Felix Salmon

The truth about Blackstone and Codere

Felix Salmon
Dec 6, 2013 23:19 UTC

I’ve always felt that the Daily Show should do more financial stuff, and there’s no doubt that Wednesday’s piece on Blackstone was funny. But it was also extremely credulous about a single Bloomberg article from October.

Jon Stewart — a man who, according to the NYT, might be “the most trusted man in America” — said that the Bloomberg piece was “unbelievable story” of how Blackstone engaged in “incredibly egregious behavior” which “should be illegal” — strong words, which elicited smart reactions from both Matt Levine and Dan Primack.

In a sign of the degree to which Bloomberg is implicitly trusted, however, all concerned — Bloomberg View, the Daily Show, Fortune — take at face value the core assertion made by Bloomberg News: that Blackstone made a profit of “from 11.4 million euros to as much as 13.7 million” on its Codere trade.

The article attributes those numbers simply to “data compiled by Bloomberg”, but in fact it’s quite easy to see where they came from. Blackstone, according to Bloomberg, “held 25 million to 30 million euros” of credit default swaps on Codere. It then forced Codere into a technical default (repaying a loan two days late) — which triggered those swaps and forced a payout at 45.5 cents on the dollar. Therefore, the amount that Blackstone received on its CDS position was somewhere between €11.375 million and €13.65 million.

But that number is gross revenue, not profit. The profit on Blackstone’s CDS position can be looked at as being the difference between that payout, on the one hand, and the amount that it spent buying the CDS in the first place, on the other. (Although in fact, as we’ll see, it’s more complicated than that.) Unless we have some idea of Blackstone’s cost basis on this trade, we have no idea what its profit was. Bloomberg, however, seems to simply assume that Blackstone’s cost basis for the CDS was zero — that it managed to accumulate all that insurance without paying anything for it whatsoever.

To be sure, Blackstone are smart operators, and I don’t doubt that they’re making a profit on this trade. But we really have no idea how big that profit was.

And in any case the whole thing was part of a much bigger trade, which has yet to be unwound. Primack explains that “in the first half of 2013, Blackstone affiliate GSO Capital Partners purchased debt and credit default swaps in Codere” — in other words, it entered into a basis trade, where it bought debt in a troubled company and also bought insurance on that debt. But Codere was already a deeply troubled company in the first half of 2013, which means that Blackstone would have had to pay some nontrivial amount of money to buy its CDS position in the first place.

So before we take Levine’s lead and admire the “majestic beauty” of the Blackstone deal, let’s wait and see just how profitable it was. We’re not going to know that for a while, since Blackstone is now a major creditor of Codere, which is (still) at very high risk of defaulting on its debt: when the original Bloomberg article was published in October, Codere’s bonds were trading at a mere 53 cents on the dollar.

The way that Blackstone made some unknown amount of money on the CDS leg of its trade, then, was to take a huge direct exposure to Codere on the other side of its trade. It’s still entirely plausible that Blackstone’s current exposure to Codere could be written down sharply, and could even end up being bigger than the profits on its CDS trade.

Two other points are worth making, here. The first is, as Primack points out, that absent new money from Blackstone, Codere was pretty certain to default in any event. As a result, Blackstone can credibly be painted as the white knight here — as the company which managed to find a way to funnel money from the CDS market back into Codere, thereby avoiding a bankruptcy filing. That’s certainly Blackstone’s view: spokesman Pete Rose says that the trade saved jobs at Codere, as well as lots of money for Codere’s supplier-creditors.

What’s more, it’s worth stopping to ask who Blackstone bought the CDS from, in the first place. Not many people are in the business of writing single-name CDS on a troubled company like Codere, and the people who do engage in such transactions tend to be highly sophisticated investors — and indeed are probably engaging in some kind of relative-value trade of their own.

Add it all up, and I really don’t think that what Blackstone did was particularly egregious; there’s certainly no reason to believe that it should be illegal. The Daily Show basically accuses Blackstone of setting fire to Codere so that it could collect the insurance proceeds — but in fact Blackstone’s actions were a large part of the reason why Codere managed to survive. Far from being a pile of ashes, Codere now has a real chance of avoiding liquidation. For a piece of clever financial engineering, that’s an uncommonly positive societal outcome.


Every contract, in the US at least, includes an implied covenant of good faith and fair dealing. Blackstone’s actions as described appear to violate that covenant. Moreover, I wouldn’t be surprised if a motivated prosecutor could find a criminal violation here. It’s disturbing that the article focused on the amount of profit Blackstone made, and not the allegation that the company created the default it collected on. If that is business as usual in the derivative markets, something has to change. Get your moral compass fixed, Felix! Then ask the counter-party how it feels about paying off after Blackstone’s manipulation.

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When the cost of sovereign default plunges

Felix Salmon
Apr 17, 2013 00:11 UTC

CMA is out with its quarterly Global Sovereign Debt Credit Risk Report, which includes this league table:


CPD stands for cumulative probability of default, which means that according to the market, Argentina has an 84.5% chance of defaulting at some point in the next five years. Calculating these probabilities is more art than science: Thomson Reuters puts the 5-year default probability at 71%, but both TR and S&P agree that the one-year default probability is about 50%.

How can that be, in a world where it seems all but certain that Argentina is going to default this year?

Well, for one thing, life is never as sure as bloggers make it out to be. But also, all the standard default probabilities assume that if Argentina defaults, bondholders will get back only 25 cents on the dollar. Which is improbably low. Argentina has both the ability and the willingness to pay its debts; it just doesn’t want to pay holdouts, and is likely to be forced into technical default as a result. This is a long way from the kind of outright debt repudiation that we’ve recently seen in countries like Ecuador, and it’s fair to assume that if and when it defaults, Argentina will try its hardest to ensure that its bondholders (holdouts excepted, of course) get repaid in full on everything they’re owed.

