Felix Salmon

How Goldman Sachs protects itself from a hundred-year storm

Felix Salmon
Oct 29, 2012 16:06 UTC

(Picture from Stephen Foley)

“When it comes to natural disasters,” says Rob Cox today, “there’s no such thing as too much preparation.” He then goes on to extend the analogy:

In advance of Sandy’s march through Manhattan, thousands of sandbags have been stacked in front of the downtown headquarters of Goldman Sachs. It is a picture whose metaphorical value should not be lost on regulators, policymakers, shareholders and the bankers themselves: when the flood comes, there can never be too many sandbags, or capital, to prevent a wipeout.

There are a few problems with this line of argument. Firstly, of course there is such a thing as too much preparation when it comes to natural disasters. Cox praises New York mayor Mike Bloomberg for evacuating Zone A — the lowest parts of the city which are most susceptible to storm surges. But an evacuation of all of Long Island, for instance, or all of Manhattan, would surely be way too much.

At the same time, three’s a good reason why Goldman Sachs needed to get in thousands of sandbags: it’s in that very-high-risk Zone A.

A brief history of Manhattan skyscrapers: they were first built in Lower Manhattan, at the highest possible points around there. Look at the Woolworth Building, say, or the New York Stock Exchange, or the Bank of New York building, or City Hall, or even Chase Manhattan Plaza: all of them are on or near Broadway, which runs up the highest part of Lower Manhattan, which means that all of them are in Zone C. And as skyscraper construction moved north in the 1930s, the same thing held true: the Empire State Building, the Chrysler Building, and all the midtown skyscrapers are all well outside the reach of any storm surge.

But then skyscraper building became more high-tech and scientific, and very tall buildings started to be constructed in Zone A, very close to the water. The architects did lots of clever mathematics, or the actuaries did lots of clever sums, and soon there were dozens of huge buildings in the Manhattan flood zone; the Goldman Sachs headquarters at 200 West Street is merely the most recent.

Now, with a Frankenstorm approaching, the decision to build so close to the water is coming home to roost, and firms like Goldman Sachs are scrambling to try to protect themselves. Hence the sandbags. Which aren’t really preparation; they’re more like a desperate last-ditch attempt to save a multi-billion-dollar headquarters building from very nasty flooding.

And the fact is that Goldman’s sandbags, along with all the other sandbags being deployed up and down the east coast (including in my very own apartment building), are very unlikely to be any use at all. They’re meant to be trying to protect property against a huge storm surge, which could reach 11 feet; the chances have to be very slim indeed that the surge will be big and powerful enough to reach the sandbags, but small and weak enough that the sandbags will suffice to keep it at bay.

Or, to put it another way: when big tail events happen, the old models get broken, and you can’t rely on them any more. That’s true when it comes to building skyscrapers, and it’s also true when it comes to financial crises. In fact, it’s even more true when it comes to financial crises.

Hurricane Sandy is a known unknown: it’s approaching New York, and the only real question is how high the storm surge is going to get. It could be six feet, it could be nine feet, it could be 12 feet. Bank capital, by contrast, is something which disappears in a much less linear fashion. A bank’s capital is just the difference between two huge numbers: its assets, and its liabilities. Its liabilities are fixed; its assets are loans, and derivatives, and other financial instruments which can fluctuate in value dramatically, especially in a crisis. What’s more, assets which banks think of as being ultra-safe — “quadruple-A”-rated super-senior CDO tranches, for instance — turn out to be precisely the assets which implode in value when a crisis comes along, turning banks insolvent overnight.

And that’s just the solvency problem: the bigger issue is liquidity, in a world where banks roll over billions of dollars of debt every day. You can protect yourself as much as you like, but if your lenders for whatever reason stop rolling over your debts, you’re toast. Let’s say you needed to sell lots of US stock today, for instance. Well, thanks to Sandy, you can’t: the stock market is closed. When liquidity dries up, everybody, no matter how prepared they are, is affected, and either central banks manage to step in to save the day, or they don’t. No mere mortal, without a printing press, can hold out.

Financial crises are similar to storms: they require humility, not hubris. Being prepared can be helpful at the margin, but ultimately it doesn’t matter how good your liquidity management teams and risk ledgers and counterparty hedging operations are: if everybody else is blown over by forces beyond their control, then you will be too.

That’s why skyscrapers always used to be built well above the water level, and that’s why we used to have dumb regulations like Glass-Steagal and Basel I, which weren’t very sophisticated, but which generally did the trick. Buildings like 200 West are a bit like Basel III: they’re built with models, so that they can withstand certain forces. But if an unprecedented storm arises, they’re still more at risk than, say, Trinity Church, built more than 150 years earlier. Sometimes, simple common sense (high ground is safer, huge books of complex derivatives can blow up in unpredictable ways) does a lot more good than any amount of sophisticated preparation.


“A brief history of Manhattan skyscrapers: they were first built in Lower Manhattan, at the highest possible points around there…all of them are on or near Broadway, which runs up the highest part of Lower Manhattan,”

It’s also where the most solid bedrock is. Don’t forget that the edges of Manhattan (and most of our coastal cities, for that matter) are mainly landfill. At the time the Woolworth was built, it would have been way too hard to put it on landfill. But, just as in places like Las Vegas and New Orleans, engineers figured out how to support taller buildings in softer ground.

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Who is to blame for Ina Drew’s downfall?

Felix Salmon
Oct 3, 2012 15:47 UTC

Susan Dominus has a big 7,500-word NYT Magazine feature on the rise and fall of Ina Drew, featuring a couple of bland quotes from Jamie Dimon but nothing — nothing on the record, at least — from Drew herself. (We’re told explicitly about four different people who declined to comment when approached by Dominus, including “London Whale” Bruno Iksil and his boss Achilles Macris; Drew is not one of the four.)

