hedge funds

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n an article for Bloomberg View last week titled “Why It’s Smart to Worry About ETFs”, Noah Smith wrote the following prescient truth: “No one knows the basic laws that govern asset markets, so there’s a tendency to use new technologies until they fail, then start over.” As we explored in WILTW June 1, 2017, algorithmic accountability has become a rising concern among technologists as we stand at the precipice of the machine-learning age. For more than a decade, blind faith in the impartiality of math has suppressed proper accounting for the inevitable biases and vulnerabilities baked into the algorithms that dominate the Digital Age. In no sector could this faith prove more costly than finance.

The rise of passive investing has been well-reported, yet the statistics remain staggering. According to Bloomberg, Vanguard saw net inflows of $2 billion per day during the first quarter of this year. According to The Wall Street Journal, quantitative hedge funds are now responsible for 27% of all U.S. stock trades by investors, up from 14% in 2013. Based on a recent Bernstein Research prediction, 50% of all assets under management in the U.S. will be passively managed by early 2018.

In these pages, we have time and again expressed concern about the potential distortions passive investing is creating. Today, evidence is everywhere in the U.S. economy — record low volatility despite a news cycle defined by turbulence; a stock market controlled by extreme top-heaviness; and many no-growth companies seeing ever-increasing valuation divergences. As always, the key questions are when will passive strategies backfire, what will prove the trigger, and how can we mitigate the damage to our portfolios? The better we understand the baked-in biases of algorithmic investing, the closer we can come to answers.

Over the last year, few have sounded the passive alarm as loudly as Steven Bregman, co-founder of investment advisor Horizon Kinetics. He believes record ETF inflows have generated “the greatest bubble ever” — “a massive systemic risk to which everyone who believes they are well-diversified in the conventional sense are now exposed.”

Bregman explained his rationale in a speech at a Grant’s conference in October:

“In the past two years, the most outstanding mutual fund and holding- company managers of the past couple of decades, each with different styles, with limited overlap in their portfolios, collectively and simultaneously underperformed the S&P 500…There is no precedent for this. It’s never happened before. It is important to understand why. Is it really because they invested poorly? In other words, were they the anomaly for underperforming — and is it reasonable to believe that they all lost their touch at the same time, they all got stupid together? Or was it the S&P 500 that was the anomaly for outperforming? One part of the answer we know… If active managers behave in a dysfunctional manner, it will eventually be reflected in underperformance relative to their benchmark, and they can be dismissed. If the passive investors behave dysfunctionally, by definition this cannot be reflected in underperformance, since the indices are the benchmark.”

At the heart of passive “dysfunction” are two key algorithmic biases: the marginalization of price discovery and the herd effect. Because shares are not bought individually, ETFs neglect company-by-company due diligence. This is not a problem when active managers can serve as a counterbalance. However, the more capital that floods into ETFs, the less power active managers possess to force algorithmic realignments. In fact, active managers are incentivized to join the herd—they underperform if they challenge ETF movements based on price discovery. This allows the herd to crowd assets and escalate their power without accountability to fundamentals.

With Exxon as his example, Bregman puts the crisis of price discovery in a real- world context:

“Aside from being 25% of the iShares U.S. Energy ETF, 22% of the Vanguard Energy ETF, and so forth, Exxon is simultaneously a Dividend Growth stock and a Deep Value stock. It is in the USA Quality Factor ETF and in the Weak Dollar U.S. Equity ETF. Get this: It’s both a Momentum Tilt stock and a Low Volatility stock. It sounds like a vaudeville act…Say in 2013, on a bench in a train station, you came upon a page torn from an ExxonMobil financial statement that a time traveler from 2016 had inadvertently left behind. There it is before you: detailed, factual knowledge of Exxon’s results three years into the future. You’d know everything except, like a morality fable, the stock price: oil prices down 50%, revenue down 46%, earnings down 75%, the dividend-payout ratio almost 3x earnings. If you shorted, you would have lost money…There is no factor in the algorithm for valuation. No analyst at the ETF organizer—or at the Pension Fund that might be investing—is concerned about it; it’s not in the job description. There is, really, no price discovery. And if there’s no price discovery, is there really a market?”