So let’s look at the 1-year CDS, which is currently trading at about 38 points up front. That means that if you want to insure $100 of Argentine debt, you need to pay $38 to do so. On top of that, if Argentina does default, you’re going to need to deliver a bond in order to get your $100 back. The way that default probabilities are calculated, they assume that defaulted bonds are going to cost about $25 each. So if you buy protection for $38, and then spend another $25 on the bond you have to deliver, you’re paying $63 in order to get your $100 payout, for a profit of $37. On the other hand, if Argentina doesn’t default within a year, you lose your $38 insurance policy, for a loss of $38. Since the profit and the loss are roughly equal, that means the probability of default is roughly 50%.

What happens, however, if the price of the defaulted bonds doesn’t fall to $25? Right now the cheapest-to-deliver bond is trading at about $33, and I doubt that it’ll fall much further than that, even if Argentina doest default. In that case, the profit to someone who bought protection drops to $29, while the loss if Argentina fails to default within a year remains $38. You wouldn’t take that trade if the probability of default was only 50%: the implied probability of default now rises to something more like 60%. And remember too that the price of the cheapest-to-deliver bond could conceivably rise post-default, depending on the actions of the Argentine government and how it decided to intervene in the markets. After all, the Argentines have a strong political interest in minimizing the profits of those who have bet against them.

The fact is that the markets know full well that countries like Argentina can and will default occasionally, despite the fact that standard CDS calculations always think of defaults as one-off events. (Just look at the presence on the league table of Argentina, Pakistan, Ukraine, and Iraq, all of which have defaulted in recent years and seem to be reasonably likely to do so again within the next half-decade.)

In a fascinating new paper, for the Deutsche Bundesbank, Klaus Adam and Michael Grill try to calculate an optimum sovereign default strategy: they try to work out when it makes sense for a sovereign to default, and when it doesn’t. And it all comes down to what they call λ, a variable which measures the cost of default to a country. They write:

We first consider — for benchmark purposes — a setting without default costs (λ=0). As we show, the full repayment assumption is then suboptimal under commitment and sovereign default is optimal for virtually all productivity realizations. This holds true independently of the country’s net foreign asset position. We then show for “prohibitive” default cost levels with λ≥1, default is never optimal.

The thing to remember, as you read this, is that λ is a variable, even though for the purposes of the paper it’s treated as though it doesn’t change. And while λ might well be relatively high for a country like Germany, the more that a country defaults, the lower it becomes. After all, a lot of the cost of default is related to the lack of market access, and countries like Argentina have precious little market access even if they don’t default.

What we’re seeing in countries like Argentina and Ecuador, I think, is a rational response to λ falling to levels very close to zero. When that happens, such countries will default quite often — and that frequent default will be baked in to bond prices no matter how healthy the country’s broader economy. As a result, the “official” default probabilities for serial defaulters like Argentina are almost always going to be understated. Although I still think that buying 1-year protection on Argentina right at current levels is probably quite a good bet.

Synthetics rise from the dead

Felix Salmon
Mar 20, 2013 21:24 UTC

Remember synthetic CDOs, the monsters of the financial crisis? Well, according to Mary Childs, they’re “making a comeback”:

Citigroup Inc. (C) is among banks that have sold as much as $1 billion of synthetic collateralized debt obligations this year, following $2 billion in all of 2012, according to estimates from the New York-based lender.

These numbers come from Mickey Bhatia, the head of structured credit at Citigroup, and they’re in stark contrast to the official numbers from Sifma, which show precisely zero synthetic CDOs in 2012, and a total of just $713.4 million in CDOs over the past four years. Read a bit further on, however, and you’ll see that Bhatia is talking about the notional amount of the trades in question; the actual dollar value of the synthetic CDOs being sold is unclear.

As you can tell from the fact that these deals aren’t showing up in the Sifma database, they’re not exactly the same as the creatures which helped to blow up the world in 2008. For one thing, as Childs notes, these new deals don’t bother taking derivatives and turning them into rated securities which can be bought and sold: they’re just bilateral deals with sophisticated clients looking for certain types of exposure.

One such client, quoted in Childs’s piece, is Ashish Shah, the head of global credit at New York-based AllianceBernstein. Encouragingly, he was previously head of credit strategy at Lehman Brothers, which I’m sure reassures everybody who’s entrusting their life savings to the kind of person who says that “a valid strategy for this part of the credit cycle” is to “leverage your exposure to better-quality credit”.

Tom Davidson of Creditflux explained in an article on March 7 that these products — he calls them “single tranche corporate collateralised swap obligations” — are being pushed by “dealers who retain an active correlation book, with Citi leading the charge”. If you don’t know what a correlation book is, my article “Recipe for Disaster: The Formula That Killed Wall Street” might help you out; basically, it’s a place to make bets on whether you think correlations are rising or falling, and/or a place to lose billions of dollars which you never thought were really at risk in the first place.

All of which raises a couple of interesting questions: Why does Citigroup, of all banks, have Wall Street’s largest correlation book? And does anybody think that Citigroup has the risk-management chops to ensure that it doesn’t blow up, a la the London whale?

It seems that what’s going on here is that Citi is trying to hedge its loan book by using credit derivatives; in turn, its credit-derivatives wonks are creating recondite structured products to sell to the buy-side in an attempt to mold their credit risk into exactly the shape they want. I, for one, don’t trust Citigroup — or anybody, really — to be good at this kind of thing: the lesson of the financial crisis, and for that matter of the Senate report into JP Morgan’s Chief Investment Office, is that everybody on Wall Street systematically overestimates the quality of their risk-management skills. If you want to manage risk, do it in simple and obvious ways, rather than by the use of highly-illiquid credit derivatives.

If I were Citigroup’s regulator, then, I’d be asking a lot of questions about whether any of this activity is really necessary or a good idea. Because all of this smells very much like 2006 to me.


I have no problem with this product — as long as the trades are washed through a central clearinghouse or exchange that would guarantee the fulfillment of trades.

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Hero of the day, CPDO edition

Felix Salmon
Nov 5, 2012 18:38 UTC

I’d never heard of Australian federal judge Jayne Jagot before today, but she’s my new favorite jurist, thanks to her decision in a recent court case which was brought against ABN Amro and Standard & Poors.