The story, as Dominus presents it, is a tragic one. Drew was a highly competent and highly successful trader, who used her deep knowledge of the markets to stay one step ahead of the quants and the rocket scientists who coveted her job. But then she decided that she needed a group of quants and rocket scientists herself, and after she came back from her year-long battle with Lyme disease, which kept her out of the office for most of 2010, she never really regained full control or understanding of what the London office was getting up to.

Dominus actually puts forward two subtly different narratives of what went wrong. The first is that the quants ultimately managed to snow her — that in her final months at JP Morgan, Drew basically didn’t know what was going on in London, and was out of her depth:

At some point in December of last year, a former executive from the group says, Drew checked in with Macris and Martin-Artajo about the position while the two men were in New York. They answered, but the executive, who understood the trade, remembers thinking that they did not give as full an answer as they could have. “I think they glossed over details to the point where Ina knew the product, the size they were trading, but she did not know what the true P.& L.” — profit and loss — “impact could possibly be in a stressful scenario,” he said. She was asking the right questions, he said, but did not seem to be picking up on what was not being said…

By the second week in May, the stress had taken a toll. A colleague saw Drew walking around the executive floor, her mascara smeared. A slight tremor in her hand left over from her illness seemed worse, a physical symbol of her emotional state. Although she still came to work dressed impeccably, she had lost weight and looked somber, almost shut down. The week that the bank decided to make a public disclosure, 20 senior people gathered in a meeting room on the 47th floor. Everyone went around the room and spoke about what they had found out and what still needed to be learned. After about 45 minutes, with the meeting drawing to a close, Drew, uncharacteristically, still had not said a word. Finally, John Hogan, the chief risk officer for the bank, asked: “Does anyone need anything? Need some help?” Drew raised her hand. “I need help,” she said. It was a white flag.

But there’s a second narrative, too — which is that the trades were actually not completely stupid, that they could actually have worked out OK in the end, and that it wasn’t the markets so much as “complicated, interlocking human dynamics” which ultimately did Drew in:

Maybe Drew still believes — as Macris does, according to people at the bank — that the position could have worked out given enough time. Maybe if she had asked the right questions sooner, her traders would have been forced to clarify or she would have sensed danger before it went out of control. Many systems failed and perhaps, too, her judgment.

Drew was someone known for her grasp of the big picture, for internalizing historical trends and economic cycles to the point where her gut instincts were almost always right. She was also someone known for having a personal touch. But in this instance, she seemed incapable of grasping the complicated, interlocking human dynamics that can’t be measured by reassuring models — the idea that a position could be leaked, that the press might bear down, that the regulatory environment could compound all those problems.

This narrative is much less believable. For one thing, pretty much all positions work out “given enough time”. But markets are all about timing. This argument sounds suspiciously similar to the testimony of Joe Cassano to the Financial Crisis Inquiry Commission: hey, if you hadn’t forced me to unwind my positions, my positions would have ended up making money! It’s a pretty silly argument from anybody who’s been in the market for more than about five minutes, and it’s especially silly were it to come from someone like Drew who has been a trader for decades.

And more generally, the whole point of being a trader with gut instincts, rather than a quant staring at computer models, is that you’re reacting to the whole world — the real, messy world, where hedge funds will leak your positions to the WSJ and Bloomberg, and where regulators don’t like nasty surprises — rather than just to the easily-tractable numbers in a VaR model.

With hindsight, it’s clear that Ina Drew was in some ways a human version of one of those clever financial strategies which works until it doesn’t. She was by all accounts an excellent manager with incredibly loyal staff — except when she set up the London office of the CIO, which managed the lion’s share of her billions, and which didn’t respect her at all. As a trader, Drew was extremely attuned to the vicissitudes of the markets — at least until she took her leave of absence, after which her fabled spidey-sense seems to have deserted her.

What’s missing from Dominus’s story is any indication of whether or how Drew was actually managed. Over her years at Chemical Bank, as it slowly transformed and grew into today’s JPMorgan Chase, Drew amassed ever-increasing quantities of money and power. Eventually, as Dominus says, she “had direct control over more money than most players on Wall Street — on the level of the top asset managers in the country, including BlackRock and Pimco”. The trader had become an asset manager, and in a very real sense she was competing with the rest of the bank: before anybody at JPMorgan could lend out a single dollar, they essentially had to persuade Jamie Dimon that the risk-adjusted returns from doing so would exceed the returns which he could get by just giving that dollar to Ina.

Drew was very good at managing and investing the money she was given, and the reward for that skill was that she got given ever-greater amounts of money — over $350 billion, in the end. But at that point, her job had changed both qualitatively and quantitatively from the job she had proven herself good at. Qualitatively, much less of her job involved trading rates in New York, and much more of it involved highly-complex derivatives trades in London, something she was never particularly comfortable with. And quantitatively, running $350 billion is both a blessing and a curse. On the one hand, you can “whale” on the market and push your counterparties around, much like a poker player with a monster stack. On the other hand, if you ever do get forced to unwind your position, you’re toast.

The big difference between Drew and pretty much everybody else on Wall Street is that she never needed to unwind anything: during the crisis, when everybody else was panicking and deleveraging, her positions only grew. In many ways, she was one of the biggest recipients of everybody else’s forced unwinds. But then, when the tables were turned, she proved to be just as human as everybody else.

One man, more than anybody else, had the job of looking at that $350 billion pot of money and wondering whether it was simply too big. And there’s no indication that Jamie Dimon ever did that. Bank clients, borrowers: they had position limits. But Ina Drew never did: she would happily accept all the money Dimon funneled her way. In a weird way, she wasn’t just Dimon’s employee, she was also his counterparty: she was the person with whom he would entrust JP Morgan’s balance sheet when he had nothing better to do with it. And it doesn’t seem that anybody at JP Morgan was worried about that particular counterparty risk — not even when Drew was out of the office for a year, and especially not when she returned to increasingly fractious internal politics.

