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CDS

Another day, another article demonizing CDS

November 28, 2009 in Finance

Bloomberg has a new article up about how the CDS market is starting to crumble – the sort of piece that looks like it’s been sitting on a back burner waiting for an excuse to stoke the flames of derivative fear (thanks, Dubai!).

One of the article’s chief arguments is that “credit-default swaps tied to Thomson SA, the Paris-based owner of film processor Technicolor Inc., paid some holders 30 percent less than those with contracts expiring a day later.” First, however, a technicality – CDS can only expire on four days of the year: the 20th of March, June, September and December (the so-called “roll dates”). Thus, the description of contracts that expire “a day later” is inaccurate. This brings me to a key point: one of the nice things about (most) fixed income is that the terms are… well, fixed. Traders know in advance when a contract will terminate, as well as the quantity (or at least the terms) and timing of any future cashflows. Those definitions extend to procedures in the event of default.

The credit event in Thomson’s case was one of restructuring, the procedures for which were recently updated as part of ISDA’s new “small bang” European protocol. Naturally, in a restructuring event – the debate over whether it should even constitute an event will be left for another post – it may be tough to claim that insurance should pay out. On the one hand, the fixed income product that was being insured just had its terms adjusted (no longer fixed, no longer the same!). On the other hand, the present value of the cashflows should be unchanged which in theory would make investors indifferent (obviously, that’s not the case). Without a cessation of payments, it’s hard to claim that insurance should pay the balance. Therefore, rather than have all insurance contracts pay out uniformly for all referenced bonds, which would fail to capture the odd nature of the restructuring event, traders agreed to set up “buckets” which will each pay out a value deemed fair by market action. The buckets are divided by time to maturity; in Thomson’s case, there were multiple buckets including a 2.5 year bucket, a 5 year bucket, and a 7.5 year bucket. This way, debtholders could more accurately match their insurance claim to the affected bonds.

The crux of Bloomberg’s argument seems to be that a swap maturing on the last roll date of one bucket would pay differently than one maturing on the first roll date of the next bucket (note the semantics – none of this “maturing one day later” language). But under the terms of the protocol, which market participants ratified, that seems appropriate to me. Remember, fixed income means terms are defined in advance. If Thomson had bonds that matured one day before the restructuring was announced, then those bonds would pay out par while bonds maturing the next day would presumably have crashed on the revelation that there isn’t cash to pay them in full (remember, unlike CDS, bonds can and do mature on any day of the year). That actually just happened with the Nakheel December 2009 bonds, which were trading well above par before Dubai’s surprise announcement brought them back to the 70’s overnight. In sum, the fact that some fixed income instruments are treated differently than other is not alarming – maturity and seniority are prime components of the fixed income market and naturally force bonds into differently performing buckets on a daily basis.

So if we can’t fault CDS for the fact that one contract pays out differently than another, maybe we can find something to be upset about because the 2.5 year bucket recovered 30% more than the 5 year bucket (in CDS terms, recall that recovering more means the contract pays less: if a bond recovers its full value, the insurance would pay out nothing at all). But here’s a secret: the disparity arose because of problems in the underlying cash market, not the derivatives market! Okay, it’s not really a secret. Euroweek figured it out well before the auction even took place:

Most of Thomson’s deliverable obligations are thought to be complex private placements and little is known about their documentation. It is possible that none will be deemed eligible for delivery.

CDS payouts aren’t determined by a bunch of traders standing in a room shouting – they are set by the market-clearing price on bonds (“deliverable obligations”) that are submitted by CDS holders in return for insurance payouts. It’s a straightforward system: CDS buyers purchase bonds in the market, then give them to the CDS sellers in return for their par value. The net payment is therefore par less the bonds traded price, or recovery. If there are few bonds available, or little transparency or liquidity about those bonds, then their market price will fluctuate for technical reasons rather than fundamentals. This phenomenon can occur with any traded security: short squeezes are perhaps the most familiar example. That’s exactly what happened with Thomson – so few of the short-dated deliverables were available for public trading that the market clearing price was bid up extremely high. In the next bucket, bonds were more liquid and so reflected recovery more accurately.

Euroweek described it nicely (again, well before the auction even took place):

…it is very likely that there will be a shortage of deliverable obligations and a scramble to get hold of what is available. The consequent short squeeze will drive up prices and the recovery rate much higher than it would otherwise be — good news for protection sellers but bad news for the buyers. For example, the most likely and liquid deliverable obligation, according to Citigroup analysts, is the June 2012 revolver, which would fall in the 2-1/2 to five year maturity bucket. It has been pushed from a 40% price to 70% in recent days.