The coverage of the decision (Quartz, FT, WSJ, Bloomberg, Reuters) concentrates, as it should, on the hugely important precedent being set here: that a ratings agency — in this case, S&P — is being found liable for losses that an investor suffered after trusting that agency.

S&P is appealing the decision, which runs to an astonishing 635,500 words, or almost 1,500 pages: it’s literally longer than War and Peace. At this point, it’s fair to assume that Jagot is one of the world’s foremost experts on structuring and rating CPDOs — crazy derivative instruments which had a brief moment of glory at the end of 2006 before imploding spectacularly during the financial crisis. And helpfully, her decision begins with a 56-paragraph summary of her findings, which lays out exactly how culpable and incompetent S&P really was.

I haven’t read the whole decision, of course, but I have read the summary — and as someone who’s been writing about CPDOs for six years now, I can attest that Jagot’s summary is the single best one-stop shop for understanding what happened with these things. She concedes at the beginning that “the explanation unavoidably refers to complex concepts which are likely to be unfamiliar to those without specialist expertise in structured finance” — this is not easy reading, and if you don’t enjoy nerding out with such concepts, I would never recommend it to you. But if you are reasonably familiar with credit default swaps, Monte Carlo simulations, volatility assumptions, and the like, then I highly recommend you read Jagot’s summary: it’s utterly eye-opening.

The case at heart is a simple one: 12 local councils in Australia bought a bunch of CPDOs, and they only did so because S&P had given those instruments a triple-A rating. S&P, in turn, should never have given the CPDOs that triple-A rating. So it’s S&P’s fault that the councils lost so much money — jointly with ABN Amro, which structured the things.

How does Jagot come to the conclusion that “a reasonably competent ratings agency” would never have given the CPDOs a triple-A rating? Simple: S&P used utterly bonkers assumptions in order to come to its conclusion.

The way that structured finance worked, pre-crisis, was that banks would come up with ever more ingenious ways of structuring products which just qualified for a triple-A rating; they would then try to persuade the ratings agencies that their reasoning was kosher. This case was no different: ABN Amro put together a model, plugged a bunch of numbers into the model, and — presto — the model spat out a default rate which was so low as to justify a triple-A rating. It then showed the model to S&P.

Given such a new concept and product, S&P really should have developed its own model from scratch. It didn’t, however — it used ABN Amro’s model instead. That was bad enough. But worse — much worse — was that S&P didn’t even come up with its own assumptions to plug into the model: it used ABN Amro’s assumptions! Even though those assumptions were unjustifiable.

Bloomberg’s Mark Gilbert explained the concept of model risk at the time:

Derivatives-based trading strategies rely on computer simulations to test their performance under different market scenarios. These simulations typically expect the future to be like the past; the collapse of Long-Term Capital Management LP in 1998 is proof of the danger of using inductive reasoning to extrapolate general laws from particular observable instances.

In my article about the Gaussian copula function, I explained how this played out in practice. CDOs were priced based on the assumption that the future would be like the past, and then when the future turned out to be very different, they blew up.

But as it turned out, if S&P had assumed that the future would be like the past — if it plugged the market realities of the time into ABN Amro’s model — the CPDOs would never have managed to get a triple-A rating. This is where Jagot’s summary is invaluable: it shows that in order to generate a triple-A credit rating, S&P basically had to stick its head in the sand and ignore market realities. Never mind the future, S&P couldn’t even model the present!

Just look at some of the assumptions which S&P made in order to be able to get the longed-for triple-A credit rating. The most glaring is the starting spread — the money investors put into CPDOs was then invested in a synthetic basket of corporate debt. The lower the yield on that debt, the less money the CPDO could make. And at the end of 2006, spreads on corporate debt were very low. When ABN Amro issued a CPDO called Rembrandt 2006-3, the spread in question was just 29bp. But S&P, in rating Rembrandt 2006-3, used a starting spread of 36bp.

The difference might seem small. But S&P knew that with a starting spread of 32bp, where ABN Amro had hedged the deal, the model could not spit out a triple-A rating. And ABN Amro knew that the triple-A rating could not be justified if the starting spread was lower than 35bp. Yet somehow Rembrandt 2006-3 managed to get a triple-A rating with the lower starting spread. How? S&P simply didn’t model it. Instead, they just used an earlier rating, from a deal which never got issued and which was modeled using the 36bp starting spread.

That wasn’t the only place where S&P made unjustifiable assumptions. For instance, check out the number they plugged in for volatility: ABN Amro assumed that the index had volatility of 15%. But it didn’t. In reality, the volatility of the index was somewhere between 28% and 29%. And S&P had recently rated a different product, called LSS, using a volatility assumption, for exactly the same index, of 35%. The problem was that with a volatility assumption of 35%, the CPDO would never rate triple-A. So S&P just discarded that figure entirely, and used ABN Amro’s instead.

Here’s Jagot:

S&P believed ABN Amro’s assertions that the actual average volatility of the Globoxx since inception was 15%. S&P did not calculate the volatility for itself although it could easily have done so and, in my view, was required to do so as a reasonably competent ratings agency…

This assumption as to volatility was unreasonably and unjustifiably low. It did not represent either a reasonably anticipated or expected (that is, non-stressed) input or market condition or an exceptional but plausible (that is, stressed) input or market condition. I am satisfied that but for this error about volatility the CPDO could not have been rated AAA by S&P on any rational or reasonable basis.

So S&P was seemingly incapable of looking at the market to see (a) the spread on corporate debt, or (b) the volatility of the index. Which probably explains another one of their whopping great errors: their assumption for where the index would be over the ten-year lifespan of the bonds. This was a number known as the long-term average spread, or LTAS, and once again, the higher the yield on corporate bonds, the better the CPDO would perform. Remember that when the CPDO was issued, the spread in question was around 30bp. So what did S&P assume it would be in future?