If there’s a villain in this story, then, it’s not Iksil or Macris or anybody in London: it’s Dimon. The buck stops with him, and yet he’s somehow emerged largely unscathed, with a stock price back in pre-Whale territory and a glossy double-page Annie Leibovitz portrait in Vanity Fair. Dimon’s ego has only grown since the whale crisis: “Honestly, I don’t care what second-guessers say in life,” he tells Dominus. “If anyone in the company knew, they should have said something.”

The question, of course, is whether Dimon would have listened. Dimon needed his own spidey-sense: he needed to be able to tell the difference between vicious internal politics and back-stabbing, on the one hand, and genuine reports of risk-management failures, on the other. When it came to the CIO, he couldn’t do that. And it’s far from clear that he’s learned his lesson.


Smart post. I’m still not quite getting why the $6b hiccup was such a big deal, given the $350b pot. Trading, a two percent loss is not a good day at all, but not the end of the world. Until it is, I guess.

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When investment banks hire risk-takers

Felix Salmon
Sep 15, 2011 21:42 UTC

Matt Taibbi is quite right about the $2 billion of rogue-trading losses at UBS. Basically, investment banks hire for risk-takers; they shouldn’t be surprised when this kind of thing happens.

The brains of investment bankers by nature are not wired for “client-based” thinking. This is the reason why the Glass-Steagall Act, which kept investment banks and commercial banks separate, was originally passed back in 1933: it just defies common sense to have professional gamblers in charge of stewarding commercial bank accounts.

Investment bankers do not see it as their jobs to tend to the dreary business of making sure Ma and Pa Main Street get their $8.03 in savings account interest every month. Nothing about traditional commercial banking – historically, the dullest of businesses, taking customer deposits and making conservative investments with them in search of a percentage point of profit here and there – turns them on.

In fact, investment bankers by nature have huge appetites for risk, and most of them take pride in being able to sleep at night even when their bets are going the wrong way.

Taibbi is receiving some blogospheric pushback, because the term “investment banker” means two very different things depending on the context. On the one hand, there’s investment banking as in M&A advice and old-fashioned merchant banking. A typical sentence would be “traders have replaced bankers in the executive suite at Goldman Sachs”. And then there’s Taibbi’s meaning: investment bankers as opposed to commercial bankers, or people who work at investment banks rather than at commercial banks. These are the people that the Vickers report is scared of.

The fact is that old-fashioned advisory bankers are pretty irrelevant here: the big money in finance has always been where the balance sheet is. And balance sheet is used on the trading floor and in commercial banking. So let’s put the fee-based bankers to one side: it’s absolutely true that investment bankers tend to love risk, even as commercial bankers have historically shunned it.

I’m reading The Devil’s Derivatives right now, Nick Dunbar’s fantastic book about credit derivatives traders. (I’ll have much more on the book when I’m done with it.) In the introduction, he makes this distinction really well, introducing the hotshot traders he dubs “the men who love to win”:

This rare, often admirable, but ultimately dangerous breed of financier isn’t wired like the rest of us. Normal people are constitutionally, genetically, down-to-their-bones risk averse: they hate to lose money. The pain of dropping $10 at the casino craps table far outweighs the pleasure of winning $10 on a throw of the dice. Give these people responsibility for decisions at small banks or insurance companies, and their risk-averse nature carries over quite naturally to their professional judgment. For most of its history, our financial system was built on the stolid, cautious decisions of bankers, the men who hate to lose. This cautious investment mind-set drove the creation of socially useful financial institutions over the last few hundred years. The anger of losing dominated their thinking. Such people are attached to the idea of certainty and stability. It took some convincing to persuade them to give that up in favor of an uncertain bet. People like that did not drive the kind of astronomical growth seen in the last two decades.

Now imagine somebody who, when confronted with uncertainty, sees not danger but opportunity. This sort of person cannot be chained to predictable, safe outcomes. This sort of person cannot be a traditional banker. For them, any uncertain bet is a chance to become unbelievably happy, and the misery of losing barely merits a moment’s consid- eration. Such people have a very high tolerance for risk. To be more precise, they crave it. Most of us accept that risk-seeking people have an economic role to play. We need entrepreneurs and inventors. But what we don’t need is for that mentality to infect the once boring and cautious job of lending and investing money.

When you’re hiring people for the UBS trading floor, you’re hiring men who love to win, congenital risk-takers. And then you surround them with risk-management protocols designed to keep them under some semblance of control. There’s a natural tension there. And if you take the hundreds of thousands of risk-takers working on trading floors in London and Hong Kong and New York and Paris, it’s a statistical inevitability that one or two of them will go rogue every year or so.

Risk-managment protocols are important, but they can never be foolproof, because they’re run by humans. So we really shouldn’t let investment bankers — by which I mean risk-hungry traders with access to billions of dollars of balance sheet — anywhere near the systemically-important balance sheets of our largest commercial banks. Losses like the $2 billion at UBS are manageable. But they’re small beer compared to the entirely legitimate losses made by the likes of Morgan Stanley’s Howie Hubler during the financial crisis. He managed to lose $9 billion, and get paid millions for doing so.

Multiply that by an entire company, and you get Lehman Brothers, or Merrill Lynch. One of the great good fortunes of the financial crisis was that neither of them was attached to a commercial bank at the time; one of the great bad fortunes of the financial crisis is that the sins of Merrill Lynch weigh down BofA’s balance sheet to this day, and are in large part responsible for the fact that, still, no one really knows whether the bank is solvent or not.


FifthDecade, LloydsTSB didn’t have a US boss either in the sense of a company in the US or an american CEO or chairman.

NRK and HBOS and B&B got into trouble over vanilla commercial and retail banking loans that went bad. HBOS was a “victim” of a massive fraud – and i mean actual fraud, not a lazy rubber stamper not ticking all the boxes – that costs it billions of pounds in its SME loans operation. Absolutely sweet FA to do with investment banking.