But the real difficulties lie in the 0 to 2-1/2 year bucket. Thomson, a French media firm, was a regular member of the main iTraxx Europe Index from series 1 to series 7 and was thus much referenced in index CDOs. There are a lot of single name hedges against the name with maturities between now and 2012, putting particular pressure on the 0 to 2-1/2 year bucket.

I’m still waiting for the article titled “CDS auction goes smoothly despite problems in bond market.”

To Bloomberg’s credit, there is a deserved debate over restructuring events and CDS more generally outside the Bang protocols (and even within them). Moreover, the Thomson example – though I disagree with the author’s specific points – is a good one for demonstrating how settling CDS remains a mystifying and seemingly arbitrary process. There is no doubt that further clarity is needed, for the benefit of all market participants. The rest of the article deals with the lack of transparency into what qualifies as a credit event and murkiness following that declaration. I have to point out that though the arguments there have merit, their very existence demonstrates that CDS by nature doesn’t force companies into default or anything along those lines – otherwise these arguments would be settled by a simple imperative to bankrupt the firm.

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Measuring aggregate risk in CDS markets

September 25, 2009 in Finance, Risk

The ECB recently published this lengthy report (PDF link) on the state of the CDS market, with particular focus on counterparty risk. It is well worth a read for either a cursory overview or more in-depth look at the mechanics and concerns of that market.

Section 3.4 regarding counterparty risk measures was especially interesting to me. Consider the passage on the use of gross outstanding notional as an indicator of risk (emphasis mine):

The notional amount of a credit default swap refers to the nominal amount of protection bought or sold on the underlying bond or loan. Notional amounts are the basis on which cash flow payments are calculated.

The gross notional amount reported by the BIS is the total of the notional amounts of all transactions that have not yet matured, prior to taking into account all offsetting transactions between pairs of counterparties. As outlined above, gross notional amounts thus represent a cumulative total of past transactions. Using gross notional amounts as an indicator of counterparty risk may be misleading, as many trades are concluded with a single counterparty.

Once negotiated, CDSs bind both counterparties until the agreed maturity. Market participants basically have three choices when increasing or reducing their CDS exposures.

First, they can terminate the contract, provided the counterparty agrees to the early termination. Second, they can fi nd a third party to replace them in the contract, provided the counterparty consents to the transfer of obligations (“novation”). As a third option, dealers that want to unwind or hedge their positions can also enter into offsetting transactions, sometimes (though not necessarily) negotiated with the same counterparty as the hedged deal. The third solution is used extensively, and so the number of trades has surged, resulting in an increase in total gross notional amounts. Indeed, this technique, by contrast with the other two, does not eliminate previous deals and instead adds them together. The end result is that external market commentators tend to pay too much attention to the gross market values in relation to other measures of the real economy such as GDP, whereas net notional amounts, where accounted for, may be downplayed or perceived as being very low or moderate in relative terms given the huge gross notional amounts outstanding.

The gross notional amount reported by the BIS is the total of the notional amounts of all transactions that have not yet matured, prior to taking into account all offsetting transactions between pairs of counterparties. As outlined above, gross notional amounts thus represent a cumulative total of past transactions. Using gross notional amounts as an indicator of counterparty risk may be misleading, as many trades are concluded with a single counterparty.

Once negotiated, CDSs bind both counterparties until the agreed maturity. Market participants basically have three choices when increasing or reducing their CDS exposures.

First, they can terminate the contract, provided the counterparty agrees to the early termination. Second, they can fi nd a third party to replace them in the contract, provided the counterparty consents to the transfer of obligations (“novation”). As a third option, dealers that want to unwind or hedge their positions can also enter into offsetting transactions, sometimes (though not necessarily) negotiated with the same counterparty as the hedged deal. The third solution is used extensively, and so the number of trades has surged, resulting in an increase in total gross notional amounts. Indeed, this technique, by contrast with the other two, does not eliminate previous deals and instead adds them together. The end result is that external market commentators tend to pay too much attention to the gross market values in relation to other measures of the real economy such as GDP, whereas net notional amounts, where accounted for, may be downplayed or perceived as being very low or moderate in relative terms given the huge gross notional amounts outstandingNotional amounts are the basis on which cash flow payments are calculated.

The gross notional amount reported by the BIS is the total of the notional amounts of all transactions that have not yet matured, prior to taking into account all offsetting transactions between pairs of counterparties. As outlined above, gross notional amounts thus represent a cumulative total of past transactions. Using gross notional amounts as an indicator of counterparty risk may be misleading, as many trades are concluded with a single counterparty.

Once negotiated, CDSs bind both counterparties until the agreed maturity. Market participants basically have three choices when increasing or reducing their CDS exposures.