We see a similar dynamic at play with quants. Competitive advantage comes from finding data points and correlations that give an edge. However, incomplete or esoteric data can mislead algorithms. So the pool of valuable insights is self-limiting. Meaning, the more money quants manage, the more the same inputs and formulas are utilized, crowding certain assets. This dynamic is what caused the “quant meltdown” of 2007. Since, quants have become more sophisticated as they integrate machine learning, yet the risk of overusing algorithmic strategies remains.

Writing about the bubble-threat quants pose, Wolf Street’s Wolf Richter pinpoints the herd problem:

“It seems algos are programmed with a bias to buy. Individual stocks have risen to ludicrous levels that leave rational humans scratching their heads. But since everything always goes up, and even small dips are big buying opportunities for these algos, machine learning teaches algos precisely that, and it becomes a self-propagating machine, until something trips a limit somewhere.”

As Richter suggests, there’s a flip side to the self-propagating coin. If algorithms have a bias to buy, they can also have a bias to sell. As we explored in WILTW February 11, 2016, we are concerned about how passive strategies will react to a severe market shock. If a key sector failure, a geopolitical crisis, or even an unknown, “black box” bias pulls an algorithmic risk trigger, will the herd run all at once? With such a concentrated market, an increasing amount of assets in weak hands have the power to create a devastating “sell” cascade—a risk tech giant stocks demonstrated over the past week.

With leverage on the rise, the potential for a “sell” cascade appears particularly threatening. Quant algorithms are designed to read market tranquility as a buy-sign for risky assets—another bias of concern. Currently, this is pushing leverage higher. As reported by The Financial Times, Morgan Stanley calculates that equity exposure of risk parity funds is now at its highest level since its records began in 1999.

This risk is compounded by the ETF transparency-problem. Because assets are bundled, it may take dangerously long to identify a toxic asset. And once toxicity is identified, the average investor may not be able to differentiate between healthy and infected ETFs. (A similar problem exacerbated market volatility during the subprime mortgage crisis a decade ago.) As Noah Smith writes, this could create a liquidity crisis: “Liquidity in the ETF market might suddenly dry up, as everyone tries to figure out which ETFs have lots of junk and which ones don’t.”

J.P. Morgan estimated this week that passive and quantitative investors now account for 60% of equity assets, which compares to less than 30% a decade ago. Moreover, they estimate that only 10% of trading volumes now originate from fundamental discretionary traders. This unprecedented rate of change no doubt opens the door to unaccountability, miscalculation and in turn, unforeseen consequence. We will continue to track developments closely as we try and pinpoint tipping points and safe havens. As we’ve discussed time and again with algorithms, advancement and transparency are most-often opposing forces. If we don’t pry open the passive black box, we will miss the biases hidden within. And given the power passive strategies have rapidly accrued, perpetuating blind faith could prove devastating.

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Portfolio management involves much more than just an investment idea. For sophisticated investors, it is also about diversification, volatility management, and exposure mitigation.

For a Bridgewater client, the investment process isn’t as much about the hedge fund as it is about the client’s risk management needs. After explaining how the fundamental investment machine works – which operates like a systematic, logic driven machine – Prince explained a portfolio customization method typically reserved for the most sophisticated of algorithmic investors.

While the core investment analysis and “truths” upon which investments are based does not change from investor to investor, the level of volatility and beta benchmark exposure can be adjusted like a dial on an oven. If an investor determines they want 7% volatility, for instance, Bridgewater customizes their investment based on this benchmark by keeping the mix of alphas the same, but adjusting their size. All other performance factors – absolute returns, drawdown, risk exposure – are driven by this volatility dial to various degrees.

The beta benchmark offers investors a method to calibrate the effectiveness of their investment to any one of 22 different benchmarks.

Bridgewater’s strategies are fundamental in nature but driven from a systematic standpoint. In fact, Ray Dalio, the fund’s founder, is credited with being among the early hedge fund leaders to embrace systematic, logic-based algorithms.

The fundamental investment process starts by developing a timeless and universal investment thesis based on “how the world works.” Each performance driver and the logic behind the investment is made entirely transparent to the investment analysis team. Engaging in “radical transparency,” a strong critique and even attack of the investment thesis – modeling through positive and negative market environments – is encouraged. It is not an environment for those who take offense at their ideas or principles being challenged can typically handle. In this respect, it is a survival of the fittest environment to various degrees – and only the strongest uncorrelated ideas rise to the top.

