Why I Left Goldman Sachs: A Wall Street Story (16 page)

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Authors: Greg Smith

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A few days later, I went into Laura’s office again, for my compensation discussion.

This was an annual ritual at Goldman Sachs. In mid-December every employee at the company, high or low, was called into his or her manager’s office and, in a ten-minute meeting, told the amount of his or her PATC (“per annum total compensation”). The amount combined base salary with bonus; bonus per se was never discussed. You did the math yourself, in your head.

Nevertheless, the meetings were known as bonus meetings, and the day was known as Bonus Day, because for everybody above analyst status, the bonus was the Main Event, the big deal, the bulk of your compensation. A lot of people who have been on Wall Street for a long time start getting used to a certain amount of bonus every year, and factor this into the planning of their family lives—things such as private schools, summer houses, nannies, vacations. So when the number doesn’t measure up, it can mean unpleasant conversations when they get home, about things that, to the rest of the world, are considered extreme luxuries. People anticipated the meeting for the whole year; on the day itself, everybody would arrive fifteen minutes early, at 6:30
A.M.
rather than 6:45.

It was an interesting day if you were a student of human nature. The bonus meetings were much like the firings. People were called into a partner’s glass-walled office, and everyone outside could see exactly what was happening. The difference with Bonus Day was that the meetings usually proceeded from the most senior people to the most junior. The partner in charge of your group would sit in his office and, outside, at around 6:45
A.M.
, the phone lines would start ringing. The most senior person’s line rang first. He’d go into the room and then emerge ten minutes later with a poker face. The next person would go in and then, ten minutes later, come out with a poker face. And so on, down the line.

There was an absurd amount of emphasis placed on these meetings. For many people, the session determined a person’s entire self-worth. In many cases, the meeting inflated (or deflated) an already exaggerated ego. But however arbitrary the number handed down by the partner might be, there was also a real poignancy to the bonus meeting. Many people had spent the year working eighty-five-hour weeks, killing themselves for the firm. They expected something in return.

Therefore, as you might imagine, Bonus Day was an emotionally charged time for almost everyone, and not everyone was able to manage the customary deadpan. You saw a lot of antics: You saw people slamming the door as they walked out. You even saw people so upset that they came out and left the office for the day, at 7:00
A.M.
It was the one day in the year that such behavior was acceptable. It was a given that some people were going to be disappointed and some elated. Bobby Schwartz was notorious on our desk for not being able to hide his emotions after a positive bonus meeting. A couple of times, Corey Stevens swore to me, he had actually seen Bobby click his heels.

The one rule that was hard and fast was that the meeting lasted ten minutes, and not one minute more. If you were disappointed with your bonus, you could speak your piece—and then, at the ten-minute mark, the partner would say, in effect, “Thank you, the meeting is finished. Accept it.”

My hopes were high when I entered Laura’s office. They were quickly dashed. Or, to put things into proper perspective, I should say that they were dampened.

She told me that for 2006, my PATC would be close to half a million dollars. By the logic of the outside world, I was being absurdly well compensated for work whose chief benefit was to maintain the robustness of the world’s capital markets—work whose benefit to mankind was limited to the pensioners and foreign governments in the pension and sovereign wealth funds I serviced. By any measure, I should have felt exceptionally lucky and grateful.

But by the warped logic of Goldman Sachs and Wall Street, I was being screwed. Our desk had brought in millions of dollars in revenue that year, and I was well aware that a vice president or managing director could have been paid between 5 and 7 percent of that total, assuming the firm was having a good year overall—which it was. It was true that I had just been promoted from associate to vice president, but, I told Laura, I didn’t think that that fact should have been held against me when it came to compensation time. I had, as she well knew, done at least 50 percent of the heavy lifting on the desk, along with Connors. I could only imagine what he had been paid. He hadn’t clicked his heels when he came out of Laura’s office, but he might as well have.

Laura smiled sadly. “I’m sorry, Greg,” she said. “You’re just too junior at this point for us to compensate you at that level. If we do as well next year, it’ll be a different story.”