First, they can terminate the contract, provided the counterparty agrees to the early termination. Second, they can fi nd a third party to replace them in the contract, provided the counterparty consents to the transfer of obligations (“novation”). As a third option, dealers that want to unwind or hedge their positions can also enter into offsetting transactions, sometimes (though not necessarily) negotiated with the same counterparty as the hedged deal. The third solution is used extensively, and so the number of trades has surged, resulting in an increase in total gross notional amounts. Indeed, this technique, by contrast with the other two, does not eliminate previous deals and instead adds them together. The end result is that external market commentators tend to pay too much attention to the gross market values in relation to other measures of the real economy such as GDP, whereas net notional amounts, where accounted for, may be downplayed or perceived as being very low or moderate in relative terms given the huge gross notional amounts outstanding.

It’s easy to come up with an example which illustrates the problems with gross notionals (the ECB’s “third solution”):

Dealer A sells $1mm of protection to Fund X. The gross notional at this time is $1mm, and the maximum that could be lost (in an extreme case with 0% recovery and the original contract transacted at a zero spread) is also $1mm. Now Dealer B sells $1mm of protection on the same name to Fund Y. The gross notional is $2mm, and so is the maximum loss in the market. But what if Dealer B had sold CDS to Dealer A instead? Then the gross notional would still be $2mm, but only $1mm could be lost, as Dealer A has hedged its position completely. Thus, gross notional has overstated the risk present in the marketplace.

Net notional is a much better measure, but, in line with my parenthetical aside, does not quite capture the risk at hand; it only does so under extreme circumstances. (It also isn’t nearly as dramatic a number, so the media is more loathe to deal with it.)

In my experience, jump to default (JTD) and jump-or-bleed to safety (JTS) measures are instructive methods for evaluating risk. Most commonly, these measures are evaluated with respect to the reference issuer, but they are easily applied to the counterparty as well. However, calculating them in aggregate – at the market level – requires knowledge of the various contracts’ market values, data which is not presently made public (gross and net notional values are available from the DTCC).

Finally, the ECB makes the salient point that any market-wide counterparty risk measure must account for collateralization. There is some ambiguity there, however, because a contract which is fully collateralized on a mark-to-market basis still has considerable counterparty risk in a jump event. Frequently, protection buyers may find that to be wrong-way risk, meaning that the exposure to a counterparty is inversely related to that counterparty’s credit rating. For example, a counterparty defaults, driving credit spreads wider (a profitable event for the protection buyer) but also making other counterparties more likely to default (a very bad thing for the protection buyer).

In failing to find a clear, universal or simple risk metric for this market – which I don’t think is necessarily preferable given the over-reliance and under-comprehension placed on VaR after its wide dissemination – we may find that the best outcome is to strive for transparency in understanding. A strong education in the mechanics and risks of complex markets is an important step forward and a necessary prerequisite for market participants in both direct and regulatory roles.

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CDS Markets, briefly (or not so briefly)

July 15, 2009 in Finance

In response to Daniel Indiviglio’s call for “someone who understands the derivatives market,” I posted the following comment on the Atlantic Business blog – and I reprint it here not just because it turned out a surprisingly complete thought, but because I’m a glutton for blogging laziness:

The CDS market works similarly to any other market: traders announce prices (privately or otherwise) at which they are willing to trade, and if two traders’ levels agree, a trade may be executed. These levels may be informed by quantitative models, gut feelings, even sheer necessity – but the mechanism by which trades are conducted is quite straightforward: two CDS traders agree to a trade, at which time their respective firms enter a legally binding contract to exchange the necessary cashflows. That part takes place off the desk, however.

There are two predominant forces in the CDS markets – again, as with most markets – the “buy side” and the “sell side”. The buy side refers to those traders looking to place directional bets; they look to trade securities as advantageous prices, hold them for some time, and then sell them at a profit. The sell side, by contrast, is not interested in taking risk; it merely wants to service the buy side and be compensated for doing so. To accomplish this, sell side traders seek to simultaneously buy and sell the same security, capturing the difference in price for themselves and taking no exposure to the security in the process. The market dynamics arise out of this tension – buy side traders looking for “good” prices, and sell side traders seeking to capture a “bid ask” spread. Increasingly, however, sell side traders are starting to resemble the buy side as banks take on proprietary risk (evidenced most recently by Goldman Sachs).

It would appear that most of the regulatory concern with the CDS market is not about *how* contracts are traded, but rather the management of those contracts themselves. The CDS market is an “over the counter” (OTC) market, meaning transactions are executed between two consenting parties rather than via an anonymous exchange. In any OTC market, there is an advantage in being “the counter” – or the sell side. This is because the sell side 1) has an information asymmetry in that they see much more of the market than any individual buy side trader and 2) can adjust their price – even away from the “fundamentally correct” price – to take advantage of the supply or demand they perceive in the wider market. Thus, one of the first regulatory aims is increased price transparency.

