Many people ask about the source for my cockroach analogy, which I go through on page 232ff in A Demon of Our Own Design. The source for this analogy is my paper with Joe Langsam in the Journal of Theoretical Biology. So I am linking to that paper here.

The argument in the paper is pretty readable if you read past the citations and the math, and it is relevant to how we construct financial markets and manage risk in those markets.

It might seem now that it was in a different world, but it was in this one, and in fact it was in the United States. Traders watched their bank of broker screens as the 30-year Treasury dropped below 8% for the first time in their youthful memory. That was in the 1980s. I was working at Morgan Stanley at the time, and someone on the Treasury desk made a trade for his own account just so he could frame the ticket from that momentous event. Yes, interest rates can go above 8%. In fact, at the time an 8% rate seemed quite reasonable.

I mention this because over the past decade or so we have constructed a financial landscape where an 8% interest rate not only is hard for us to envision, but where it would be disastrous. The reason is the huge stock of adjustable rate mortgages. Looking at the dislocations that are coming about from the subprime problems and the related credit crunch, it is hard to fathom the effect on the housing market and the overall economy if all those remaining homeowners with various flavors of adjustable rate mortgages saw rates shoot up hundreds of basis points. I don’t know how to quantify the effect, but I would hope that there are researchers at the Fed who do. And I would bet that the implications are pretty scary. Maybe so scary that the Fed would not be able to push interest rates up very far for fear of triggering a populist revolt.

Of course, now all of the discussion is about possible Fed easing. So I am worrying about something that is not even on the radar screen. But can anyone envision a scenario where a substantial increase in interest rates would make sense from an economic standpoint, but where the Fed finds its hands tied because the costs to homeowners would be too great?

What a mess. With multi-billion dollar trading losses, we are starting to see heads roll. Citigroup is losing its long-time fixed income head Tom Maheras and several of his lieutenants. Merrill is continuing in its approach to managing human capital, bringing in new blood and losing experienced hands in the fixed income business. Oh, and they are putting someone into a Chief Risk Officer role. Talk about closing the barn door….

Other firms have fared very poorly but so far without executing any of the troops. Morgan Stanley layered a heart-stopping $390MM one-day loss in its prop trading desk on top of far bigger losses on leveraged loans and the like. This loss in Process Driven Trading was similar in timing to the losses at Goldman’s Global Alpha fund, AQR and other quant hedge funds. Which pretty much tells us that what this secretive group at Morgan Stanley was up to was a not-so-secretive strategy: They had a lot of capital riding on the same sort of momentum and value versus growth quant equity strategies as the rest of the gang.

What I don’t understand in all of this is that for all the mention in the press of the risk takers, there is not a single mention I have found of the people who are supposed to be overseeing the risk. If you are the Chief Risk Officer and everything blows up, don’t you bear some responsibility?

To get the idea of the CRO job, let me tell you a bit about myself. Although I am older and have a slight build, I am an Olympic athlete. My event is the shot put. I consider myself a top notch athlete in this event. I work out like the other competitors, follow a high protein diet, steer clear of performance enhancing drugs and train at the local track. The only trouble I have is when the Olympics roll around every four years, because it turns out that for an Olympic athlete, I am not very good. But then, that is only an occasional blip in my otherwise Olympic-worthy regimen.

In the CRO job 99% of the days there is nothing going wrong. The only test you get of how well you are doing – short of pouring out risk reports and looking ponderous and prudent in meetings – is what happens to the firm during times of market crisis. Every few years something calamitous happens in the market; if the firm gets blown away, that suggests you did not do a very good job.

What about the job of the risk taker? Well, a risk taker does, after all, take risk. He tries to do so intelligently, that is, he tries to put on positions that he hopes have a high return per unit of risk. But how much risk he takes and where he takes it has to be dictated by someone. You can’t just say “take risk, and good luck”.

