frustrated and pissed off at having to keep explaining to investors that the environment was tough for our strategy. I’ve always felt that we’re in a no-excuse business. Just like high-level competitive sports, no matter how tough the conditions are, it shouldn’t matter, because you just have to be better than your competitors.”
Macnguyen, like most hedge fund managers, lives pretty high up in psychologist Abraham Maslow’s hierarchy of needs. Food, water, sleep, sex? Check. Security, employment, health? Yep. Friendship, family, intimacy? Check, again. (He’s married and has a stepson, 21, and a son, 7.)
What began to elude him, it seems, is the next level: self-esteem, confidence, and perceived respect from others. He grumbles about rivals getting more attention—and money to manage—despite inferior performance. He singles out a doppelgänger (at least on paper): a former investment banker from an Ivy League school who’s also 46: David Einhorn, who runs Greenlight Capital. They worked together at a small hedge fund firm called Siegler, Collery & Co. in 1993. Since it started in 2009, Ivory Optimal has returned 113.5 percent, edging Greenlight’s 112 percent for the same period. Yet Greenlight manages $12 billion, almost four times what Ivory does, and that bothers Macnguyen. “The only difference between me and Einhorn is that he’s higher profile and I’m purposely very low profile,” Macnguyen says. “Plus, I’m supercompetitive and will only get better over time.”
In conversation, Macnguyen toggles between bravado, like that, and self-flagellation. He frets about recent years when he failed to do the single thing hedge fund managers get paid for: generating alpha. Alpha is profit that doesn’t come from the whole market going up or down. Anyone can get lucky and make big money by taking a big risk. Alpha is different. It’s return you get beyond the risk you take. And hedge fund managers have to produce enough to cover their fees. Ivory’s are an industry-standard 2 percent of assets per month plus 20 percent of annual gains.
Bloomberg Markets
In 2010 and 2011, few of Macnguyen’s picks worked. He shorted Amazon.com, betting that earnings would tumble as the company invested heavily to keep revenue rising. Sure enough, earnings fell, but investors didn’t care, and the stock rose. He bought shares of Hospira, a maker of injectable drugs, when they slumped into the $40s from close to $60 in 2011. Then the company warned that regulatory issues had slowed production at a plant in Rocky Mount, North Carolina, and the stock dropped into the $20s. Macnguyen tried to hang on for the rebound he expected, but the losses mounted. “For every winner we had, we had a loser,” he says. “We didn’t add a lot of alpha for two years, and that is painful for a guy like me.”
It’s a familiar story. Managers of equity funds, once accustomed to beating the S&P 500, have, as a group, been thrashed in each of the past six years, according to an index of equity funds tracked by Hedge Fund Research in Chicago, and have bested the index in just three of the past 12.
Explanations—or excuses—abound: There’s more competition now as some 10,000 hedge funds look for stuff to buy with $3 trillion they’ve collected from pensions, endowments, and rich people; the U.S. Federal Reserve’s dovish interest rate policy won’t let the market fall; hedge funds do better in down years, and the U.S. stock market hasn’t had one in six years. Many of the great ones have given up. Jeff Vinik, who managed the famed mutual fund Fidelity Magellan from 1992 to 1996, shut his hedge fund, Vinik Asset Management, in 2013 and returned $6 billion to investors after ill-timed bets on stock indexes and gold-mining shares.
There may be more at work. Nobel laureate Daniel Kahneman wrote in his 2011 book, Thinking, Fast and Slow, that stock-picking managers exist because of an “illusion of skill” and add no value compared with passive—and cheaper—index investing.
“It’s very difficult to do what these people are trying to do,” says Matthew Litwin, head of manager research at Greycourt, a consultant to 100 wealthy families and institutions with a total of $9 billion to invest. (He puts his clients’ money in a variety of vehicles, including, occasionally, hedge funds. He declined to comment specifically on Ivory.) “Most people will fail.”
Macnguyen isn’t buying into any illusion of skill. He agrees that most managers will fail. He just doesn’t intend to be among them.
Macnguyen’s arc toward an absurdly high net worth is as unlikely as any American’s. He was born in Cam Ranh Bay in 1968, the same year the North Vietnamese army surprised the south with the Tet Offensive, taking the Vietnam War to a new, bloodier level. His family moved to Saigon, now Ho Chi Minh City, and his father served in the navy, then in the South Vietnamese congress. They planned to stay, even as the Viet Cong took over in April 1975.
Then his mother had a dream about falling off a cliff and being saved by the hand of the Buddha. Early that morning, his parents packed up eight of their 10 kids—two had gone to the U.S.—and rushed to Saigon’s harbor, where his father commandeered a boat and chugged out to sea with 500 refugees. Pirates shot at them in the South China Sea. They ran out of fuel, and his father threatened to shoot at a Chinese tanker unless it towed his vessel to land.