A second concern is how each trader’s firm treats the contract after it has been traded. AIG was not required to post collateral on their sold CDS, and consequently was ruined when they discovered they had sold more contracts than they had collateral to back them. Lehman’s bankruptcy locked away funds owed to other firms, because they did not only have exposure to the firm they traded CDS *on*; they had exposure to the firm they traded *with* as well. The regulatory solution to the issue of counterparty risk is to create a CDS clearinghouse, which will standardize all collateral disputes and decrease counterparty risk throughout the market.

Finally, people are afraid that CDS are mathematically complex, difficult to price products – and to an extent they can be. Nonetheless, this fear arises with many derivatives, because they do not trade on an open market and do not represent “pure” parts of the capital structure (as if companies only issued simple stock and bonds in the first place). A response would be that having a mathematical grounding should actually increase people’s faith in receiving an honest price, for in the absence of a highly liquid market, how else can you determine whether a price is fair? Thinly traded stocks may jump tens of percents each day, because there is no price discovery mechanism – and without a grounding in transparent math, who can say what the proper level is? Unfortunately, many attempts to explain CDS veer into complex math simply because they can, not because they need to. CDOs, while more complex, have a similar problem (though I recently tried my hand here).

I believe that these three items: OTC, counterparties, and scary math have greatly contributed to the demonization of CDS contracts. As Petrobull stated, the incestuous nature of many trading desks and sometimes-difficult trading vocabulary only add to the confusion. Moreover, we have seen the concrete and disastrous toll that derivatives can have in AIG and Lehman, among others, cementing (or necessitating the invention of) the error of these market’s ways in our collective psychology.

Indiviglio was last seen on TGR here.

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Spotted: a free lunch

June 11, 2009 in Finance

The internets are buzzing about the CDS trade that netted small brokerage firm Amherst a nice profit at the expense of Wall Street giant JPM.

I may be missing something, but it seems to me that the risk hasn’t disappeared (as is being implied), it has merely been transferred from the mortgage originators (or whomever they sold the bonds to) to Aurora, the mortgage servicer. It’s a key distinction.

Basically, as I see it, Amherst raised a lot of money based on the fear of default and used those proceeds to eliminate the possibility of default as it pertains to the original risk-takers. It so happens that they were able to “raise” so much money that they ended up being paid to perform this service (such as it may be). They did not, however, eliminate the risk of mortgage default. Aurora now holds those bonds and is on the line if homeowners should fail to pay; I’m sure Amherst has passed on enough of the profit so that Aurora can not lose money on the deal.

So the “risk” still exists nominally, but so much profit was extracted from the trade that there is no downside risk to the arbitrageurs.

Ah, there’s the key word that I haven’t seen in any article – arbitrage. Not often you can point to such an obvious example in plain daylight, but nonetheless I’m surprised no one is calling this what it is. Amherst was able to sell (potentially unlimited) amounts of CDS at a price which was obviously too high. At a lower price, simple cash constraints may have prevented them from exploiting the trade, since no counterparty would sufficiently pay them enough to call the entire bond issue.

The system isn’t broken; on the contrary, this is it in action! To all you Markowitz mean-variance CAPM scholars out there: you need events like this to ensure equilibrium! Unless, of course, you assume them away (or worse, into the mysterious realm of “endogenaity”).

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Deconstructing the Gaussian copula, part I

June 5, 2009 in Finance, Math

(Parts II, II and a half, and III of this series are also available.)

Newsweek has a new article about Paul Wilmott called “Revenge of the Nerd” which I really enjoyed, with two caveats.

In its opening the article compares quants to aeronautical engineers who design faulty planes (CDOs). The author observes:

Yet while aeronautical engineers who willfully designed a faulty plane might be on trial for criminal negligence, Wall Street’s math gurus are, for the most part, still employed. Strangely, the banks need quants more than ever right now.

But where is the logical conclusion of the aeronautical metaphor, that other engineers would be needed to fix the planes? In that framework, there’s no contradiction.