After the research idea makes it through a strong due diligence process, strategies are assessed for goodness and correlation based on a series of qualitative and quantitative metrics. These fundamentally based systems measure the pressure on each market, with pressure dials that scale from fully bullish to fully bearish with smooth gradations in between.

This research, for which Ray Dalio, Bob Prince and Greg Jensen are intimately familiar, is then handed off to the asset management team where portfolio exposure impact is assessed. At each stage of the portfolio management process there are idiosyncratic methods that Bridgewater utilizes to deliver uncorrelated performance improvement.

After asset management, the third and final step of the process is trade execution. Bridgewater doesn’t invest in individual name stocks to the extent of most hedge funds but rather engages in significant derivatives exposure. In large part this is done for the sake of exposure efficiency but also allows the degree of volatility and risk management customization, much of which is done through various leverage adjustments.

Bridgewater is a machine, but a machine based on a systematic logic that is firmly run by humans. The output has been some of the most uncorrelated performance in the history of major hedge funds.

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Hedge funds, you read here in June, are often riskier than they are made out to be. Putting your money into ‘a fund that blows up, closes down or disappears with all your money’, I suggested, is a real risk for the unwary investor. The danger, I could have written, is that you will find your money being looked after by Brian Hunter, a 32-year-old energy trader from Calgary who last month single-handedly accounted for the largest hedge-fund meltdown since records began.

In the space of two short weeks, Mr Hunter worked his way through some $6.5 billion when his complex strategy of forward bets on the price of natural gas went badly wrong, wiping out 70 per cent of the capital deployed by his hedge fund employers, Amaranth Advisors. In one day alone, Mr Hunter and his colleagues on the energy trading team lost $560 million as the price of natural gas futures plunged and they were unable to liquidate their positions fast enough to meet their margin calls and preserve their lines of credit.

The fund is now attempting to close down what remains of its operations in an orderly fashion. The energy trading positions have been sold to other market participants and what is left of its $9 billion of capital (not much) will be returned to investors. This being North America, a carrion-seeking flight of lawyers is hovering over the scene, looking to institute a legal action of some sort for the unhappy victims.

Aside from wealthy individuals, those feeling the heat from the meltdown include the San Diego county pension scheme, which has lost some $100 million, and two fund-of-hedge-funds run by Morgan Stanley and Goldman Sachs, whose allegedly sophisticated monitoring systems proved unable to spot the trouble ahead. Man Group, the quoted UK hedge fund group, also had a small exposure to Mr Hunter’s trading activities.

The losses at Amaranth dwarf even those of Long Term Capital Management, the now infamous hedge fund that boasted two Nobel Prize-winning economists among its founders yet still went down in flames in 1998. It lost $4 billion in a few weeks when an even more complex series of bets on a range of financial derivative contracts proved to be less fireproof than its ultra-sophisticated risk modelling had suggested. LTCM was eventually bailed out by a consortium of leading Wall Street banks at the instigation of the Federal Reserve.

The failure of Amaranth has fortunately had few such repercussions. While there is no question that hedge funds are here to stay, the Amaranth case is an unwelcome setback for the industry at a time when its advocates are pitching hard to persuade pension funds that hedge funds are a valuable new investment class, and regulators that private investors should be allowed much broader access to these new and poorly understood investment vehicles.

Amaranth was not some fly-by-night bucket shop, but an A-list fund operating from Greenwich, Connecticut, the hedge fund capital of the world, a place cutely described at a recent industry dinner as ‘New York on steroids’. Morgan Stanley and Goldman Sachs were both happy to put clients’ money with Amaranth — and if they can’t spot a blow-up coming, we may well ask, what hope has anyone else?

All hedge funds trumpet the fact that they have sophisticated risk systems that allow them to pursue absolute returns — that is, make money in both up and down markets — in a controlled manner. The best, to be fair, do just that, but the lure of big bucks is now attracting a much more diverse crowd of wannabes, to the point where even veteran hedgies such as Steven Cohen, founder of SAC Capital Advisors, says that it is getting harder to make outsize returns. ‘We’re entering a new environment. The days of big returns are gone,’ he told the Wall Street Journal this summer.