Frannie were always what people seem to think IBs are, that is government back-stopped hedge funds where the profits went to the shareholders and management and the massive losses were socialised, yet weirdly they are the “victim”.

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How monoculture is like triple-A CDOs

Felix Salmon
Mar 3, 2010 22:37 UTC

Tom Laskawy, of Beyond Green, writes asking for a bit more detail about this bit of my locavorism article:

If you only grow one crop, the downside of losing it all to an outbreak is catastrophe. In rural Iowa it might mean financial ruin; in Niger, it could mean starvation.

Big agriculture companies like DuPont and Archer Daniels Midland (ADM), of course, have an answer to this problem: genetically engineered crops that are resistant to disease. But that answer is the agricultural equivalent of creating triple-A-rated mortgage bonds, fabricated precisely to prevent the problem of credit risk. It doesn’t make the problem go away: It just makes the problem rarer and much more dangerous when it does occur because no one is — or even can be — prepared for such a high-impact, low-probability event.

The point here is that a disease-resistant crop is a lot like a triple-A-rated structured bond: they’re both artificially engineered to be as safe as possible. That would be a wonderfully good thing if no one knew that they were so safe. But if you’re aware of a safety improvement, that often just has the effect of increasing the amount of risk you take: people drive faster when they’re wearing seatbelts, and they take on a lot more leverage when they’re buying AAA-rated bonds.

The agricultural equivalent is the move to industrial-scale monoculture, “safe” in the knowledge that lots of clever engineers in the US have made the crop into the agribusiness version of a bankruptcy-remote special-purpose entity.

But the problem is that bankruptcy-remote doesn’t mean that bankruptcy is impossible: just ask the people running Citigroup’s AAA-rated SIVs. If and when the unlikely event eventually happens, the amount of devastation caused is directly proportional to the degree to which people thought they were protected. When something like that goes wrong, it goes very wrong indeed: artificial safety improvements have the effect of turning outcomes binary.

Essentially, you’re trading a large number of small problems for a small probability that at some point you’re going to have an absolutely enormous problem.

And on a long enough time line, even a small probability is bound to happen sooner or later. Which is something that the likes of Bob Rubin would do well to remember.



What, you don’t like the idea of caribou for breakfast, lunch, supper?

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Measuring total risk

Felix Salmon
Feb 7, 2010 12:41 UTC

Peter Conti-Brown has a new paper proposing the creation of what he calls a Fat Tail Risk Metric, or FTRM. The paper itself is flawed, and the details of how it’s constructed would need to be reworked from scratch. But conceptually, the FTRM I think is a good idea. Here’s Conti-Brown’s abstract:

The paper proposes a legal solution that will create a more robust metric: require mandatory disclosure of a firm’s exposure to contingent liabilities, such as guarantees for the debts of off-balance sheet entities, and all varieties of OTC derivatives contracts. Such disclosures—akin to publicly traded corporations’ filing of 10-Ks with the SEC—will allow regulators and researchers to approximate an apocalyptic, black-out, no-bankruptcy-protection and no-bailout scenario of a firm’s implosion; force firm’s to maintain daily record-keeping on such obligations, a task which has proved difficult in the past; and, most importantly, will open up a crucial subset of data that has, until now, been opaque or completely invisible.

Conti-Brown’s method for coming up with the FTRM involves adding up a firm’s total netted derivatives exposure; the size of its off-balance-sheet vehicles; and its liabilities. That gives a total-risk measure; the FTRM itself is the log of that figure.

There are lots of problems here. For one thing, netting derivatives exposure effectively eliminates an enormous amount of counterparty risk. For another thing, it’s impossible to calculate: if I write a call option on a stock, there’s no limit to how much my contingent liability might be, because there’s no limit to how far that stock can rise. And off-balance-sheet vehicles are just one of a potentially infinite line of entities which remove a company’s legal liability, but where the firm can still end up paying out a lot of money in practice. Think, for instance, the money which Bear Stearns threw at its failed hedge funds, or the money which banks used to make whole the people who invested in auction-rate securities. Those things don’t look like bank liabilities, or even contingent liabilities, until it’s far too late.

But put all that to one side: one thing which doesn’t currently exist, and which would be very useful indeed, is some kind of measure of the total amount of risk in the financial system. A lot of people had a conception, pre-crisis, of some kind of law of the conservation of risk: that tools like mortgage-backed securities simply moved risk from banks’ balance sheets to investment accounts, and therefore, at the margin, actually dispersed risk and made the system safer. What was missed, however, was the fact that total risk was increasing fast, especially as house prices rose and the equity in those houses was converted into financial assets through the magic of second mortgages, cash-out refinancings, and home-equity lines of credit.

Some types of risk are more dangerous than others, of course: if there’s a stock-market bubble, then it’s easy to see that the total value of the stock market, which is the total amount that can be lost in the stock market, has risen a lot. But stock-market investments are a little bit like houses without mortgages: where there’s very little leverage, there’s also relatively little in the way of systemic risk. It’s rare to suffer great harm from the value of your house falling if you don’t have a mortgage.

Still, stock-market bubbles can cause harm, and it’s worth including equities as part of the total risk in the system, along with bonds and loans. That’s one metric which macroprudential regulators should certainly keep an eye on; Conti-Brown’s idea is then basically to try to disaggregate that risk on a firm-by-firm basis, to see which companies have the most risk and to see how concentrated the risk is in a small number of large institutions.

It won’t be easy to do that — indeed, it will be impossible to do it with much accuracy. But even an inaccurate measurement will be helpful, especially if it becomes a time series and people can see how it’s been changing over time. It’s good to know how much risk is out there — and it’s better to know that financial institutions themselves are keeping an eye on that number, and trying to measure it as part of their responsibilities to their regulator.


Conti-Brown here. Felix, excellent critiques. Thanks for engaging the issue. I think, though, that the FTRM survives some, if not all, of “flaws” you’ve identified.