But that point is minor. Here’s what really bothered me (my comments are inserted in bold):

In 2000, the CDO market was jump-started by David X. Li, who, while working at JPMorgan, created the Gaussian copula function (no, he didn’t), a formula for determining the correlation between the default rates of different securities (no, it’s not). In theory, the model tells you the odds that, if one CDO goes bad, others will too (no, it doesn’t). The apparent genius of the Gaussian copula is its abstraction (true, but not in the way the author means). Rather than relying on the immense amount of data used to figure the odds that a CDO might default (there is no such data; issuers default, not CDOs), Li appeared to have discovered a law of correlation (no, he didn’t). That is, you didn’t need the data; the correlation was just there. Armed with it, quants could price CDOs much faster, and traders could buy and sell them at record speeds. Gaussian was rocket fuel for the CDO market (“Gaussian” is an adjective, not a noun). The global volume of CDO deals went from $157 billion in 2004 to $520 billion in 2006. As more banks got in on the game, the once large profit margins started to shrink. In order for banks to make the same kind of returns, they had to pack more and more loans into a CDO, essentially making bigger bombs. Li was on his way to a Nobel Prize when the world blew up (no, he wasn’t).

I have no problem with the simplification of difficult topics (in fact, I encourage it). I also have no problem with bashing Gaussian copulas as applied to CDO’s (the argument was featured in my thesis years ago). But I have severe issues and frustrations with poor reporting of false information. Will 99% of this paragraph’s readers realize it’s incorrect or even care? Of course not! But it doesn’t make it all right.

Deep breath. Ready to go deeper?

This paragraph seems to be lifted largely from a recent Wired article (my response to that article would evolve into my “models are just the tool” tirade). Anyway:

“David X. Li…created the Gaussian copula function.” The Gaussian copula is rooted in research from more than 250 years ago. In fact, Gauss – a prodigal mathematician whose influence extends far beyond the bell curve – died in 1855! It’s unclear when the first bivariate extensions were arrived at, but Wikipedia notes that it must have been developed by 1872. The copula itself would not be described until 1959, but almost immediately mathematicians used it to decompose the multivariate normal distribution into a pairing of Gaussian marginals and something the new vocabulary termed a Gaussian copula. All David Li did was pair the copula and CDO pricing for the first time.

“…a formula for determining the correlation between the default rates of different securities.” Copulas describe the dependence structure of random variables. Correlation is a way of condensing the information contained in the copula down to a single number. The sentence as written suggests that the copula is used to measure correlation when in fact it is the other way around. In fact, you can not even create a Gaussian copula until after you decide what correlation to use.

“In theory, the model tells you the odds that, if one CDO goes bad, others will too.” I assume the author meant to write “if one issuer goes bad” rather than “if one CDO goes bad”, because the Gaussian copula as applied to CDO’s describes the issuers within the CDO, not CDOs to each other. In this framework, the sentence is correct: copulas describe the dependence structure, which essentially means “how one issuer relates to other issuers.” In this case, the thing being measured is default probability.

“The apparent genius of the Gaussian copula is its abstraction.” This is a true statement as it stands: the brilliance of the copula function is that it abstracts the dependence structure from the marginal distributions, meaning the dependence of, for example, two dice numbered 1-6 has the same copula as the behavior of two dice numbered 2-7. Before the development of the copula, the 1-6 dice would have a completely different function than the 2-7 dice, because one would have to account for the marginal differences while defining their dependence.

However, the abstraction the author is referring to is that “you don’t need the data, you only need the correlation” (see below). The Gaussian copula as Li implemented it boils all correlation down to a single number, enabling such an abstraction.

“Rather than relying on the immense amount of data used to figure the odds that a CDO might default…” The available data consists of CDS spreads and bond z-spreads, which may be used to imply a default probability for each issuer. However, to figure out if a CDO will default, one must evaluate the probability of multiple firms defaulting within a given time frame. This is the correlation parameter. Thus, the data alone does not tell you about the likelihood of CDO default.

The default probabilities extracted from historical data are not independent, and so can not simply be added (or multiplied, to be more precise) together. Moreover, the correlation which may be measured in CDS is the correlation of changes in default probability, and the jump to correlations of actual bankruptcy events is much more difficult, not in the least because there are relatively few historical defaults, compared to the number of issuers.

This isn’t to say that the data can’t be used – in fact the data must be used – but the key realization is that without a model (I struggle to think of one capable of handling such data that isn’t a copula), the data yields no worthwhile insights. Merely having the data is not enough to price a CDO.

“Li appeared to have discovered a law of correlation.” As I’ve mentioned, Li did not “discover” anything. He merely applied an existing model to a new dataset.

“You didn’t need the data; the correlation was just there.” Of course you need the data – the correlation is meaningless without the default probabilities extracted from the data. What the author presumably means is that your correlation number does not have to represent the “true” level of correlation observed in your data (which, as I’ve stated, is a nearly impossible thing to observe in the first place).

But having said that, this is probably the one thing the author has correct. After some futile efforts, researchers stopped measuring correlation and started holding a finger in the air to determine the “right” level. Similar to implied volatility in option pricing, correlation was unobservable and the “right” correlation was whatever level made the model price come out the same as the market price. Unfortunately, in a space where traders became so dependent on their models, the chain was circular: markets were informed solely by correlation-based models, which were themselves calibrated to the market.

