ISDA: Stop Making Sense

The following is a response I just posted on Bloomberg to some criticism last week coming from the International Swaps and Derivatives Association. They took issue with some things I had written in my latest Bloomberg column. I think their comment was partially fair, and also partially misleading, so I thought some clarification would be useful. The text below is identical to what appears (or will very shortly) in Bloomberg:

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My most recent Bloomberg column on the network of credit default swaps contracts provoked a comment from the International Swaps and Derivatives Association, Inc. The group objected to my characterization of the network of outstanding CDS contracts as "hidden" and potentially a source of trouble. I'd like to address their concerns, and also raise some questions.

Contrary to the association's claim, I am aware of the existence of the Depository Trust & Clearing Corporation. I'll admit to having underestimated how much their project to create a warehouse of information on CDS contracts has developed in the past few years; my statement that these contracts are not "recorded by any central repository" was too strong, as a partial repository does exist, and the DTCC deserves great credit for creating it.

However, it is not clear that this repository gives such a complete picture of outstanding CDS linkages that we can all relax.

For example, DTCC's repository covers 98 percent of all outstanding CDS contracts, not 100 percent. Asking why may or may not be a quibble. After all, a map showing 98 percent of the largest 300 cities in the U.S. could leave out New York, Los Angeles, Chicago, Houston and Philadelphia. Moreover, the simple number of contracts tells us nothing about the values listed on those contracts. In principle, the missing 2 percent of contracts could represent a significant fraction of the outstanding value of CDS contracts.

More importantly, when thinking about potentially cascading risks in a complex network, fine details of the network topology -- its architecture or wiring diagram -- matter a lot. Indeed, the CDS contracts that put American Insurance Group Inc. in grave danger in 2008 represented a tiny fraction -- much less than 1 percent -- of the total number of outstanding CDS contracts.

Hence, it would be interesting to know why the repository holds only 98 percent rather than 100 percent. There may be a very simple and reassuring answer, but it's not readily apparent from DTCC's description of the repository.

Also, there is another issue which makes "fully transparent" not quite the right phrase for this network of contracts, even if we suppose the 98 percent leaves out nothing of importance.

The DTCC commendably makes its data available to regulators. Still, it appears that the full network of interdependencies created by CDS contracts may remain opaque to regulators, because DTCC, according to its own description, enables...

"... each regulator to access reports tailored to their specific entitlements as a market regulator, prudential or primary supervisor, or central bank. These detailed reports are created for each regulator to show only the CDS data relevant to its jurisdiction, regulated entities or currency, at the appropriate level of aggregation."

This would imply, for example, that regulators in the U.S. can look and see which of their banks have sold CDS on, say, a big German bank. But the health of the U.S. banks then depends directly on the health of that German bank, which may in turn have sold CDS on Greek or Italian debt or any number of other things. The DTCC data on the latter CDS contracts would, apparently, not be available to U.S. regulators, being out of their jurisdiction.

The point is that a financial institution is at risk not only from contracts it has entered into, but also from contracts that its many counterparties have entered into (this is the whole idea of systemic risk linked to the possibility of contagion). Credible tests of the financial network's resilience require a truly global analysis of the potential pathways along which distress (particularly from outright counterparty failures) may spread. It's not clear that any regulator has the full data on which such an analysis can be based.

None of this, by any means, is meant as a criticism of DTCC or what it has done in the past few years. The 98 percent figure is impressive, and let's hope the 98 percent soon becomes 100 percent and the DTCC finds a way to make ALL information in the repository available to regulators everywhere. Even better would be full disclosure to the public.

Of course, nothing in the comment from the International Swaps and Derivatives Association changes the main point of my column, which was that it is incorrect to believe that more CDS contracts -- or, more generally, more financial interdependencies of any kind, including links created by other derivatives such as interest-rate swaps -- automatically lead to better risk-sharing and a safer banking system. More apparent risk-sharing can actually mean more systemic risk and less overall banking safety.

(Mark Buchanan is a Bloomberg View columnist.)

Sharing risk can increase risk

I have a column coming out in Bloomberg Views sometime this evening (US time). It touches on the European debt crisis and the issue of outstanding credit default swaps. This post is intended to provide a few more technical details on the study by Stefano Battiston and colleagues, which I mention in the column, showing that more risk sharing between institutions can, in some cases, lead to greater systemic risk. [Note: this work was carried out as part of an ambitious European research project called Forecasting Financial Crises, which brings together economists, physicists, computer scientists and others in an effort to forge new insights into economic systems by exploiting ideas from other areas of science.]

The authors of this study start out by noting the obvious: that credit networks can both help institutions to pool resources to achieve things they couldn't on their own, and to diversify against the risks they face. At the same time, the linking together of institutions by contracts implies a greater chance for the propagation of financial stress from one place to another. The same thing applies to any network such as the electrical grid -- sharing demands among many generating stations makes for a more adaptive and efficient system, able to handle fluctuations in demand, yet also means that failures can spread across much of the network very quickly. New Orleans can be blacked out in a few seconds because a tree fell in Cleveland.