At Amaranth Mr Hunter routinely held hundreds of positions in an array of derivative contracts linked to future prices in the natural gas market. These bets were ‘geared up’ by using borrowed money and margin calls to magnify the gains and losses. As so often happens, it appeared for a while that he had the Midas touch. In 2005 Amaranth made $1.3 billion from his trading activities, and $2 billion more in the first four months of this year.

But there were warning signs too. In May he lost nearly $1 billion. At his previous employers, after a similar period of success, he departed abruptly having lost two thirds of his gains in the last month of the year, something he apparently attributed to faults in the bank’s trading systems. Some seasoned hedge fund investors, it now appears, declined to invest in the Amaranth fund because of its flawed risk controls.

In September, triggered by a sharp fall in energy prices and a disappointing (for some) absence of hurricanes, the whole operation blew up in Mr Hunter’s face. According to his boss, the dramatic losses were the result of a highly improbable combination of events, a sharp decline in the future price of natural gas coupled with the rare inability of the fund to unwind its positions in the market. The reality, everyone else in the business suspects, is rather different.

Hubris and overconfidence surely played a part, as evidenced by the ever bigger bets that Mr Hunter appeared to be taking. Whatever risk systems the hedge fund had in place, losing two thirds of the firm’s capital in two weeks suggests a certain (shall we say) inadequacy on that score. Judging by the way that natural gas prices have bounced back up since the Amaranth meltdown, other traders were happy to put the squeeze on when it became clear that the firm’s trades were not working out. Mr Hunter’s fall from grace is further proof of the adage that in investment, as in the Battle of Britain, ‘there are old pilots and there are bold pilots, but there are no old, bold pilots’.

There is a more fundamental issue too, one that increasingly exercises regulators who worry about the damage that so much highly leveraged trading could do to the financial system the next time something goes wrong — as it surely will. Taking huge leveraged bets on such volatile phenomena as future natural gas prices, where the weather is a major factor, is in truth more akin to gambling than investing, as properly understood.

The lopsided reward structure of hedge funds — heads the fund manager wins, tails the investor loses — actively encourages aggressive managers to take big bets with other people’s money, a factor that industry apologists typically neglect to mention. There is nothing wrong with the hedge fund concept, nor with taking calculated risks, but investors who have the gambling instinct, as Keynes perceptively wrote some 70 years ago, ‘must pay to this propensity the appropriate toll’.

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Asymmetry in the market deals with probabilities and expectations. Probability is nothing more than a math calculation that tries to deal with uncertainty or the unknown, which is of course the future.

Volatility is low. Lower than it has been for, well almost forever. Articles are being written on how low volatility is, what it means, is this a new paradigm, etc.

Obviously this is a time to buy volatility, that should it return, could provide that asymmetrical outcome sought. My favourite target in these circumstances are yield hogs. These chaps buy high yield, mostly junk, for the returns as against say treasuries.

With volatility so cheap…you can buy volatility a long way into the future, to allow time to work in your favour, for pennies. That will be my trade on Monday when the markets re-open. My candidate is prepared.

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Good performance, mediocre results or even downright ugly returns. When it comes to hedge funds, it scarcely matters. Even as some investors begin to sour on these high-priced stock pickers, the top fund managers still haul in enormous paychecks.

The 25 best-paid hedge fund managers earned a collective $11 billion in 2016, according to an annual ranking published on Tuesday by Institutional Investor’s Alpha magazine.

Even managers who had a tough year were able to cash in. Nearly half of the top-25 earners made single-digit returns for their investors, a lackluster sum in a year when the Standard & Poor’s 500-stock index was up 12 percent, accounting for reinvested dividends.

The Top 10 Hedge Fund Earners

The top earning hedge fund managers in 2016, based on estimates of performance fees and each individual’s invested assets.