1. Fair point about the netted notional amount eliminating counter-party risks. I’m not wedded to netting derivatives, because the FTRM isn’t about producing with any degree of accuracy the actual dollar amount that an imploding firm would lose — it’s about applying a consistent standard across the entire marketplace that approximates that loss. The goal is to force the loss exposure into the outer boundary of a place where we couldn’t imagine the loss to be bigger. So long as we apply that standard evenly, and there are no obvious risks not included in the metric, then we’ll be on our way to getting the data we need. That’s a long way of saying I think I agree with you — the notional value of the contracts may make more sense than the netted value. I’ll have to look more deeply at those who have argued about the misleading consequences of notional v. netted values (Singh at the IMF has a few papers on this).

2. Re: the impossibility of calculating the sale of calls or any other derivative contract that could go awry to an infinite limit. There are two reasons why FTRM survives this critique. First, we can simply put a coefficient in front of these contracts that will assume away any surprises. For example, we assume that the stock underlying the call grows 1000% in a day, or 10,000% and calculate the FTRM for that contract accordingly. Taleb would say, of course, that even these kinds of exaggerated changes could happen, and there we’d be left holding the bag. That may be true. Maybe stocks can grow in a single day by 10000%. But here’s the second reason why this matters less: if stocks are growing 10000% in a single day, then we’re probably not really in a situation of huge systemic risk. Soaring stocks might cripple the seller of call options, but are less likely to endanger the entire system. Of course, periods of enormous volatility could produce precisely this kind of result, but I’m skeptical for reasons that I’ll save for another time (related to how quickly new calls would have to be sold, at values that would be crippling, in a market of such volatility). Also, the exaggerated coefficient calculation on theoretically infinite exposure contracts would, again, resolve this issue. It doesn’t really matter what the number is, so long as it is applied evenly to all players and all similar contracts.

3. Re: the criticism that off-balance sheet contingent liabilities are ill-defined. I address the issue of Bear Stearns like liabilities in the paper (though not by name, until now: all of these critiques are excellent and will be addressed specifically). The point would be to bring all such contingent liabilities into the FTRM, regardless of whether they are hedge funds, insurance contracts, SIVs, or any other liability that could occur suddenly, and require immediate payment. The value of those guarantees would either be delineated by contract, or would simply be the FTRM of the subsidiary.

4. In response to the first comment to the post, the FTRM explicitly does not assume that we can simply tally up the data and then understand/control all of the complexities of financial contracts and institutions. The main intention here is to probe deeply into the long/fat tails of these kinds of risks, and see what sort of contingent liabilities firms are taking on, and how those values change over time. If we mandate disclosure of these kinds of liabilities (and, as I mention in the paper, I’m not particularly wedded to derivatives and off-balance sheet guarantees alone; I propose them merely as a proxy, and would be delighted to hear of other, more precise proxies), then we can get the data necessary to start teasing out relationships between this kind of risk exposure and bankruptcy, failure, market cap, CDS spreads, and any other relevant variable. This is a proposal, then, for the long-haul: it may not prove its worth for decades. But that doesn’t mean it shouldn’t be disclosed.

One last note about expressing the FTRM in a logarithmic form, rather than in dollar amount. The point here is not only a critique on the current use of VaR as a dollar figure (which is easily decontextualized and misinterpreted), but also because so many of the assumptions in FTRM are near crazy — how can, for example, all a firm’s assets go to zero and its liabilities retain their full book value? The dollar figure that such assumptions produce would simply be unwieldy and non-sensical. The log of that value is meant to express it differently. What that log value actually means won’t be immediately clear. The true import of an FTRM of 11.348, for example, will only be discovered over time and experience.

Apologies for the length of the response. Thanks for engaging the issue. Hopefully others will build on this idea and, eventually, we can get at some of the data that, until now, has either been buried in previous disclosures, or remained completely invisible.

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When Goldman Sachs hates marking to market

Felix Salmon
Feb 3, 2010 13:50 UTC

The most ridiculous sentence I’ve read today comes from Goldman Sachs, protesting against proposals that money-market funds should be marked to market. But first let’s remember what Goldman CEO Lloyd Blankfein has to say about marking to market:

For Goldman Sachs, the daily marking of positions to current market prices was a key contributor to our decision to reduce risk relatively early in markets and in positions that were deteriorating. This process can be difficult, and sometimes painful, but I believe it is a discipline that should define financial institutions. We mark-to-market, not because we are required to, but because we wouldn’t know how to assess or manage risk if market prices were not reflected on our books.

Now read this, from his employee James McNamara:

We do not believe that disclosing shadow prices or market-based prices of portfolio securities would be informative to investors… Investors who perceive a NAV differential between two money market funds may wrongly assume that the fund with the lower market NAV is experiencing a material credit or liquidity problem. This may result in destabilizing — and unnecessary — levels of redemption activity in that fund, which could infect other funds managed by the same adviser or other funds as well. The Commission should be mindful of this type of unintended consequence before adopting regulations mandating the disclosure of market-based NAV’s and market-based pricing of portfolio securities.

When Goldman Sachs reduces its positions as a result of declining market prices, then, that’s a necessary, if difficult and sometimes painful, discipline. When investors in money-market funds do the same thing, however, that’s destabilizing and unnecessary. Alles klar?

David Reilly makes short shrift of such hypocrisy in his column today, and adds something important:

The industry’s case against floating values is that investors would pull cash out of money-market funds because they want investments with a stable value. That, the argument goes, would deprive American companies of a vital source of funding, since money-market funds are big buyers of short-term commercial paper issued by companies.

That is a well-worn ploy from the financial-services industry to counter any change that cuts into business. Banks used this tactic effectively in 2003 and 2004, for instance, to pressure the Financial Accounting Standards Board to water down rules that would have limited banks’ ability to use off-balance- sheet vehicles.

The result was out-of-control securitization and under- capitalized banks, both of which played huge roles in crashing the financial system.