In banking, the authors note, Allen and Gale (references given in the paper) did some pioneering work on the properties of credit networks:

... in their pioneering contribution Allen and Gale reach the conclusion that if the credit network of the interbank market is a credit chain – in which each agent is linked only to one neighbor along a ring – the probability of a collapse of each and every agent (a bankruptcy avalanche) in case a node is hit by a shock is equal to one. As the number of partners of each agent increases, i.e. as the network evolves toward completeness, the risk of a collapse of the agent hit by the shock goes asymptotically to zero, thanks to risk sharing. The larger the pool of connected neighbors whom the agent can share the shock with, the smaller the risk of a collapse of the agent and therefore of the network, i.e. the higher network resilience. Systemic risk is at a minimum when the credit network is complete, i.e. when agents fully diversify individual risks. In other words, there is a monotonically decreasing relationship between the probability of individual failure/systemic risk and the degree of connectivity of the credit network.

This is essentially the positive story of risk sharing which is taken as the norm in much thinking about risk management. More sharing is better; the probability of individual failure always decreases as the density of risk-sharing links grows.

This is not what Battiston and colleagues find under slightly more general assumptions of how the network is put together and how institutions interact. I'll give a brief outline of what is different in their model in a moment; what comes out of it is the very different conclusion that...

The larger the number of connected neighbors, the smaller the risk of an individual collapse but the higher systemic risk may be and therefore the lower network resilience. In other words, in our paper, the relationship between connectivity and systemic risk is not monotonically decreasing as in Allen and Gale, but hump shaped, i.e. decreasing for relatively low degree of connectivity and increasing afterwards.

 Note that they are making a distinction between two kinds of risk: 1. individual risk, arising from factors specific to one bank's business and which can make it go bankrupt, and 2. systemic risk, arising from the propagation of financial distress through the system. As in Allen and Gale, they find that individual risk DOES decrease with increasing connectivity: banks become more resistant to shocks coming from their own business, but that systemic risk DOES NOT decrease. The latter risk increases with higher connectivity, and can win out in determining the overall chance a bank might go bankrupt. In effect, the effort on the part of many banks to manage their own risks can end up creating a new systemic risk that is worse than the risk they have reduced through risk sharing.

There are two principle elements in the credit network model they study. First is the obvious fact that resilience of an institution in such a network depends on the resilience of those with whom it shares risks. Buying CDS against the potential default of your Greek bonds is all well and good as long as the bank from whom you purchased the CDS remains solvent. In the 2008 crisis, Goldman Sachs and other banks had purchased CDS from A.I.G. to cover their exposure to securitized mortgages, but those CDS would have been more or less without value had the US government not stepped in to bail out A.I.G.

The second factor model is very important, and it's something I didn't have space to mention in the Bloomberg essay. This is the notion that financial distress tends to have an inherently nonlinear aspect to it -- some trouble or distress tends to bring more in its wake. Battiston and colleagues call this "trend reinforcement, " and describe it as follows:

... trend reinforcement is also quite a general mechanism in credit networks. It can occur in at least two situations. In the first one (see e.g. in (Morris and Shin, 2008)), consider an agent A that is hit by a shock due a loss in value of some securities among her assets. If such shock is large enough, so that some of A’s creditors claim their funds back, A is forced to fire-sell some of the securities in order to pay the debt. If the securities are sold below the market price, the asset side of the balance sheet is decreasing more than the liability side and the leverage of A is unintentionally increased. This situation can lead to a spiral of losses and decreasing robustness (Brunnermeier, 2008; Brunnermeier and Pederson, 2009). A second situation is the one in which when the agent A is hit by a shock, her creditor B makes condition to credit harder in the next period. Indeed it is well documented that lenders ask a higher external finance premium when the borrowers’ financial conditions worsen (Bernanke et al., 1999). This can be seen as a cost from the point of view of A and thus as an additional shock hitting A in the next period. In both situations, a decrease in robustness at period t increases the chance of a decrease in robustness at period t + 1.

It is the interplay of such positive feedback with the propagation of distress in a dense network which causes the overall increase in systemic risk at high connectivity.

I'm not going to wade into the detailed mathematics. Roughly speaking, the authors develop some stochastic equations to follow the evolution of a bank's "robustness" R -- considered to be a number between 0 and 1, with 1 being fully robust. A bankruptcy event is marked by R passing through 0. This is a standard approach in the finance literature on modeling corporate bankruptcies. The equations they derive incorporate their assumptions about the positive influences of risk sharing and the negative influences of distress propagation and trend reinforcement.