James Simons
Renaissance Technologies
$1.6 billion

Ray Dalio
Bridgewater Associates
$1.4 billion

John Overdeck
Two Sigma
$750 million

David Siegel
Two Sigma
$750 million

David Tepper
Appaloosa Management
$700 million

Kenneth Griffin
$600 million

Paul Singer
Elliott Management Corp.
$590 million

Michael Hintze
$450 million

David Shaw
D. E. Shaw Group
$415 million

Israel Englander
Millennium Management
$410 million

The top earner of 2016 was James Simons, the former code breaker for the National Security Agency and the founder of Renaissance Technologies, who made $1.6 billion. Ray Dalio, the founder of Bridgewater Associates who is best known for his philosophy of “radical transparency,” came in a close second with $1.4 billion. Further down the list was Robert Mercer, the co-chief executive of Renaissance and one of the biggest backers of Donald J. Trump’s presidential campaign, who earned $125 million.

But some of the best-known names in the industry — including William A. Ackman, John A. Paulson and Edward S. Lampert — failed to make the list. Also missing from the list: women.

The list is based on estimates drawn from each individual’s share of their firm’s management and performance fees. It also takes into consideration each manager’s own capital invested in the funds.

These outsize paydays come at a turning point for the industry. For eight consecutive years, hedge funds have disappointed, underperforming a roaring stock market. In addition, some managers have lost billions of dollars through wrong-footed bets, marking what one hedge fund billionaire, Daniel S. Loeb, called a “catastrophic period” for the industry.

Some frustrated investors headed for the exits in 2016, taking with them $70 billion from the $3 trillion industry. As a result, managers shut their doors and wound down their funds at the fastest rate since the financial crisis in 2008.

Things became so tough last year that big money managers found themselves sitting at the negotiating table with their investors, offering lower fees and better terms for sharing in the returns.

“It’s a moment in time where you’re going to see a cleansing of the hedge fund industry,” said Adam I. Taback, head of global alternative investments at Wells Fargo Investment Institute.

“The industry had a lot of money and a lot of growth all chasing the same investments,” Mr. Taback said, adding that a culling was much needed for the industry to return to its roots.

Despite hedge fund managers’ struggles to beat the market, their compensation has soared over the past decade. The $11 billion payday for the top-25 managers in 2016 is down from $13 billion the previous year, but still more than double what the top earners made in 2000, the first year that Institutional Investor compiled its list. It also dwarfs the sums earned by executives of public companies.

Even the lowest-ranking manager on Alpha magazine’s expanded top-50 list made more money in 2016 than any big United States bank executive, including Jamie Dimon of J. P. Morgan, Lloyd Blankfein of Goldman Sachs and James Gorman of Morgan Stanley, all of who have been criticized for their big paychecks.


James Simons, at $1.6 billion, was the nation’s best-paid hedge fund manager last year, according to Institutional Investor’s Alpha magazine. CreditFred R. Conrad/The New York Times

The key to these large paydays is the fee system known as 2-and-20. Hedge funds typically charge investors 2 percent of their investment annually, regardless of performance. So even in a disappointing year, managers still are paid a handsome sum. In the event they make a profit, the funds take 20 percent of that as well.

Not all hedge funds underperformed in 2016. At the $42 billion Renaissance, where a team of cryptographers, physicists and astronomers parse large volumes of data, the firm’s two public funds, Renaissance Institutional Equities Fund and Renaissance Institutional Diversified Alpha Fund, gained 21.5 percent and 11 percent, respectively.

At Bridgewater, Mr. Dalio’s $165 billion firm, the flagship fund, Pure Alpha, gained just 2.4 percent. But its newest fund, Optimal, gained 7 percent, and its All Weather fund, which charges lower fees, gained 11.6 percent.

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Romanticizing that you are a contrarian when you are indistinguishable from consensus can’t be good.

The quote above comes from Adam Parker, Morgan Stanley’s U.S.equity strategist and director of quantitative research. He set the Internet abuzz this past weekend with a research note in which he wondered why he keeps getting questions from money managers about why stocks rose in the past two months and what will happen next. Most, he said, preface their queries by noting that they are contrarians. They then proceed to ask the same questions:

What is this price action telling you?

What are other investors asking you about?”

How are other people positioned?

What’s the current sentiment?

The belief among many managers is that their perspective is unique or contrarian, while everyone else’s is mainstream, seems to be surprisingly common.

Therein lies the paradox of looking at sentiment data. Everyone thinks of themselves as above average, just like the children of Lake Wobegon. Of course, believing yourself above average is a very average thing to believe.