The fact is that higher short-term funding costs for large corporations are a feature, not a bug, in terms of moving money-market funds to floating NAVs. Goldman might like to bellyache about “the diminished supply of short-term credit to corporations” that might result, but short-term credit is always the most systemically-dangerous form of credit, since it can dry up with no warning and cause a major liquidity crisis.

More generally, it’s both silly and far too easy for banks to cry “more expensive credit!” every time that anybody proposes tightening regulations on anything from credit cards to prop trading. Yes, it is true that decades of financial-sector deregulation led to cheaper credit, in the financial industry, in the housing market, in the private-equity world, and elsewhere. This was not a good thing. $1 NAVs obscure the risks inherent in money-market funds, and a sensible regulatory overhaul would put an end to them.


Mark to market makes sense to me, but maybe it needs to be strengthened.
Consider the following. Goldmans bought “insurance” from AIG, but AIG was ultimately unable to fulfil the contract and so the US Govt bailed AIG out and gave Goldmans billions.
Both Goldmans and AIG report quarterly under SEC rules, so at various points in the year they would have been assessing their exposures to each other, presumably under mark to market.
My suggestion is that if either party believes an exposure is greater than a threshold amount (say the lower of 10% of capital and reserves for either party, or $1 billion), then this needs to go to a “clearing” function in the SEC to verify it is reasonable and sustainable.
AIG would probably still have collapsed, and possibly earlier, but I think it would have alerted Goldmans and others to look elsewhere for insurance or rein in their exposures, and it would certainly have cost the taxpayer a lot less.
So I say lets have mark to market, but lets have it applied consistently and then make use of it.

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Crisis chart of the day: The correlation between severity and probability

Felix Salmon
Jan 14, 2010 20:14 UTC

The World Economic Forum has released its annual Global Risks report, which kicks off with this chart:


There’s a key explaining what all these numbers are, ranging from 1 (food price volatility) to 36 (data fraud/loss). But the really scary thing, for me, is the pretty clear positive correlation between severity and likelihood: the trillion-dollar risks all have a significant probability of happening, with the most severe risk of all — a global asset price collapse — being associated with a probability of well over 20%.

That collapse in asset prices is #6; #7 (developed-country retrenchment from globalization) is just as severe, if not as likely. #2 is a spike in the oil price, #5 is fiscal crises, #31 is chronic diseases, and #4 is a slowing Chinese economy.

The report is being published in the run-up to the WEF’s annual meeting, in Davos, where the great and the good will try to convince themselves that they’re part of the solution rather than being part of the problem. But frankly there’s really nothing they can do about the biggest risk of all, that asset-price collapse. In fact, given how rich they are, they’re likely to bear the brunt of it themselves.


Cute chart, Felix. On page 38 of the report it starts to describe how they generated it:

The Global Risks Landscape

The visualisation of risk on the landscape places risks
by severity of impact (measured in US$) on the vertical
axis and the likelihood of occurrence on the horizontal
axis over a 10-year time horizon. The numerical
assessment of these categories of risks is created
through qualitative assessment by the partners of the
report. The risks which appear in the upper right-hand
corner are those with the highest impact and highest
likelihood and are the focus of the narrative of this

I’m a statistician by trade. Whenever I see a nifty graph, I think: “Wow, how would you generate a graph like that?” This was one of those graphs.

Surveying expert opinion is sometimes the best method for generating data because there is no other reasonable option. But expert opinion is prone to biases — man is a social creature; even scientists are prone to the biases of their peers, much more the rest of us.

As a result, I wouldn’t give this graph too much weight. If the experts are generally right, it will indicate some weak tendency toward the result, but as for numbers, I would be reluctant to put one significant figure, much less two sig figs.

One other note: I think the timespan of the figures in the report are meant to span the next 10 years. That is an aid toward understanding what their hypothetical probabilities mean.

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John Paulson’s high-risk hubris

Felix Salmon
Jan 14, 2010 06:17 UTC

Malcom Gladwell is no particular expert on financial markets. But he has said, according to Moe Tkacik, that of all the people he has interviewed, he most identifies with Nassim Nicholas Taleb — in a 7,800-word profile which explains just how hard it is to invest in markets when your strategy involves losing money every day and waiting for a tail event.

With a few notable exceptions, like the few days when the market reopened after September 11th — Empirica has done nothing but lose money since last April. “We cannot blow up, we can only bleed to death,” Taleb says, and bleeding to death, absorbing the pain of steady losses, is precisely what human beings are hardwired to avoid. “Say you’ve got a guy who is long on Russian bonds,” Savery says. “He’s making money every day. One day, lightning strikes and he loses five times what he made. Still, on three hundred and sixty-four out of three hundred and sixty-five days he was very happily making money. It’s much harder to be the other guy, the guy losing money three hundred and sixty-four days out of three hundred and sixty-five, because you start questioning yourself. Am I ever going to make it back? Am I really right? What if it takes ten years? Will I even be sane ten years from now?” What the normal trader gets from his daily winnings is feedback, the pleasing illusion of progress. At Empirica, there is no feedback. “It’s like you’re playing the piano for ten years and you still can’t play chopsticks,” Spitznagel say, “and the only thing you have to keep you going is the belief that one day you’ll wake up and play like Rachmaninoff.”

So I was very puzzled to pick up this week’s New Yorker to find Gladwell write about John Paulson in very different terms. (The story is behind a firewall; it’s not particularly worth paying for, although the magazine as a whole is a fantastic value.)

Gladwell in this essay characterizes Paulson as “The most successful entrepreneur on Wall Street — certainly of the past decade and perhaps even of the postwar era”. I think this involves a very narrow criterion of what makes successful entrepreneur. Later in the essay Gladwell talks about how “people who work for themselves are far happier than the rest of us”, and in my experience hedge-fund managers — who do after all work primarily for their clients — are not in fact particularly happy people. They might not have a single boss telling them what to do, but the pressures of managing other people’s money are immense.