The critique is not limited to the use of a Gaussian copula, however.

“Gaussian was rocket fuel for the CDO market.” Another true statement, but one which reveals the author’s unfamiliarity: “Gaussian” is an adjective used to describe a type of model. It’s a person’s name. This is like saying “Newtonian revolutionized the world of physics” when you want to talk about a model of gravitational acceleration or “Darwinian turned the study of biology upside down.”

“Li was on his way to a Nobel Prize when the world blew up.” No, he most emphatically was not. This is a repeat of a one of Felix’s statements from the Wired article. Even if the model had been perfectly accurate, do today’s financial journalists think pricing a financial derivative is worthy of a Nobel prize? Black/Scholes/Merton didn’t win a Nobel prize for their option pricing model, they won it for the research they did into the economics of asset pricing. The option model was just a nice benefit on the side.

A fundamental issue with this paragraph, on top of all these highlights, is that not once does it explain the actual problem. If you read the paragraph, and I asked you why did they blow up, could you tell me? I’m sure you’d say something about the correlation not being reflective of the data. And I’d respond, well then why didn’t we just start using the data, or start using the right correlation?

I’ll try to answer these questions soon in part II.

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Negative swap spreads

June 2, 2009 in Finance

Felix Salmon writes about the negative swap spread – a fascinating turn of events. Or at least, it was when the swap spread went negative almost a year ago.

The swap spread is the extra amount that an interest rate swap yields over a similar Treasury bond. Typically, a swap yields a few basis points more to compensate investors for the extra risk that comes from dealing with a bank instead of with the US government. Shortly after the Lehman default, however, a funny thing happened: the 30 year swap spread became negative. Effectively, it was cheaper to deal with a bank than with the government. Since then, the spread has wavered between 0 and -40 basis points.

What inspired Felix’s post was the large moves in the swap spread over the last few days. He speculates that it is on account of GM-related hedging (and counter-hedging) activity. I’m not convinced that is the case. Though the swap spread moved a massive amount Monday afternoon (rising 15 bps), it also rose 15 bps last Wednesday (May 27) and fell 15 the following day. On Wednesday, the move was tentatively attributed to mortgage-related hedging as Treasury yields moved higher. On Thursday, there was no good explanation. Today, it’s the GM bankruptcy. Forgive me for being skeptical.

Felix’s final point, however, is the one that really surprised me:

The market in interest-rate swaps is enormous — orders of magnitude greater than the market in credit default swaps — and, like most markets, it’s done some pretty crazy things over the past year, with long-dated swap spreads going negative for most of that time. Because there aren’t any systemic implications of things like negative long-dated swap spreads, and because the swaps market is a zero-sum game where for every winner there’s an equal and opposite loser, policymakers and bloggers and pundits haven’t paid much attention to it. That’s fine, they don’t need to. But it’s really important for fixed-income traders, which is why the likes of Jansen spend a lot of time looking at it.

The implication, I believe is that interest rate swaps are different from “something else” (read: CDS) because they lack are a “zero-sum game” and lack “systemic implications.”

But CDS are a zero sum game! In fact, I can’t think of a financial asset that isn’t a zero-sum game. If you follow the trail, it appears that Felix may be referencing either someone who commented on an article of his over at Seeking Alpha, or a different Seeking Alpha article – and you know how I feel about Seeking Alpha – which essentially argue that CDS are not zero sum because they have negative externalities (like requiring bailouts). But, if I may be cynical for a second, the bailout is the only thing preventing CDS from being zero-sum! Zero-sum means no dollars are invented or disappear; every one transfers one-for-one among involved parties. It does NOT mean that dollars are self contained. Saying CDS are not zero sum because they caused the meltdown of 2008 is like saying Russian bonds are not zero sum because they led to LTCM’s bailout in 1998. Every dollar made comes from someone else’s pocket. That’s what zero sum means. Nothing more. Nothing less. The concept that any modern financial contract (including a Ponzi scheme!) is not zero sum is odd. The economic process itself is not zero sum, because wealth can be created (or destroyed), but derivatives thereof (contracts, if you will) are zero sum because every dollar made comes, effectively, from the counterparty. End of rant.

And to the other point, that interest rate swaps lack systemic implications – newly bankrupt Jefferson County, Alabama, begs to differ.

Felix also refers to negative convexity in his post, following it quickly with “don’t ask” and a link to an incomprehensible article. I wrote on the topic a couple months ago, though I can’t promise to be much more clear.