The meeting was over. I stayed and worked for the rest of the day.

While the world started seeing a financial crisis only in 2008, my clients were the canary in the coal mine. On our desk, we started seeing a crisis in 2007. Unbeknownst to the broader world, a significant portion of my clients started blowing up in the summer of 2007, in what became a huge “quant meltdown,” and was a foreboding sign of what was to come just one year later.

On Wall Street, the term
quant
typically refers to a geek who has a PhD in a field such as physics, applied math, electrical engineering, or economics. Within the investment banks, quants do all the intellectual heavy lifting: they build financial models to manage risk; they test formulas to price complicated derivatives, sometimes designing structured products so complex and opaque that, even though they may be designed to meet a specific client need, their true worth is impossible for the client to assess. In the meantime, these structured products can generate millions of dollars in revenues for Wall Street firms. It is not the most glamorous work, but make no mistake: quants can be worth their weight in gold; the best ones get paid millions of dollars. Sadly, that’s why actual rocket scientists and engineers leave their professions for the allure of making ten times as much money in finance.

Some quants have gone out on their own and started quantitative hedge funds, relying on their smarts and the models they’ve built to generate outsize returns for themselves and their investors. (When you hear someone on Wall Street talk about a “black box,” there isn’t an actual box. It is the computer model that one of these quants has built.) It was my job to cover the biggest quant funds on the Street—in particular, Goldman’s flagship fund, Global Alpha, run by Mark Carhart and Ray Iwanowski; AQR Capital, run by Cliff Asness; and Bridgewater Associates, run by Ray Dalio. I mostly dealt with the trading desk at each of these hedge funds. In 2007 these three managers alone had close to $100 billion in assets, and saying they ran into a little trouble in the summer of 2007 would be a huge understatement.

The name Global Alpha was very Goldman Sachs.
Alpha
is not just a term that primatologists use to describe the big swinging monkey who rules the pack. In finance terminology,
alpha
indicates the excess return of an investment relative to its benchmark.

Global Alpha had been created in the 1990s by Cliff Asness, who had an aura of being so smart that some people said he could bend spoons just by looking at them. He’d studied under the libertarian economist Eugene Fama and had a doctorate in finance from the University of Chicago. Asness had developed a black-box computer model that combined, in powerful ways, the ideas of value investing (buying stocks, bonds, currencies, and commodities at less than their intrinsic value and holding on till the price rises) and momentum investing (buying or selling securities according to their movement over a certain period). The model, which was designed to seize on anomalies (mispriced securities), produced such impressive results that in 1997, in the midst of the inflating dot-com bubble, Asness left Goldman to start his own hedge fund, AQR Capital.

After he left, the running of Global Alpha fell to his two deputies, Carhart and Iwanowski. They more or less kept Asness’s quant model and tried to improve on it over time. This computer program could decide, more quickly than any human, when to buy and when to sell. For most of the next decade, even during the 2002–2005 recession, Carhart and Iwanowski’s black box kept minting money for the firm, month after month after month. The media speculated that Mark and Ray were earning $20 million a year. Global Alpha became a source of huge pride and revenue for the firm—to the point where our detractors were enviously likening all of Goldman Sachs to a giant hedge fund.

I had a front-row seat to this world: quant hedge funds were a substantial part of my client base in Derivatives Sales, and one of my most important clients was Global Alpha. This may seem strange—how could I have had a client relationship with another part of the Goldman Sachs empire?—but the rigorously enforced Chinese wall between divisions at Goldman Sachs made it possible. On behalf of Global Alpha, I was allowed to execute “agency” business—transparent, commissioned trades of futures, options, or stock on an exchange such as the CME or the NYSE. For compliance reasons, however, I was not allowed to execute “principal” business—transactions in which Goldman Sachs would have to commit its own money to take the other side of a Global Alpha trade. Principal trades might carry an embedded fee, known as the “bid-offer spread,” instead of the flat commissions that agency business carried.
*

For a long time, though, the commissions generated by Global Alpha—which ran into the millions of dollars because of the size of the fund and the magnitude of the trades—were big business for our desk, and for me. And what I saw in the summer of 2007 was that, for one day, then two, then three, then for an entire week, Carhart, Iwanowski, and Asness’s excellent black boxes suddenly stopped working.