Although there was no rational or reasonable basis for doing so other than the fact that one approach enabled the CPDO to satisfy the AAA rating quantile and the other approach did not, S&P decided that its base case for modelling and rating the CPDO should be an LTAS of 40 bps for one year and 80 bps for nine years… Although the split between 40 bps and 80 bps was itself arbitrary, the most salient point is that the modelling showed that if the assumed LTAS of 40 bps was extended to two years then, all other assumptions being the same, the CPDO again did not meet the AAA rating quantile. S&P then drew a further arbitrary, irrational and unreasonable distinction between the lower LTAS of 40 bps lasting for one year as opposed to two years, the result of which was that on S&P’s approach the CPDO achieved the AAA rating quantile default rate of 0.728% (which it did not if the lower LTAS of 40 bps continued for two years).

There’s really no way of reading what S&P did, here, except that it simply massaged the assumptions it was using until it managed to find something which was consistent with the triple-A rating it wanted. When spreads are at 30bp, what makes you think they’ll average 40bp over one year and then 80bp over nine years? Especially when the index as a whole has never averaged anything like 80bp? It’s simply not a reasonable assumption, and the fact that S&P made it just goes to show how the agency was acting for its paymasters — ABN Amro — and was not putting out reliable ratings at all.

There’s more, too. S&P also plugged into its model an assumption of 7% for something called roll-down benefit, or RDB. Every six months, the CPDO would exit its existing positions, and buy new positions in the index maturing six months later. In general, bonds which mature later have higher yields, so S&P assumed that on average, the new index would yield 7bp more than the old index. And that was an utterly crucial assumption. Never mind the triple-A rating: without the RDB, the CPDO couldn’t even get an investment-grade rating. It wouldn’t even be triple-B.

That was a reasonable assumption, at the time — in terms of the general slope of the yield curve. In general, corporate bonds do tend to yield about 7bp more if they mature 6 months later. But in assuming the 7bp figure, S&P completely ignored the fact that it was comparing apples and oranges: the components of the new index would not always be the same as the components of the old index. After all, the index was an index of investment-grade corporate debt, so if a company lost its investment-grade credit rating, it wouldn’t be included in the index any more.

You’d think that a ratings agency, of all institutions, would be alive to the risk of ratings downgrades. But, it turns out, not so much. ABN Amro, in its model , simply didn’t include what’s known as “ratings migration” — and S&P, similarly, completely ignored it.

The result, in reality, was devastating. Because companies could borrow at such low rates, they were particularly vulnerable to being taken over by private-equity firms which could load them up with cheap debt, devastating their credit ratings. And that’s exactly what happened. A whole series of investment-grade companies, like Alliance Boots, Alltel, and Boston Scientific, got levered up by their new private-equity owners, and lost their investment-grade credit ratings.

When those companies dropped out of the index, the companies which were left had significantly lower yields than the index as a whole did before. As a result, rather than yielding 7bp more than the old index, the new index actually yielded 15bp less. That just devastated the CPDOs, and ultimately led them to default.

Put it all together, and you get a very shocking view of S&P. Here’s the list:

  • S&P used the wrong model input for starting spread.
  • S&P used the wrong model input for volatilty.
  • S&P used the wrong model input for average spread.
  • S&P completely ignored ratings migration.

If S&P had just got any one of these things right, the CPDO would never have gotten that triple-A rating. If it had got them all right, the CPDO would almost certainly not even have been investment grade, let alone triple-A.

S&P was not doing its job, and as a result a bunch of Australian municipalities lost a great deal of money. Jagot has found S&P liable, as she should. Good for her.


Hey Felix,

How do you explain your previous thoughts on CPDOs?

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The HP capital-structure arbitrage

Felix Salmon
Aug 1, 2012 15:49 UTC

Last week, Arik Hesseldahl — a tech writer who’s the first to admit he’s no expert on finance — discovered the wonderful world of credit default swaps in general, and single-name CDS on Hewlett-Packard, in particular. The cost of single-name protection on HP has been going up, and that can only mean one thing: it’s “mainly a barometer of the state of anxiety over its finances and its balance sheet”, he wrote.

Hesseldahl’s corporate cousins Rolfe Winkler and Matt Wirz followed up a couple of days ago:

A $10 million five-year insurance policy on H-P debt costs $260,000 according to data provider Markit. That price has doubled since April and quadrupled since a year ago. While there is no prospect of H-P going under any time soon, bond investors are clearly unhappy about the company’s deteriorating prospects and balance sheet.

But I don’t buy it. For one thing, as David Merkel points out in a comment on on Hesseldahl’s latest post, the HP bond market is not panicking at all: its bond prices remain perfectly healthy. He continues:

The markets for single name CDS are thin because there are no natural counterparties that want to nakedly go long credit risk. Those wanting to nakedly short credit risk therefore have to pay a premium to do so, usually higher than the credit spread inherent on a corporate bond of the same maturity.

And if one or two hedge funds want to do it “in size,” guess what? The CDS market will back off considerably, and make them pay through the nose.

It’s hard to spook the bond market for a liquid bond issuer; it is easy to spook the CDS market.

Why might one or two hedge funds suddenly want to buy protection on HP (and Dell, and Lexmark)? There’s an easy and obvious explanation: their share prices. HP, Dell, and Lexmark are all trading at less than 7 times earnings, at the lowest prices they’ve seen in a decade. They’re all in the fast-changing and volatile technology business. The only certainty here is uncertainty: it’s reasonable to assume that in five years’ time, each of these companies is going to be in a very different place to where it is now.

Which sets up an easy and obvious capital-structure arbitrage. You go long the stock, and then you hedge with single-name credit protection — the only way you can effectively go short the debt. The stock market is deep and liquid enough that you can buy your shares without moving the market; the single-name CDS market isn’t, but no mind. Even if you overpay a bit for the CDS, the trade still looks attractive, on a five-year time horizon.

In five years’ time, it’s entirely possible that at least one of these companies will be toast — in which case anybody who bought the CDS today will have scored a home run. On the other hand, if they’re not toast, the stocks are likely to be significantly higher than they are right now. Basically, the stock price is incorporating a significant probability of collapse, and if you take that probability away, then it should be much higher. And buying protection in the CDS market is one way of effectively taking that probability away.