The Macnguyens made it to the Philippines, then to a military camp in Arkansas, and finally to Hyde Park, New York. Curtis’s father sold vacuum cleaners door-to-door. His mother worked in a factory making candy canes.
Macnguyen didn’t speak a word of English when he arrived in the U.S. at the age of 6, the baby of the family. He learned it, worked at McDonald’s, and spent one summer with a sister in Hawaii, picking heart-shaped anthurium flowers off the rain-soaked slopes of the Big Island for $2.17 an hour, illegally. He’d come home covered in leeches.
He worked equally hard in school, captained the tennis team, and went to the University of Pennsylvania to study engineering. A tedious summer job writing computer code in a cubicle prompted a transfer to the Wharton School, even though he knew nothing about finance. He graduated summa cum laude in 1990.
He worked in New York at Morgan Stanley for less than a year before landing a spot at Gleacher & Co., the investment bank founded by Eric Gleacher, who had advised Kohlberg Kravis Roberts on its record-setting, $30 billion buyout of RJR Nabisco in 1989. Gleacher paid more than other banks, and Macnguyen’s salary doubled, to $100,000.
The place turned out to be a hedge fund incubator. At least five other analysts who worked there went on to start funds, including Larry Robbins, later the founder of Glenview Capital Management, which now has $10 billion under management.
The place was perfect for a gambler like Macnguyen. “We’d play Nerf basketball for thousands of dollars,” says former co-worker Raji Khabbaz, who also launched a fund. “Some of those games got pretty expensive.”
The group learned about hedge funds after stock-picking legend Julian Robertson hired Gleacher to try to sell a stake in his Tiger Management. Khabbaz worked on the offering, and he and Macnguyen saw just how lucrative hedge funds could be. They pitched Gleacher on starting one in-house, but he passed, so Macnguyen bolted for Siegler Collery in 1993. “They had $80 million of assets, and that was big,” he says. Einhorn, the soon-to-be founder of Greenlight, joined the firm right afterward.
Macnguyen started Ivory in 1998. He chose the name in part because, over time, he’d spent days spelling Macnguyen on calls, and also because, in Southeast Asia, the elephant and ivory are symbols of good fortune. In its first three years, Ivory Flagship beat the S&P 500 by 7 percentage points, 26 percentage points, and 19 percentage points, respectively.
New York began to wear on Macnguyen, and he decided to make a move he’d long contemplated, to Los Angeles, where he had often traveled for work. “Every time I got off the plane, I had the best feeling in the world,” he says.
In his new suite in Brentwood, Macnguyen had healthy returns for years, in all sorts of markets. True to conservative form, he protected investors from disaster in 2008. He caught the rebound in 2009.
Then the Federal Reserve flooded the market with money, lifting almost all boats. But not Macnguyen’s. Amazon rose in his face, and Hospira fell. Nothing seemed to work. He got beaten by index funds, which would be a little like Macnguyen beating Kuchar at golf. It just shouldn’t happen.
The slump changed his core beliefs about his business. Before, he thought he could build a company that would outlast him. Now, that seemed impossible. If he was off his game, then the whole firm lost. No one seemed to step up.
So Macnguyen stepped back into the trenches. In Brentwood, he had allowed himself a private office. Now, he knocked out the wall that separated him from his six analysts. Everyone sits, stands, and mills around in one big room, and he hears everything the analysts say, not just what they choose to report to him in meetings. “A lot of times, it’s the thing that they don’t tell me that’s important,” Macnguyen says.
To the same end, he has software that lets everyone in the firm post ideas, no matter how harebrained, so he can see them. If the ideas pass tests for valuation, profitability, and some three dozen other factors, they get a very serious look.
Working for Macnguyen at Ivory sounds almost as tough as picking flowers in the leechy hills of Hawaii. He rides his staff hard, forcing them to defend their stock selections. “If you don’t put your ass on the line and make a high-conviction call, then you will never learn,” Macnguyen says. “You have to be so wrong, and it has to hurt so badly, and everybody has to see it, that you will never make that mistake again.”
If one thing riles Macnguyen most, it’s probably the lack of respect he gets for making money with such low risk. Everyone harps on one number: return. Macnguyen believes sophisticated investors, at least, should be talking about risk-adjusted return, which can be measured by a manager’s efficiency ratio. That’s annual return divided by annual volatility. The higher the ratio, the better. Ivory Optimal’s was 1.65 as of December. That beat another hard-driving hedge funder: Bill Ackman, the top manager in Bloomberg Markets’ 2014 ranking of large funds. His Pershing Square International had a ratio of 1.31.
“People don’t pay attention to guys who make money on a risk-adjusted basis when the market is up,” Macnguyen says. “In the next five years, the market isn’t going to be up as much as it has been.”