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The CDS made me do it

May 1, 2009 in Finance

The Chrysler debacle has given rise to another CDS-related claim: these dastardly products permit scenarios in which bondholders are willing to put a company into bankruptcy by distorting the investors’ incentives. If the bondholders own a lot of CDS, then bankruptcy is more profitable than ongoing operations or restructuring.

There are two major problems with this argument. The first is that it is premised in the notion that bondholders, in the absence of CDS, would never choose bankruptcy over an alternative. This, history and common sense show, is just not true. Frequently, bankruptcy is a much better option that continuing operations (witness the airlines every few decades, as well as countless companies finding the current environment too stressful) because it provides current debt relief and perhaps more importantly may open financing channels that would be closed otherwise. Many people believe that Chrysler should have gone bankrupt years ago. The fact that auto companies’ profits for two decades have been driven solely by their financing arms and not their manufacturing operations is telling. Who knows, a Chrysler that went through bankruptcy instead of a disastrous merger could be healthy today! So, the premise that “only with CDS” would bondholders choose bankruptcy over another option is absolutely ridiculous.

But even if someone accepts that CDS are not the sole reason bondholders choose bankruptcy, motive may still come into play. In the above examples, the bankruptcy choice was “good for the company” but not necessarily “good for the bondholder” (though it is very difficult for me to think of an example where that is actually the case, since by definition the bondholders own the company’s assets). In a CDS-motivated bankruptcy push, one might argue that the choice is profitable for the bondholders but not necessarily good for the company. Since such a claim is not falsifiable – I can neither find a convincing case for or against it (though I lean strongly against in most cases) - I will instead point out that the situation is hardly unique to CDS. If I have a portfolio of two competing companies’ bonds, and the bankruptcy of one will benefit the other, then as the weaker company approaches bankruptcy I may push it to file in order to reap the benefit on the rest of my portfolio. In other words, a long-only bond portfolio containing negatively correlated distressed assets is pairwise equivalent to a long and short credit portfolio. CDS does not introduce this scenario, it just makes it more obvious to the press that creditors hedge themselves.

It is a sad state when we blindly rebel against what we don’t understand. If we were dealing with a CDO^2, I completely understand why there would be – and is – some nervousness about the nature of the product – because there simply isn’t a straightforward way of defining the exposure. But CDS is not a complicated product despite its reputation. I frequently teach the basics of CDS and find, properly explained, that the product is much easier to explain than the dynamics of an equity investment (witness: leveraged ETFs). Companies blow up all the time on equity investments, derivative aided or not (Ackman’s TGT fund, for example), and we don’t hear the fallout, because we believe that stocks are “understandable” and CDS is “complicated,” so the equity blowup is the investment firm’s fault, but the credit blowup is the product’s fault.

Remember, AIG didn’t take itself down with incompetence, negligence, and greed… CDS did. And that’s all there is to know.

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The Short Squeeze

April 30, 2009 in Finance

It is a favorite chorus of the anti-CDS crowd that CDS can make it more difficult for a company to survive, since bidding up CDS prices can affect the firm’s cost of borrowing.

This is about a hair’s width away from the oft-cited argument that “short selling is bad because it drives down stock prices,” a view that has was disproven in a massive 2005 study as well as multiple studies (pdf) showing the recent ban was actually harmful, not to mention market participants ultimately declaring it a failure.

However – in fairness – there is one time where short selling, or taking a short position more generally (such as through CDS), makes an indisputable impact on the underlying security: the short squeeze.

What happens when investment firms that have bought (potentially) limitless amounts of insurance on another company’s debt need to hedge their short position? They must compete to buy the relatively few tangible assets that can provide that hedge: the company’s bonds themselves. And this bidding war is ferocious. CDS driving a company’s spread wider is a bit of a wags-the-dog situation. But massive demand for a company’s bonds, that’s real. Moreover, it has been a major driver of the recent credit rally, which in turn fuels the equity run.

The most dramatic example of a short squeeze in action is of course Volkswagon, which gained 500% in one day last fall and was briefly the most valuable company in the world after a massively short investor base suddenly realized there weren’t enough shares to go around (Porsche had conveniently purchased most of them, and would end up booking a profit). But here’s the key: if short sellers can drive stock prices down, then surely VW – with one of the highest short to shares ratios ever – would have experienced some sort of price depression. But no, the stock hardly dropped in the months preceding the spike. Instead, this particular example of financial product failure resulted in saavy VW employees becoming millionaires overnight.