This kind of trade only works for companies in unpredictable sectors that have low stock prices and relatively low borrowing costs; such opportunities don’t come along very often. But when they do come along, it’s entirely predictable that a hedge fund or two will put on this kind of trade. In no way are such trades a sign that bond investors are worried about the company’s future: in fact, bond investors are not the kind of investors who put on this trade at all.

And so, as Merkel says, reporters should be very wary indeed of drawing too many conclusions from movements in the illiquid CDS market. Sometimes, they really don’t mean anything at all.


Yeah, I think you are right. Might need to update regulation to handle CDS, though. They aren’t quite congruous to options.

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The dangerous Gaussian copula function

Felix Salmon
Jun 21, 2012 13:14 UTC

I’m not sure which is more flattering: someone getting the Gaussian copula function tattooed across his arm, or Donald MacKenzie titling his latest paper after my Wired story on that function.

MacKenzie is a very smart sociologist, who understands quants and copula functions much more deeply than I ever did. (And, like most journalists, I forgot nearly all of what I ever knew about them within weeks of writing the article.) His paper is largely sociological, and I wouldn’t recommend reading it if you don’t like running across phrases like “the beginnings of a typology of mechanisms of counterperformativity”. But the good news is that if you want an English-language translation, Lisa Pollack has done an amazing job of extracting the interesting bits, and there’s no reason for me to try to replicate what she’s already done so well.

Here’s how Lisa sums it up:

The quant community also didn’t, and doesn’t, rate the Gaussian copula model highly at all. In fact, we’re putting that very mildly if the statements from quants interviewed by the researchers are anything to go by.

Furthermore, this was a view held by many before the financial crisis hit. But even in the face of this rejection, the model has stayed in use through multiple crises and is still in use.

I’m going to push back here a little bit. For one thing, although the “many” is implied, it’s never quite stated. Yes, MacKenzie interviewed 29 people before the crisis, including 24 quants. But all the interviews took place after the “correlation crisis” of 2005, when the weaknesses of the Gaussian copula function first became obvious. And in fact MacKenzie cites only one pre-crisis interview with a quant who was very skeptical of the function — and that was with “a quant who had contributed importantly to its technical development”.

My reaction to this is that of course anybody who contributed to the technical development of the Gaussian copula function was highly aware of its weaknesses. In fact, that was a theme running through my article, as summed up in the quote with which I ended it, from David Li, the inventor of the function. “The most dangerous part,” he said, “is when people believe everything coming out of it”.

What I suspect, here, but don’t know for sure because MacKenzie doesn’t really describe his interviewees, is that the people he talked to for this paper tended to be the most senior, worldly, introspective, and successful quants — not to mention the ones who spoke good English. Every bank has graybeards who love to talk about how tools like Gaussian copula functions or value-at-risk are massively inadequate. Those graybeards get a lot of lip-service. But in practice, both senior management and the traders in the trenches end up using the quick-and-dirty measures because they don’t have the time or the sophistication to do anything else.

MacKenzie doesn’t buy the idea of “F9 monkeys” — people who just input a security, press F9, and out pops a price. But he seems much more interested in making a broader sociological point:

In our research experience, the ‘model dope’ exists, but not as an actual person: rather (in the form of, e.g., ‘sheet monkey’ or ‘F9 model monkey’) it is a rhetorical device that actors deploy. It is a way of describing someone as different from oneself: a way of ‘othering’ them. There is no clear evidence in our research of model-dope behaviour or beliefs. (For example, none of the 29 interviews we conducted prior to the crisis contains anything approaching an unequivocal endorsement of Gaussian copula models.) Any satisfactory notion of ‘culture’, it seems to us, must treat the cultural dope and its local equivalents such as ‘sheet monkey’ as forms of othering, not adequate conceptualizations of the actor. Nor are ‘cultures’ equivalent to sets of meanings, symbols and values: they encompass practices, including the most material of practices. Ultimately, culture should be treated as a verb, not a noun (it is unfortunate that use of the verb is currently restricted to its biological sense): people do cultures, rather than culture existing as a thing causing them to act as they do.

I’ll leave the discussions of verbing culture and “othering” to MacKenzie, but I do still believe that on a day-to-day basis, banks were full of people who were happy to just accept whatever the model spit out — especially, as MacKenzie demonstrates, if doing so did wonders for their end-of-year bonus. And while MacKenzie draws distinctions between banks and investors, and between credit-based and asset-backed securitizations, even he admits that there were people managing enormous CDOs who didn’t even know what a correlation model was, let alone have a deeply skeptical attitude towards it.

The fact is, as MacKenzie demonstrates, that there were enormous numbers of people whose bonuses depended on believing that the numbers thrown out by the Gaussian copula function were accurate:

In the early years of the credit derivatives market it was not unusual for traders to sell a deal ‘at par’ – 100 cents in the dollar – when their ‘bank[‘s] system would have told them that this was worth about 70 cents’. A single trade ‘would make [$]20 million of P&L.’)

While it’s possible, in that context, for a determined researcher in an in-depth interview to elicit doubts about the utility of the function from relatively senior people, it’s really not possible for those doubts to get acted on, or even to really exist in the bank itself, as opposed to in discussions down the pub after work.

MacKenzie doesn’t like the way my article simplified the sociology of Wall Street:

The seventh section then returns to the question posed by Salmon’s article, enquiring into the extent to which the Gaussian copula family of models ‘killed Wall Street’. An adequate answer, we posit, demands both a differentiated understanding of that family of models and also, more importantly, a grasp of the fact that a model never has effects ‘in itself’ but only via the material cultures and organizational processes in which it is embedded.

I genuinely have no idea what a “material culture” might be; I’ll leave that kind of thing to MacKenzie. And I’ll admit that the “Wall Street” of my title was a broad church, including not only investment banks but basically anybody who might ever touch a CDO. If MacKenzie wants to make the case that Gaussian credulity was found much more on the buy side and at the credit rating agencies than at the sell side, I’ll happily give him that.