With all the crowding in finance these days, one of the easiest mistakes to make is getting stuck in a “hedge fund hotel,” a stock owned mostly by other funds. They’re pricey and crowded, and guests tend to leave all at once. Just before the 2008 crash, Macnguyen saw the funds piling into energy companies and commodities producers, and he stayed clear. When the funds had to sell assets to return money to panicked investors, those stocks got whacked.
Since then, Macnguyen has honed a system for avoiding investors who aren’t in for the long haul: He looks for stocks that are mired in a trench, of sorts: 50 percent below a two-year high and within 20 percent of recent lows. Within that band, the number of shares traded must exceed all of the outstanding shares. “By then, everyone who is nervous is already gone,” he says. They’ll have been churned out. After his systems find a stock that fits, Macnguyen and his team do deep research, calling the company, visiting, and scrutinizing earnings calls.
“The perfect idea for Curtis,” says Jim Vincent, a managing director at AllianceBernstein who has been pitching ideas to Macnguyen for years, “would be a company that’s profoundly oversold and hated and has a new CEO who has a chip on his shoulder and a heavy ownership of stock that’s locked up for a long time, in a cyclical business that just troughed.”
Boston Scientific met many of those criteria. It showed up on Macnguyen’s churner screen in 2012, after it had fallen below $6 from $14 back in 2008. Ivory started looking at it and learned that the company had been struggling since 2006, when the U.S. Food and Drug Administration barred it from releasing some new products until it resolved manufacturing problems. The FDA lifted the ban in 2010, but the company kept losing money. It hired a new CEO in 2011. Ivory started buying in 2012. The swooning revenue stabilized in 2013, and that was enough to lift the stock to $12 from $6. On April 9, it closed at $18.10. “We try to find really good setups, where you have to be a little bit right to make a lot of money and a lot wrong to lose a little bit of money,” Macnguyen says.
Another churner find: memory chip maker Micron Technology. Macnguyen bought it at $6 in 2012. On April 9, it closed at $27.82, and Ivory owns 2 million shares. He points out that Einhorn backed up the truck and bought 23 million shares of Micron in 2013 and paid closer to $14.50.
The victories are adding up for Macnguyen, and he says he feels better about things than he did in the depths of his slump. Not content, by any means, but better. Ivory Optimal returned 28.3 percent in 2013, compared with 32.4 percent for the S&P 500. But the Optimal fund’s net exposure to the market—its longs minus its shorts—was just 24.3 percent. In 2014, Optimal rose 11.4 percent, lagging the market by about 2 percentage points. Its net exposure was 33 percent.
Making big money like that with limited risk isn’t easy. Nor is carrying a boulder underwater. These days, Macnguyen can go about 30 yards before he has to drop it and come up for air, probably longer if there’s money on the line. Then he goes back down and lifts it off the sandy bottom for another run.
Active managers suffered more than usual last year—S&P Dow Jones investigated why.
The proportion of active US equity managers that underperformed the S&P 500 index in 2014 was “extraordinarily high”, according to S&P Dow.
“In a low-dispersion environment, the value of skill goes down.” —Chris Bennett & Craig Lazzara, S&P Dow JonesResearch by the index provider reported that record-low measurements of stock dispersion in the benchmark had wiped out many opportunities for stockpickers to outperform.
“This is not primarily a reflection of manager skill,” wrote Senior Index Analyst Chris Bennett and Managing Director Craig Lazzara. “The problem is that in a low-dispersion environment, the value of skill goes down.”
Of a sample of 362 US equity funds, just 37 outperformed the S&P 500’s 20.76% return in 2014, a significantly lower proportion (10%) than in the previous two years, according to data from FE Analytics collated by CIO.
“For low-dispersion, high correlation sectors, the most important decision is the sector call, rather than individual stock recommendations.”Bennett and Lazzara reviewed historical dispersions within S&P 500 industry sectors and between sectors, as well as comparing the index to mid-cap and small-cap benchmarks. Small caps offered the highest dispersion and volatility measures, the pair found, meaning better stock-picking opportunities were likely.
The pair also argued that managers should focus on sector calls rather than always trying to pick the best individual stocks—at least when it came to the S&P 500.
“For low-dispersion, high correlation sectors, the most important decision is the sector call, rather than individual stock recommendations,” Bennett and Lazzara wrote. “A correct sector call will be reflected relatively consistently across all stocks in the sector.”
Analysts covering utilities or energy companies “would be well advised to spend most time and effort deciding whether to be in or out of the sector”, the report concluded, citing the low levels of dispersion between such stocks. In contrast, analysts working on technology or healthcare “may be better off trying to separate the sectoral wheat from the sectoral chaff.”
Bennett and Lazzara’s paper, “Some Implications of Sector Dispersion”, can be downloaded from the S&P Dow Jones website.
It's not a question of enough, pal. It's a zero sum game, somebody wins, somebody loses. Money itself isn't lost or made, it's simply transferred from one perception to another.