What’s more, any hedge fund manager playing a version of the negative-carry trade has it much worse than most of his peers. Warren Buffett says that the first rule of running other people’s money is don’t lose it; the second rule is “don’t forget the first rule”. One of the reasons Taleb gave for giving up running money day-to-day was precisely the incredible toll it takes when you’re losing money almost every day. Andrew Lahde, another huge winner from the subprime crisis, also quit the business, citing the way in which the stress of the job destroyed his health. Gladwell himself talks about how successful entrepreneurs will deliberately harm their own reputation if it means improving their risk-adjusted returns. That’s not a route to happiness.

And in any event, although success is often measured in dollars on Wall Street, even Wall Streeters don’t end the analysis there. Is Paulson really a more successful entrepreneur than, say, Charles Schwab, just because he arguably has more money? For that matter, Mike Bloomberg has not only founded a hugely successful company which can run very well without his presence; has also made more money than Paulson. Even if Paulson does count as an entrepreneur, it’s not at all obvious how he counts as being more successful than Bloomberg.

But I digress. The point is that Paulson, like Taleb, is a negative-carry kind of guy. Positive-carry investing can take you a very long way, and indeed it’s the foundation of the entire global banking industry, but it’s negative-carry trades which have the ability to score enormous home runs like Paulson’s. Many big hedge-fund managers avoid negative-carry trades, because they feel too much like a gambling habit: you pay out money every day in the hope of scoring a huge jackpot. That’s not the kind of strategy most investors in hedge funds particularly like, and indeed the likes of Taleb take great care to sell their funds as hedging devices — a place to put a small amount of your net worth for insurance purposes — much more than as absolute-return vehicles.

Paulson is no Taleb: his clients are pretty typical hedge-fund investors, including rich individuals who really hate losing money. Which means that his negative-carry trade — buying credit default swaps which obligated him to pay out millions of dollars in annual premiums, with no income attached at all — was extremely risky, from a business point of view. Gladwell quotes Greg Zuckerman explaining that “the most an investor could lose would be 8 percent a year”, while the upside (as we saw) turned out to be astronomical. But it doesn’t take many years of 8% losses — or any losses at all, for that matter — for clients to pull all their money out of your hedge fund.

Paulson was not actively trying to burst the bubble, in the way that George Soros pushed the pound out of the European exchange-rate mechanism with his legendary 1992 negative-carry trade. Instead, he was just the biggest of a long line of investors who saw that there was a housing bubble and tried to find a way to go short. Those who were right but too early disappeared into the footnotes of finance — if they were lucky to get even that. They learned the hard way that “the market can stay irrational longer than you can stay solvent”. Paulson was like them: he felt certain that the bubble was going to burst, but he didn’t — couldn’t — know when, and he simply had to pray that it would happen before his investors deserted him.

What’s more, there was no guarantee that even if the housing bubble did burst, that Paulson was going to make lots of money. To be sure, he had a lovely model, put together by his colleague Paolo Pellegrini, showing that if house prices stopped rising, subprime mortgages were going to suffer enormous losses. But on the other hand, all the banks and credit-rating agencies also had models, showing that the bonds that Paulson was betting against had almost no chance of defaulting. When your model shows one thing, and everybody else’s models show something else entirely, there’s a very good chance that your model is flawed.

Gladwell’s thesis, in this essay, is that Paulson is actually very risk-averse, rather than being a big risk-taker. “Would we so revere risk-taking,” he asks right before introducing Paulson as Exhibit A, “if we realized that the people who are supposedly taking bold risks in the cause of entrepreneurship are actually doing no such thing?”

The fact is that Paulson did take bold risks, on factors which were entirely out of his control: When would the bubble burst? How long could he hold out before his investors deserted him? Indeed, Paulson’s strategy had a Ponzi aspect to it, where he would try to make up losses with new investments: “He bought CDS contracts by the truckload,” Gladwell writes, “and, when he ran out of money, he found new investors, raising billions of new dollars so he could buy even more.”

Warren Buffett has described his most recent mega-acquisition, that of Burlington Northern, as a huge bet on the long-term health of the US economy. That kind of bet has made him more billions than even Paulson can dream of, and it’s a bet made in the positive-sum game of the equity markets. Stocks can and do rise over time, and a well diversified stock-market investor has been able to reasonably expect to see some kind of profit over the long term.

Paulson, by contrast, was playing in the zero-sum derivatives markets. In order for him to make any money at all, somebody else had to lose. If I bought a random basket of derivatives contracts and held them over the long term, my expectation would be that I would end up with less money than when I started.

The amount of sheer hubris involved in Paulson’s trade, then, is enormous. He had to have an unshakeable faith in the infallibility of his own models, in a world where no model is infallible. He had to have entirely irrational confidence that the bubble would burst before he ran out of cash. And he had to do all of this with other people’s money: while he was already personally set for life when he entered into the bet, he couldn’t say the same thing about all of his clients, who didn’t necessarily share his shoot-for-the-moon risk profile.

After all, Paulson’s clients had invested their money with a manager whose returns, Gladwell quotes Zuckerman as saying, were solid, careful, and decidedly unspectacular. Did Paulson decide to put them into a risky derivatives trade with a negative carry just because he’d already made lots of money and was now aiming for posterity? I’m sure all those clients are very happy with Paulson today. But if you’d told them about his strategy while the bubble was still inflating, they might have had a very different opinion indeed.

Update: Zuckerman responds, in the comments.


I thought I’d weigh in on Salmon’s interesting piece, given that it concerns John Paulson, and my recent book, The Greatest Trade Ever.

Were there risks to Paulson’s trade? For sure. Losses of 8% a year for a few years certainly add up. Then there was the reputation risk—if the trade hadn’t worked, Paulson would have been know as the guy who bet foolishly against mortgages after the experts warned him not to. Paulson likely wouldn’t have been able to try anything similar ever again. Further, when the trade finally started to pay off in early 2007 and Paulson piled up billions, he held on to most of his positions rather than cash out, transforming the trade, in my view, into a riskier one. He suddenly sat on huge profits that easily could have evaporated (as some of them did when the subprime market rallied in the summer of 2007).