But the fact is that the Gaussian copula function was invidious, and did cause enormous losses all over the world. The way I like to think about it is that value-at-risk allowed banks to ignore tail risk, and the Gaussian copula function did a magnificent job in maximizing that tail risk. The two together were lethal. And while there are surely many other models which inhabit Wall Street in much the same way, I sincerely hope that none of them are remotely as dangerous as the Gaussian copula function turned out to be.


I think this an exceptionally informative, helpful comment thread. For better or worse I have elsewhere represented the following as a fair summary of the relationship of the GCF to valuation of derivatives, as they – and it – contributed to mortgage fraud and the run up and crash in housing prices. Am I wrong?

What caused the Great Recession in 2008? A crash in the money supply, which the Greenspan Fed had allowed to grow based on debt derivatives. When the values of those derivatives crashed, the money supply went too. Why had credit derivatives become so important in financial institutions operations? Because they allowed the institutions to escape effective regulation and evaluation of their investment instruments and behavior, and they were very, very, important to the booking of immediate profit on which the bonuses allocated to traders were based.

How did mortgages become involved in this cycle? Mortgages were the most readily available, least regulated, financial instrument which could be used in the creation of credit derivatives. As the demand for credit derivatives grew, the demand for mortgages grew. Traders needed the derivatives to show “profits”, their institutions needed mortgages to create derivatives, mortgage bankers needed borrowers to sell mortgages, borrowers needed housing values inflated by (essentially) fraudulent appraisals to justify the credit they were obtaining.

At the root, the entire cycle depended on the ability of institutions to create, and traders to sell, financial instruments which were rated very highly by – it is now clear – incompetent and complicit credit rating agencies. Much of the valuation and rating of these instruments was supported by mathematical modelling tools which were always suspect, and have now been shown to be dangerous.

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Could Spain’s bank bailout trigger its CDS?

Felix Salmon
Jun 11, 2012 19:34 UTC

Matt Levine has an excellent post on the latest storm in a CDS teacup, which has been prompted by Europe’s bailout of Spanish banks. If you feel any need to follow this kind of thing at all, here’s basically what you need to know.

Firstly, this bailout is going to add a good €100 billion or so to Spain’s national debt, over and above its existing bonds. That in and of itself makes Spain less creditworthy: the more debt you have, the lower the chances are that you’re going to be able to pay it all back.

More worryingly, for holders of Spain’s national debt, this new bank-bailout debt (which is owed by the country of Spain, remember, since the money isn’t going directly to the banks) carries something known as preferred creditor status. That means that if push comes to shove, Spain will repay the bailout debt before repaying any of its bonds.

To take a simplified example: if Spain has €100 billion in bailout debt due and another €200 billion in bond payments due, and only has €150 billion on hand, then an equitable treatment would be to ask each of its creditors to take a 50% haircut. But with preferred creditor status, Europe will get its €100 billion back in full, and bondholders would have to take a 75% haircut. So holding Spanish bonds just became significantly riskier, this weekend.

Now here comes the CDS angle: if this subordination is written into European law, does that mean that the Europeans just subordinated Spain’s bondholders? Because if they did, then that might count as a credit event, and allow anybody holding Spanish CDS to trigger those CDS and ask to be paid out in full.

There’s lots of discussion here about the difference between the two different places that the money for the Spanish bank bailout might come from: the EFSF, on the one hand, and the ESM, on the other. The ESM’s preferred-creditor status is enshrined in law; the EFSF’s isn’t. In practice, as Joseph Cotterill points out, they behave the same way: European countries will treat the EFSF exactly the same way they treat the ESM, and the EFSF managed to get away haircut-free in the Greek restructuring. But as far as CDS documentation is concerned, what happens in practice doesn’t matter. What matters is the legal theory.

And when it comes to the legalese, it doesn’t get much more impenetrable than this:

“Subordination” means, with respect to an obligation (the “Subordinated Obligation”) and another obligation of the Reference Entity to which such obligation is being compared (the “Senior Obligation”), a contractual, trust or similar arrangement providing that (i) upon the liquidation, dissolution, reorganization or winding up of the Reference Entity, claims of the holders of the Senior Obligation will be satisfied prior to the claims of the holders of the Subordinated Obligation or (ii) the holders of the Subordinated Obligation will not be entitled to receive or retain payments in respect of their claims against the Reference Entity at any time that the Reference Entity is in payment arrears or is otherwise in default under the Senior Obligation. … For purposes of determining whether Subordination exists or whether an obligation is Subordinated with respect to another obligation to which it is being compared, the existence of preferred creditors arising by operation of law or of collateral, credit support or other credit enhancement arrangements shall not be taken into account, except that, notwithstanding the foregoing, priorities arising by operation of law shall be taken into account where the Reference Entity is a Sovereign.

Christopher Whittall has found some lawyers willing to stick their necks out and translate this into English. Basically, there are two ways that CDS can be triggered on the grounds of subordination. The first one is moot, since it applies to entities which can be liquidated, and therefore clearly doesn’t apply to sovereigns. The second one is a bit more complicated, but it basically comes down to the question of whether Spain would be allowed to pay its bondholders if it was in arrears to the ESM. And that’s a question of Spanish law, not European treaty. Unless and until the Spaniards pass a law to that effect, the CDS probably can’t be triggered — which isn’t to say that some enterprising hedge-fund manager somewhere isn’t going to give it the old college try.

Even if the CDS were triggered, however, that wouldn’t be the worst thing in the world. So long as Spain keeps on paying its bond payments on time, the CDS auction, were there to be such a thing, would happen at a pretty high price, and would be no big deal. Think of the auction for Fannie Mae and Freddie Mac: they both had a credit event, but the clearing price was basically par, so holders of CDS didn’t make any kind of profits.

And more generally, the fact that the European Union has been so blasé about these matters is definitely encouraging. Once upon a time, lots of Eurocrats seemed to think that they really had to worry about the CDS market, and whether there was a credit event in Greece. Now, in the wake of the Greek restructuring, they’ve grown up, and they understand that the credit derivatives market is not important enough to worry about or to build policy around. They’re going to do their thing, and the CDS market will react as it may. (Including, perhaps, by just giving up on the whole sovereign-CDS thing entirely.)