The key result shows up clearly in the figure (below), which shows the overall probability of a bank in the network to go bankrupt (a probability per unit of time) versus the amount of risk-sharing connectivity in the network (here given by k, the number of partners with which each bank shares risks). It may not be easy to see, but the figure shows a dashed line (labeled 'baseline') which reflects the classical result on risk sharing in the absence of trend reinforcement. More connectivity is always good. But the red curve shows the more realistic result with trend reinforcement or the positive feedback associated with financial distress taken into account. Now adding connectivity is only good for a while, and eventually becomes positively harmful. There's a middle range of optimal connectivity beyond which more connections only serve to put bank in greater danger.
 

Finally, the authors of this paper make very interesting observations about the potential relevance of this model to globalization, which has been an experiment in risk sharing on a global scale, with an outcome -- at the moment -- which appears not entirely positive:

In a broader perspective, this conceptual framework may have far reaching implications also for the assessment of the costs and benefits of globalization. Since some credit relations involve agents located in different countries, national credit networks are connected in a world wide web of credit relationships. The increasing interlinkage of credit networks – one of the main features of globalization – allows for international risk sharing but it also makes room for the propagation of financial distress across borders. The recent, and still ongoing, financial crisis is a case in point.

International risk sharing may prevail in the early stage of globalization, i.e. when connectivity is relatively ”low”. An increase in connectivity at this stage therefore may be beneficial. On the other hand, if connectivity is already high, i.e. in the mature stage of globalization, an increase in connectivity may bring to the fore the internationalization of financial distress. An increase in connectivity, in other words, may increase the likelihood of financial crises worldwide.

Which is, in part, why we're not yet out of the European debt crisis woods.

Central corporate control revealed by mathematics

If you haven't already heard about this new study on the network of corporate control, do have a look. The idea behind it was to use network analysis of who owns whom in the corporate world (established through stock ownership) to tease out centrality of control. New Scientist magazine offers a nice account, which starts as follows:

AS PROTESTS against financial power sweep the world this week, science may have confirmed the protesters' worst fears. An analysis of the relationships between 43,000 transnational corporations has identified a relatively small group of companies, mainly banks, with disproportionate power over the global economy.

The study's assumptions have attracted some criticism, but complex systems analysts contacted by New Scientist say it is a unique effort to untangle control in the global economy. Pushing the analysis further, they say, could help to identify ways of making global capitalism more stable.

The idea that a few bankers control a large chunk of the global economy might not seem like news to New York's Occupy Wall Street movement and protesters elsewhere (see photo). But the study, by a trio of complex systems theorists at the Swiss Federal Institute of Technology in Zurich, is the first to go beyond ideology to empirically identify such a network of power. It combines the mathematics long used to model natural systems with comprehensive corporate data to map ownership among the world's transnational corporations (TNCs).

But also have a look at the web site of the project behind the study, the European project Forecasting Financial Crises, where the authors have tried to clear up several common misinterpretations of just what the study shows.

Indeed, I know the members of this group quite well. They're great scientists and this is a beautiful piece of work. If you know a little about natural complex networks, then the structures found here actually aren't terrifically surprising. However, they are interesting, and it's very important to have the structure documented in detail. Moreover, just because the structure observed here is very common in real world complex networks doesn't mean its something that is good for society.

The European debt crisis in a picture

From the New York Times (by way of Simon Johnson), a beautiful (and scary) picture of the various debt connections among European nations. (Best to right click and download and then open so you can easily zoom in and out as the picture is mighty big.)

My question is - what happens if the Euro does collapse? Do European nations have well-planned emergency measures to restore the Franc, Deutchmark, Lira and other European currencies quickly? Somehow I'm not feeling reassured.

Stress tests?

I suspect that what goes on at the European Banking Authority is pretty much above board, in general, but still -- are the stress tests reported on here really designed to find points of potential weakness? I'm not reassured when the New York Times reports that the tests were designed in part to "restore confidence in the overall health of the European financial system." This sounds a little like a public relations angle.

Later, the article gets to the real issue: are these stress tests designed to test the banks against realistically severe scenarios, or instead to throw up some soft balls to be hit hardly so as to restore (misplaced) confidence? Kudos to the writer for including this illuminating quote:

“This year’s tests still did not include the impact of a formal debt default by a European government, which is the single greatest risk facing the European banking sector at present,” Marie Diron, an economist who advises the consulting firm Ernst & Young, wrote in a note. “The publication of these results will not assuage investors’ fears over the resilience of the E.U. banking sector,” she wrote, referring to the European Union.   

Bank runs begin in Greece and Ireland

Gavyn Davies refers to the image below, which presents a rather disturbing trend in bank deposits in Greece and Ireland. Notably, banks in these two countries in the past year or two have experienced a sharp increase in withdrawals of retail deposits:

Davies suggests they've lost 15% of their deposits, but it could be significantly worse than that -- note that the data in the figure only goes up to around December 2010. Extrapolate the trend through to today and I'm guessing the loss is approaching 30-35%.

Fully one third of the retails deposits in these two nations have been pulled out?! Yikes. Not a good sign. As Davies comments:

As the UK government found in the case of Northern Rock, the appearance of queues outside banks is one of the worst nightmares which a central bank can face. It has not happened in Europe – yet.