The fundamental problem with computer models for trading securities is that they don’t effectively take the outside world into account. They don’t have human thoughts, so psychology can never figure into their calculations. Unlike Gary Cohn in the commodities pit, they can’t look into the whites of people’s eyes and see their fear. And as Gary discovered so successfully, a large part of trading is based on understanding other traders’ emotions. Are they scared? Are they panicked?

In the summer of 2007, fear had started to creep into the markets, and the computer models simply couldn’t pick it up. My colleagues and I began to worry about Global Alpha and AQR when we saw something curious going on with the funds’ vital signs. We used to track how closely these funds’ performance correlated to a benchmark such as the S&P 500 Index (a collection of five hundred stocks that acts as a kind of blood pressure gauge for the stock market). Normally, the quant funds traded within 10 to 50 basis points of the S&P. (A basis point—“bip” for short—is a unit equal to a hundredth of a percentage point: 100 bips equals 1 percent.) In the summer of 2007, AQR and Global Alpha were showing a variance of greater than 250 bips from the S&P 500. Highly abnormal.

We needed to figure out what was going on, and to understand what’s really going on in a quant meltdown, you need to talk to a quant. I was fortunate to have had a great one on our team. Like Cliff Asness, Helga had an economics PhD from Chicago. She spoke with her fellow geniuses at other banks and hedge funds and deduced that the quant funds seemed to be falling victim to their own success: there were just too many of them using the exact same model.

It wasn’t just AQR and Global Alpha that used the model. There were other big funds run by PhDs working with variations on Cliff’s special sauce: there was James Simons’s Renaissance Technologies, and there was D. E. Shaw, among many smaller imitators. As a result of all these companies working off similar models, investment opportunities in heavily capitalized mainstream companies were becoming crowded, so the computers were increasingly seeking out more illiquid and less widely held investments. The more out of the way the security, the fewer buyers and sellers for it, so it can be hard to unwind one of these investments. Although quants do think about the dangers of illiquidity a lot, the mistake they made this time was to fail to imagine that everyone would want to get out at the same time. They were so hypnotized by all the relentless success that they just kept doing most of what the computer model was telling them to do.

If the computer spat out, “Buy 10,000 shares of Lukoil,” the fund’s traders went out and bought the Russian oil company. If the computer said, “Sell May wheat futures,” the traders started selling. The programs kept looking for freakier securities that displayed the anomalies the model was looking for—and the fund managers kept trading. Not enough questions were being asked.

Then, suddenly, everybody’s model was saying, “Sell.” Ironically, this fear in the market was actually being driven by something completely different: emerging jitters in the subprime mortgage market. Nothing to do with math; everything to do with emotion.

But the computers didn’t care. They had known before what to do, and they knew now. Selling made sense to the computer model, and it is very rare that quants overrule the model. The problems were twofold, and they were massive: First, the out-of-the-way securities that the computer models had chosen to unwind were illiquid. Second, since everybody’s model was saying the same thing, there were few buyers.

It was as though somebody had yelled, “Fire!” in a crowded theater and the exits were blocked.

All at once that August 2007, the quant hedge funds’ computer models began imploding. Everyone was trying to unload the same securities at the same time, and as prices went lower and lower, the funds began to hemorrhage money. In addition, investors in these funds panicked and demanded to be cashed out. The one-two punch of the black boxes going haywire and investors making mass redemptions gutted several of my desk’s biggest clients. AQR survived because the firm had launched other, nonquant funds that appealed to retail investors. But Goldman’s own quant fund was not as fortunate. Global Alpha lost more than 30 percent that summer, and the fund never really recovered. Its comanagers quit in 2009, and the firm shut it down in 2011.