But the dangers to Paulson’s trade weren’t outsized and it’s fair to say that he wasn’t acting an “extremely risky” fashion. So I disagree with the thrust of the Salmon piece.

Paulson was using credit-default swaps, which have a much more limited downside than a short position on equities or many other negative bets. The embrace of CDS was a sign that Paulson was indeed risk-averse. And it is unlikely that Paulson ever would have faced 8% annual losses for an extended period. If he was wrong on his trade and housing held up or kept rising, most of those who took out risky mortgages would have refinanced their loans (most of which had 2-year teaser rates), ending his CDS trade.

Just as important, Paulson was smart enough — and risk-averse enough — to place most of his subprime bets in a separate fund and lock his investors up for two years in that fund. That way, if he was wrong, it wouldn’t cripple his entire firm. That was good business sense, but also another sign of watching the downside

It’s a misunderstanding to say that Paulson “simply had to pray that it would happen before his investors deserted him.” As I note, they were locked up for two years, at least those in Paulson’s credit funds. And they were well aware of the potential downside, it was all spelled out and quite obvious, since they were buying CDS contracts with set payments. I’m not sure betting billions on the health of the rail industry, a la Buffett, is less risky — or suggests less “hubris” — than entering into CDS contracts with set costs to buy insurance on toxic mortgages.

And to say there’s a “Ponzi aspect” to what Paulson was doing is a bit silly. It’s sort of like saying Pimco is running a huge Ponzi scheme because it takes in money from investors each day, and – get this — uses it to buy investments that the firm likes. Even if new money came it, the returns to Paulson’s investors would have been based on their initial investment and when it was made.

Oh, and Andrew Lahde did complain about his back, and the stresses of his job as a hedge-fund manager. But that’s not why he quit the business. He simply enjoys spending time on the beach with beautiful women. Thanks for taking the time to read my book and for the interesting discussion! Greg Zuckerman

Posted by GZuckerman | Report as abusive

The risk-averse rich

Felix Salmon
Dec 15, 2009 18:36 UTC

What’s the correlation between wealth and risk appetite? I suspect that it’s somewhat bell-shaped: when you’re very poor you can’t afford to take any risks, while if you’re entering the middle classes you often feel that you have to take risks, especially with your retirement assets, if you’re going to have a chance of maintaining your standard of living once you stop working. If you already have more money than you’ll ever spend, however, then you don’t need to take those kind of risks any more, and you start becoming much more conservative again — see for instance the way in which Suze Orman is invested only in wrapped munis.

This big picture can be blurred by the fact that many of the riskiest investments, like venture-capital funds or leveraged hedge funds, are invested in only by the wealthy. But look a bit closer and you’ll invariably find that the investors in those funds are careful to make sure they’re set for life before taking a small percentage of their wealth and investing it in high-risk assets.

But thanks to a new law, we can now see how senior executives invest their money. And it turns out that even diversified stock-market investments are too risky for them:

Top executives at Bank of New York Mellon Corp. could invest their savings in a fixed-income fund that had a 6.6% return in 2008; thanks to electing this fund, Steven Elliott, senior vice chairman, had earnings of $1.3 million on his account, according to filings.

Executives at Cummins Inc. could choose among three options: the return on the S&P 500, “the Lehman Bond Index, or 10 year Treasury Bill + 2%,” according to filings. The executives at the engine maker had a total of $1.4 million in gains on their accounts, suggesting that none of them elected the stock index.

Executives at Illinois Tool Works Inc., a maker of fasteners and adhesives, received returns of 6.1% to 8.4% in 2008, while investments in the employees’ 401(k) lost 25%. A spokeswoman says that so far this year, the average return of employees’ 401(k) plans has been 23%, while the interest credited to the executives’ deferred-compensation plan is just 5.6%.

The WSJ implies, and Ryan Chittum makes explicit, the concept that any executives seeing gains in their retirement accounts were somehow getting special treatment, compared to ordinary employees whose 401(k)s got destroyed. But the bigger point here is that the rich executives are simply availing themselves of the luxury of being able to afford very low risk, modest-return investments. (As ever, Comcast is the outlying villain, guaranteeing senior executives a 12% return on their savings. Yuck.)

I’d also be interested in finding out how much company-specific credit risk is involved in these schemes. A giveaway is the word “notional”:

These deferred-compensation plans generally provide notional investment elections that mirror the returns on mutual funds available in the employee 401(k) plan.

In other words, we’re not talking about actual returns on actual money, here, we’re talking about notional returns on notional money which is really just an unsecured liability of the company to the executive. If the company goes bust, the money disappears — and even if it doesn’t, the money might not ever arrive. Just ask Fred Goodwin and Dick Grasso whether promised retirement funds are certain to become real cash.

There’s something to like about the fact that senior executives have an enormous amount of their retirement assets tied up in unsecured obligations of their employer: it gives them a strong incentive to avoid the kind of fat-tailed risks which could really wipe them out. So I’m not as shocked by the WSJ story as Chittum is. Except for that Comcast factoid, of course.


Then again one has to consider the ‘absolute’ sophistication on the investor and the ‘understanding’ of risk.

Russian Oligarchs – and mini-Oligarchs – who leveraged their assets with borrowed money to invest in yet more risky assets, that were highly correlated with their underlying loan collateral, did well while markets were rising, but got punished hard during the 75-percent decline. Both in terms of margin calls, and being forceably closed-out of those leveraged bets as the price of the underlying collateral declined relative to the value of the debt they needed to repay, and losses in the value of their underlying assets.

They got killed by leverage because they misunderstood the risk they were taking and how soon market sentiment in a real crisis could turn against them. Billionaires became millionaires. Some millionaires lost ‘almost’ all their ‘financial’ assets.

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