One datapoint does not a proof make, but look at today’s credit market, or even the recent equity markets rise on decreasing volume, and you’ll be unable to ignore the power of short covering to drive real asset prices higher. The market works on supply and demand; derivatives have a seperate market and so do not affect underlying asset prices except to the extent that people use derivative prices to extract risk information which informs their demand for the underlying. But whenever the derivative market and tangible market intersect, look out! If I own an arbitrary number of CDS and suddenly I need bonds to cover, the market’s normal mechanics will be disrupted. Even the VW example represents a perversion of supply and demand – Porsche was slowly buying up all the shares while other investors were shorting them, restricting supply dramatically. I remember headlines at the time which announced Porsche was actually releasing shares just to placate shorts who needed to cover.

Ultimately, if capitalist markets represent the method by which capital is most efficiently allocated and required returns are most efficiently expressed, then a long-only market is hardly the epitome of that ideal. But as long as companies can point the finger at “security manipulation” instead of their own performance (expert witness: bank stocks declining despite the short sale ban), we will continue to have this debate. Not that any company complains when the short squeeze pushes them higher. Instead, they just issue debt and stock, a behavior which lately has been married to the highest rate of insider selling in year.

So the next time someone tries to claim that CDS, or short selling, can have an adverse impact on asset prices, don’t throw study after study at them which demonstrates otherwise. Just point out that to the extent their argument is true, it’s effect is much more dramatic on the squeeze side – the upside – than where their complaint lies.

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The hits just keep on coming: Citigroup earnings

April 17, 2009 in Finance, News

The accounting alchemy Citi used this morning to report a “profit” is being much more widely reported than Goldman’s Decembrist revolt, but I want to address it nonetheless.

On the surface, Citi reported a profit of $1.6B. Unfortunately, by the time that trickled down to common shareholders there was only -$966M left, a loss of -$0.18/share. The balance went to dividends and expenses associated with Citi’s various preferred shareholders.

But the headline is that Citi had a $2.5B gain (or 156% of their net income) because of a relatively new accounting rule that allows firms to have unrealized gains as their credit spreads widen. The higher spread reduces the value of the firm’s debt, and that reduction of liability is a gain. In theory, Citi could go repurchase their debt below cost and monetize the difference. Obviously, however, Citi can’t do that, and in all likelihood that 2.5B will be reversed over time as Citi recovers, or even entirely lost if Citi defaults. So I’m going to disregard this rule that allows company to profit from what essentially amounts to themselves doing worse.

The most interesting facet of all, though, is that if (big, sarcastic if) the talking heads are right and short selling/CDS speculators are to blame for spreads widening out of control, then I think Citi really owes those “market manipulators” a thank you and a heartfelt apology, since it is only because of their shenanegans that Citi posted a profit. End of sarcasm.

Citi reported profit: 1.6B or almost $0.29/share

Unrealized gain on liability reduction: 2.5B or $0.47/share

Preferred expenses: 2.5B or $0.47/share

Back it all out and what’s left for common shareholders? -3.4B or -$0.65/share.

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The Man who Broke the CDS?

March 24, 2009 in Finance

George Soros has written an opinion in today’s WSJ calling for the regulation – and elimination – of CDS.

He notes that CDS are instruments which allow speculation on default:

What makes [CDS] toxic is that such speculation can be self-validating.

I find his nature-of-the-security argument severely lacking:

The negative effect is reinforced by the fact that CDS are tradable and therefore tend to be priced as warrants, which can be sold at anytime, not as options, which would require an actual default to be cashed in. People buy them not because they expect an eventual default, but because they expect the CDS to appreciate in response to adverse developments.

AIG thought it was selling insurance on bonds, and as such, they considered CDS outrageously overpriced. In fact, it was selling bear-market warrants and it severely underestimated the risk.

AIG underestimated their MTM risk, to be sure, but they had negotiated their MTM risk away via collateral-free counterparty agreements. In this paradigm, AIG’s real downfall was their credit-rating downgrade, which forced them to post collateral. There’s no question their risk management was awful, but were they not downgraded they’d still be solvent, since few of the CDS they sold have actually defaulted (and consequently mandated cashflows).

This begs an interesting question (and points out the ridiculousness of the rating agencies) — if you have an institution which is solvent at credit rating A and insolvent at credit rating B, which one should it have?

But Soros isn’t finished:

[I]t’s clear that AIG, Bear Stearns, Lehman Brothers and others were destroyed by bear raids in which the shorting of stocks and buying CDS mutually amplified and reinforced each other….

And AIG failed to understand this.

So let’s review. A company whose “expertise” is financial products didn’t understand how they work, but George Soros can explain it succinctly in a WSJ opinion. Sounds to me like the problem lies with AIG, not the CDS.

But Soros would argue that the fault for taking down massive institutions like Bear, Lehman, and AIG lies with crazy speculators, not with any failures of those firms. And we should act now to prevent these crazy individuals from taking down any more institutions, especially – say it ain’t so – a government arm like the Treasury.

Now where would a timid investor like Soros get an idea like that?

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