The summer of 2007 was highly unnerving.
What is happening here?
everyone wondered.
This market makes no sense.
Colleagues canceled vacations, afraid to be away from the desk until the volatility died down. Wall Street likes predictability, and all at once predictability had gone out the window. Confidence evaporated. Clients stopped trading. It was sad to see the order flows of clients such as Global Alpha decrease slowly but surely, and significantly. Some of these quant funds went from being among the biggest commission payers on the Street to the smallest, with annual commissions plummeting from the millions of dollars to the thousands. The business environment after the summer of 2007 was tough. We were all looking for ways to keep the lights on.

One solution, according to management, was to go elephant hunting. In quarterly internal “town hall” meetings conducted by the heads of the division, there was often an entire segment devoted to giving kudos to salespeople who had done elephant trades.

In good times, transparent, flat-fee commission business was steady and paid the bills; it was a volume business. But if the register wasn’t ringing, as was now the case, new types of business had to be found.

What could make up the fastest for lost revenue? Products that were quick hits, that had very high margin embedded in them. As a general rule on Wall Street, the less transparent a product is, the more money is in it for the firm. Over-the-counter derivatives (OTC, meaning not listed on an exchange) and structured products (complex, nontransparent derivatives with all sorts of bells and whistles) were the trades to go for.

As I’ve mentioned, Matt Ricci, my boss’s boss, had coined the term
elephant trades
to signify those trades where Goldman made $1 million or more in discretionary profit. When you executed one of these trades, the revenue would go next to your name in the form of a gross credit, or GC, another favorite Ricci term. (Matt Ricci had left the firm by early 2007 to go to another bank, but many of his catchphrases remained.)

One client that did an elephant trade was the government of Libya, which gave Goldman $1.3 billion to invest in a product that bundled a bet on currencies with call options on big liquid stocks such as Citigroup, UniCredit, Santander, and Allianz. Placed just before the financial crisis, this bet was one Libya would come to regret. Its $1.3 billion was vaporized in short order—gone. I had to wonder why Goldman Sachs would want to get in bed with Muammar Gaddafi and his exchequer. This was business that the firm probably would have turned away a few years ago, due to the possible reputational damage of dealing with a nation once officially declared a terrorist state by the U.S. government. But now the margins were just so big that it was hard to say no.

But no matter who the firm was dealing with, Goldman and Wall Street were getting really smart at playing on clients’ fear and greed. The sales pitch went something like this: “The world is falling apart. You need a magic fix to protect yourself and help you outperform your peers. You should trade this structured derivatives product that we have specially tailored for you.”

The problem: there was no magic fix. Sure, these clients were foolish to trade these products, but I don’t believe they were educated enough to understand them, and I don’t believe the risks and rewards were presented objectively to them.

———

It was a climate like this one, a climate of fear, that allowed my old colleague Bobby Schwartz to go from zero to hero at Goldman Sachs.

I first met Bobby when I was a second-year analyst, at the beginning of my tenure with Corey Stevens on the Futures desk in late 2002. The Jewish John Kennedy was a third-year analyst, a year older than me, and a bit of a strange guy. He was athletic, with a head of thick dark hair (hence his nickname), but was somewhat inept socially—a lot of what he said came off as just plain goofy. He had an amazing ability to do complex calculations in his head. At the same time, he was extremely absentminded. He was like a numbers nerd in a jock’s body: both halves of the Nutty Professor combined.

Bobby had had a rocky start at Goldman, showing up late for work and occasionally making trading errors—sometimes forgetting about orders, buying instead of selling, miscalculating quantities. If you’d seen him then, you’d have thought,
Here’s a guy who’s bound to get fired
. I thought this. And yet somehow he hung on, slowly learning the art of social interaction and getting a few senior people to like him.

When the clients started panicking in the summer of 2007, Bobby was their guy. His quantitative skills made it easy for him to persuade smart but scared people to do things that made the firm significant amounts of money: dive into extremely complex, structured-product trades. If the client said, “Can you explain that to me?” Bobby could say, “Sure—here’s the math formula.” Then he would walk the client through it—but he would often skip steps because his mind worked so quickly.

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