In other words, the subordination matters; whether or not the subordination constitutes a credit event under ISDA rules, not so much. As the EFSF and ESM continue to disburse money to the European periphery, that’s the thing to concentrate on most: how much money have they given out, and when do they need to be repaid? Because all of those payments are going to come first, before any payments to bondholders.


The money comes from the EFSF not the ESM, so it isn’t as bad as all that. Unlike the Californian debt crisis of course…

Posted by FifthDecade | Report as abusive

Why banks shouldn’t play in CDS markets

Felix Salmon
May 29, 2012 14:21 UTC

There are a few different ways to look at the seemingly-unstoppable rise of the amount of “excess deposits” that JP Morgan ended up handing to its Chief Investment Office, rather than lending out to individuals and businesses needing loans. Maybe big corporations are flocking to deposit their billions at Chase because they know it’s too big to fail. Maybe Chase just can’t find anybody who both wants to borrow money and is likely to pay it back. Maybe — and more likely — Jamie Dimon funneled increasing sums to the CIO just because the CIO could generate a higher internal rate of return than his plain-vanilla lenders could.

But as Roger Lowenstein explains today, a large part of what we’re seeing here is the way in which lending has morphed into investing. All of us intuitively understand that there’s a difference between lending someone money, on the one hand, and buying a bond, on the other. The former is a bilateral contractual relationship which lasts until the loan is repaid; the latter is an anonymous purchase of securities which can be flipped for a profit (or sold at a loss) after weeks or days or even minutes.

The CIO, playing in the bond and derivatives markets, is very much in the latter camp rather than the former, as you can guess by looking at its name. It makes investments, rather than disbursing loans. But the danger here is not just that $400 billion of JP Morgan’s assets are being put to work gambling in the markets rather than extending loans to clients. The danger is that as the CIO gets bigger, it effectively turns the JP Morgan Chase loan portfolio into an investment, too.

It’s worth quoting Lowenstein at some length, here:

The new Jamie, and the people working for him, don’t have to worry quite so much. They know that if they become uncomfortable with the loans they can always hedge them in the derivatives market…

When JPMorgan hedges, it doesn’t get rid of the risk. That only happens when the customer repays the loan or, say, improves its balance sheet. JPMorgan’s hedges didn’t make the risk disappear; they merely transferred it to someone else.

Jamie had an escape hatch, but hedging doesn’t offer an escape for markets as a whole…

JPMorgan still issues loans but with half an eye on their “hedging” potential, that is, on the willingness of traders who may be halfway around the globe to assume the risk. These traders are less well-placed to evaluate the risk. They don’t know the customer and, of course, they haven’t the faintest concern for character. By habit and preference, their involvement is apt to be brief.

They assume risk by writing a swap contract in the full knowledge that they can unwind it via another swap days or even hours later. Someone may get stuck with the bad coin but, each trader is certain, it won’t be him or her. So the approach of these traders is inherently short-term — too short to invest the time and effort to evaluate the risk. Too short, we might say, to really care.

The plasticity of modern finance — the ease with which institutions can transfer risk — is a major cause of the heightened frequency of meltdowns and increased volatility.

To put this another way: liquidity is dangerous, because it breeds complacency. All you need to do is set a stop-loss, and you’ve protected yourself from large losses. Until, of course, the markets seize up and bids simply disappear from the market altogether. Or until your elaborate and complex hedging operations turn out to have been badly constructed, and you wake up in the morning with a loss pegged at $2 billion and growing.

Alan Greenspan famously said in 2003 that “what we have found over the years in the marketplace is that derivatives have been an extraordinarily useful vehicle to transfer risk from those who shouldn’t be taking it to those who are willing to and are capable of doing so.” In practice, if you look at the actions of the CIO, derivatives were used to transfer risk from those who should have been taking it — big lenders — to hedge funds who make money only when JP Morgan turns out to have fundamentally miscalculated its risk basis.

Entities who want to really take on credit risk are called banks, and they do so by lending. People who sell credit protection in the markets, by contrast, are traders and speculators who trust in the liquidity of the CDS market and who are sure that they will be able to get out quickly if things turn against them. And thus is the CDS market used shunt risks off, unseen, into the tails.

Liquidity isn’t just dangerous in the loan market. Look at houses, which used to be highly-illiquid investments characterized by a long-term relationship between a homeowner and a lender. When did things fall apart? When that relationship was replaced by a frenzy of securitization and refinancings, with even 30-year mortgages lasting for just a year or two before they were paid off by someone flipping their house or deciding they needed a cash-out refinance. The more liquid housing became — the closer it came to being piggy bank, to be tapped for cash at any time — the more dangerous it became, as well.

Lowenstein’s proposed solution — banning credit default swaps entirely — is not going to happen. But it’s a useful lens through which regulators should be looking at the banks they regulate.

Activity in the CDS market, on this view, is a sign of weakness, not strength: it’s a sign that the bank doesn’t have much faith in its own relationships and underwriting standards, and is reduced to having to buy protection from speculators in order to feel comfortable with the risks that it’s taking. Since those speculators, by definition, don’t have remotely as much information about the bank’s borrowers as the bank does, and since they certainly can’t put covenants into loans protecting them from profligacy at the borrower, such trades make very little economic sense in theory.

Regulators should remember this the next time a bank starts boasting about its sophisticated, state-of-the-art risk management systems. Most of the time, those systems involve complex bets in a zero-sum-game derivatives market, where the bank’s counterparties charge a premium for the fact that they’re on the wrong side of an information asymmetry. At best, in such cases, the bank is merely abdicating responsibility for its risks, rather than properly managing them. And at worst, it thinks that it has gotten the credit risk off its books, when in fact it’s just pushed that risk into the tails, where it’s bigger than ever.

Either way, regulators should have precious little time for such antics. They should force banks to go back to basics, instead, and manage their risks the old-fashioned way, by building strong relationships with their borrowers. Lending those borrowers money right now, when such lending is sorely needed, would be a good start.