Let’s use Parker’s comments as a reminder about why it is only when sentiment data hits extremes that it has much use as a signal for the above-average investor.

Recall our earlier admonitions on the topic:

One of my favorite pastimes is dissecting accepted Wall Street wisdom to see if it contains any value for investors or traders. Often, upon examination, the widely held beliefs turn out to be closer to magical thinking than financial acumen . . . One of the more recent examples is the way some analysts use data on sentiment to determine how much an investor should allocate to equities. The problem is that the sentiment data is inconclusive and sometimes contradictory. There is no signal within the noisy data.

Remember, most of the time, the contrarian investor is wrong. The vast majority of the time, the market is the crowd. Hence, making a bet against the crowd means you are fighting the market. The majority of investing dollars are the fuel that moves stocks and bonds along their long-term, multiyear trends. It is only when sentiment reaches terrific extremes that taking a position opposite the crowd can potentially produce a huge score. Even then, the timing is very, very tricky.

As we learned in “The Big Short,” the folks who made the contrarian bet against subprime mortgages and derivatives still had to absorb a lot of punishment before their wager paid off. Even when the market finally moved their way, the index that tracked this asset class took a long time to catch up to the reality of the meltdown.

Right, but even a little early, is a very difficult trade to maintain.

Perhaps this is the reason that not many assets are managed purely on the basis of sentiment. Most of the time, sentiment correctly reflects the positioning of most market participants. It is beta (market-matching returns). Occasionally, it is spectacularly wrong, and that is beta as well. Hence, if you are pursuing an index-based strategy of beta (as I do) and not trying to outperform what the markets give you, there isn’t a whole lot you can do about sentiment.

Taking what the wily Mr. Market offers means that at times you will be buying when sentiment reaches an exuberant extreme, and at other times you will be buying when the market is in the depths of despair. The good news is that regular rebalancing allows something of a contrarian trade, selling a bit of what has run up and buying a bit of what has gotten clobbered. Do that for a few decades and theacademics promise that you will pick up anywhere from 50 basis points to 100 basis points in additional returns. It’s the closest thing to a free lunch in investing.

The big problem with sentiment as an indicator is that the data is often noisy and inconclusive. An even bigger issue is that some managers think they are not part of the crowd that produces this noisy, inconclusive data. This helps explain why so many managers — believing themselves to be contrarians when they are really holding a consensus view — so rarely outperform the market.


August was a torrid month for hedge funds, and other prominent hedge fund managers have disclosed bets that have turned sour. Many funds were crowded in the same stocks that were hammered by the rapid sell-off last week.

Leon G. Cooperman, founder of the $9 billion Omega Advisors, told investors on Aug. 21 that he was down 11 percent for the month. Last week, William A. Ackman surprised investors by announcing that all the gains for his Pershing Square Capital Management hedge fund for the year had been wiped out by “significant volatility” in the global markets. Mr. Ackman’s multibillion-dollar hedge fund was down 7.3 percent for the quarter and 4.3 percent for the year as of Aug. 25.

The world’s largest hedge fund, Bridgewater Associates, led by Raymond Dalio, told investors that its Pure Alpha fund was down 4.77 percent as of Aug. 21. And the flagship fund of Third Point, led by Daniel S. Loeb, is up just 0.6 percent for the year, after losing 5.1 percent in August.

For Mr. Einhorn, this year has been one of bad timing and wrong calls. In July, Mr. Einhorn called his investment in SunEdison “our only significant winner,” adding that the stock had gone from $24 a share to $29.91 a share over the quarter. But in August, the stock took a sharp dive and is now trading at $10.40 a share.

Mr. Einhorn also bet heavily on the chip maker Micron Technology, increasing his stake in the company over the second quarter, according to the latest 13F filings.

Even so, he told investors in July that it was “our biggest loser” in the quarter. “It’s a cyclical business and, regrettably, we missed the turn of the cycle,” he told investors in a letter in July.

Along with gold, General Motors and Apple rank among his biggest long positions, both of which have had uneven returns in recent months. His fund has held a small position in Greek bank stocks and warrants. “Greece has been anything but sun-kissed,” Mr. Einhorn wrote in his July letter.