Commercial banks should never be allowed to use cds, or any other hedge instrument, to hedge their collateralized loan portfolio. For large banks, the size and diversity of its collateralized loans are the hedge. Bankers’ claims that additional hedges are needed are an indication that the loan portfolios are not healthy, and that this is fully recognized by the managers of our largest banking institutions. But how do you hedge against an overall collapse in the collateral (e.g. housing market collapse)? Well, the likelihood of such a collapse is greatly reduced if we don’t have a speculative bubble in the first place. Also, as we have seen, at that point your hedges blow up just as surely as your collateral, and you need to seek relief from taxpayers, who may or may not be in the mood to help you out, and recent banking shenanigans aren’t helping those prospects.

I am in total agreement with KenG_CA — we have way too much investment money chasing far too few investment opportunities. And we’ve had this condition for a long time. Too much of our productive capacity is being squirreled away as private investments (since so much of our output now goes to the wealthy) rather than public investments in infrastructure, education, public health, etc. This goes back at least as far as the dot-com bubble, and I suspect its roots lay partly in the tax restructuring that occurred under Reagan (although I believe there are other causes as well). In any case, the Bush tax cuts were gasoline on that fire, and likely lit the Great Recession conflagration we are now still trying to put out.

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How Bruno Iksil lost $2 billion

Felix Salmon
May 16, 2012 21:46 UTC

In February 2009, Deutsche Bank announced that its Credit Trading desk had managed to lose €3.4 billion in the fourth quarter of 2008, with €1 billion of those losses directly attributable to the bank’s prop desk.

The losses in the Credit Proprietary Trading business were mainly driven by losses on long positions in the U.S. Automotive sector and by falling corporate and convertible bond prices and basis widening versus the Credit Default Swaps (CDS) established to hedge them.

In English, Deutsche Bank had put on a basis trade: it owned credit instruments, like bonds, and it also owned credit default swaps designed to hedge against those loans. And then the trade blew up.

The Deutsche trader responsible for the monster losses was Boaz Weinstein, who eventually left the bank to start his own hedge fund, Saba Capital. His first job, obviously, was to make sure he didn’t blow up a second time. But his second job, it seems, was to use his experience at Deutsche to be able to notice when someone else was about to blow up on a massive basis trade. In this case, JP Morgan.

Go back to early February, long before the articles about the “London Whale” came out in Bloomberg and the WSJ, and you’ll find Weinstein revealing his biggest trade at the Harbor Investment Conference:

The derivatives trader and legendary hedge fund manager said his trade idea is to buy Investment Grade Series 9 10-Year Index CDS (maturing on 12/20/2017).

“They are very attractive,” he explained adding that they can be bought at a “very good discount.”

At the time, Weinstein didn’t know — or necessarily even suspect — that his big trade would involve a zero-sum bet with one of the biggest hedge funds in the world, JP Morgan’s Chief Investment Office. But over time, as he bought more and more protection but the price stubbornly refused to rise, he began to learn just how big the other size of the trade was. Whale big.

Tracy Alloway and Sam Jones have pieced together the best account yet of what exactly JP Morgan was up to. Yet again, it was a basis trade, although this one was horribly complex even by basis-trade standards. Essentially, that CDX.NA.IG.9 position was a second-order hedge, designed to offset volatility in JP Morgan’s first-order hedge, which was designed to offset credit risk in the rest of the bank’s portfolio.

The first-order hedge itself doesn’t make a great deal of sense — Iksil seems to have bought “tranches” of CDS indices, which would pay off if some (but not all) credits suddenly got into trouble. For a bank which had broad economic exposure to European meltdown and/or a US double dip, that seems like a pretty narrow hedge.

But if the first-order hedge is weird, the second-order hedge is downright scary. Do you remember the notorious Howie Hubler trade at Morgan Stanley, where he made a smart bet against dangerous subprime securities, but then put on a much larger “hedge” which ended up costing him $9 billion? Iksil’s trade seems a bit like that:

Because of the mechanics of the trade, in order to achieve a “market neutral” position, whereby JPMorgan hedged the bet against volatility as best it could and offset the cost of its short positions, the bank had to sell far more units of cheap protection on the IG.9 as a whole than it bought on short, more expensive tranches.

Inevitably things started to go wrong. There are two things you can do when something starts to go wrong in the markets. You can unwind your position at a loss. Or you can try to fix it. Iksil, and Drew, chose the latter:

The two legs of JPMorgan’s trade did not move according to the relationship the bank had expected, meaning the position became imperfectly hedged. Like many credit models before it, JPMorgan appeared to misjudge correlation – one of the hardest market phenomena to accurately capture in mathematics.

In order to try and stay risk neutral, the dynamic hedge required even more long protection to be sold. The bank continued to write swaps on the IG.9, causing a pricing distortion that was spotted by more and more hedge funds seeking profit.

The rest, pretty much, is history.

Iksil, we’re told, is going to leave JP Morgan, while taking his own sweet time doing so: “although a spokeswoman for the bank said Mr. Iksil is still employed, he is no longer trading on behalf on the bank and is expected to be gone by the end of the year”. I’m sure he’ll use the intervening months to feel out his chances of being able to raise a few billion dollars for a hedge fund of his own, and weigh them up against simply joining a fund like Saba. Iksil’s now learned a $2 billion lesson — and as Boaz Weinstein can attest, once learned, those lessons can be surprisingly valuable.


@Realist50 Are you trying to say the banks ignored common sense just because the regulators said it was OK? Were they really so unworried about repayment of debt? I don’t think so, and any bank that did had fools in charge. Just because debt is expressed in a single currency doesn’t mean you treat each borrower the same way; the risk of repayment varies. Even at the time of the Euro launch it was widely reported on TV and in the media that Greece had fiddled the figures to get into the currency in the first place. Greece shouldn’t have been let in, but that was a political decision by Germany’s right wing Chancellor, Helmut Kohl and France’s Socialist President, Francois Mitterand who drove the sudden Eurozone expansion.

By hedging risk down (or thinking risk has been reduced), the perceived need for higher interest rates declines, which increases borrowing for overspending countries – but one day comes the reckoning… if the risk had not been hedged, the real risk would not have been disguised, and the degree of danger would have been harder to ignore.

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