The job of the risk manager at these firms is to convey the risk parameters to the risk takers, to define the boundaries. And that should involve more than simply running a value at risk calculation on the computer. If that is all you want, you don’t need a guy making a few million a year and employing a staff of hundreds. Before I would be so harsh on Tom Maheras and his compatriots, I would be calling to task the people who allowed that risk level to be taken in the first place.

I testified before the House Financial Services Committee on Tuesday in a hearing on "Systemic Risk: Examining Regulators Ability to Respond to Threats to the Financial System". In my written testimony I provided my views on specific questions they had posed in their invitation.

One of the points I made in my testimony was the idea of the government taking on a role as a liquidity provider of last resort. This is something I addressed in my September 10th post, "Bailouts for Profit", and it was also a central point brought up in the testimony of another member of the panel, Professor Steven Schwarcz of Duke University. I had considered this a radical idea, but it was a dominant focus from the members of the committee during the two hours of questions.

[This is a modified version of an article I wrote that appeared in the September issue of Institutional Investor].

With the collapse of the U.S. subprime market and the aftershocks that have been felt in credit and equity markets, there has been a lot of talk about fat tails, 20 standard deviation moves and 100-year event. We seem to hear such descriptions fairly frequently, which suggests that maybe all the talk isn’t really about 100-year events after all. Maybe it is more a reflection of investors’ market views than it is of market reality.

No market veteran should be surprised to see periods when securities prices move violently. The recent rise in credit spreads is nothing compared to what happened in 1998 leading up to and following the collapse of hedge fund Long-Term Capital Management or, for that matter, during the junk bond crisis earlier that decade, when spreads quadrupled.

What catches many investors off guard and leads them to make the “100 year” sort of comment is not the behavior of individual markets, but the concurrent big and unexpected moves among markets. It’s the surprising linkages that suddenly appear between markets that should not have much to do with one other and the failed linkages between those that should march in tandem. That is, investors are not as dumbfounded when volatility skyrockets as when correlations go awry. This may be because investors depend on correlation for hedging and diversifying. And nothing hurts more than to think you are well hedged and then to discover you are not hedged at all.

Surprising Market Linkages

Correlations between markets, however, can shift wildly and in unanticipated ways — and usually at the worst possible time, when there is a crisis with volatility that is out of hand. To see this, think back on some of the unexpected correlations that have haunted us in earlier market crises:

• The 1987 stock market crash. During the crash, Wall Street junk bond trading desks that had been using Treasury bonds as a hedge were surprised to find that their junk bonds tanked while Treasuries strengthened. They had the double whammy of losing on the junk bond inventory and on the hedge as well. The reason for this is easy to see in retrospect: Investors started to look at junk bonds more as stock-like risk than as interest rate vehicles while Treasuries became a safe haven during the flight to quality and so were bid up.
• The 1997 Asian crisis. The financial crisis that started in July 1997 with the collapse of the Thai baht sank equity markets across Asia and ended up enveloping Brazil as well. Emerging-markets fund managers who thought they had diversified portfolios — and might have inched up their risk accordingly — found themselves losing on all fronts. The reason was not that these markets had suddenly become economically linked with Brazil, but rather that the banks that were in the middle of the crisis, and that were being forced to reduce leverage, could not do so effectively in the illiquid Asian markets, so they sold off other assets, including sizable holdings in Brazil.
• The fall of Long-Term Capital Management in 1998. When the LTCM crisis hit, volatility shot up everywhere, as would be expected. Everywhere, that is, but Germany. There, the implied volatility dropped to near historical lows. Not coincidentally, it was in Germany that LTCM and others had sizable long volatility bets; as they closed out of those positions, the derivatives they held dropped in price, and the implied volatility thus dropped as well. Chalk one up for the adage that markets move to inflict the most pain.

And now we get to the crazy markets of August 2007. Stresses in a minor part of the mortgage market — so minor that Federal Reserve Board chairman Ben Bernanke testified before Congress in March that the impact of the problem had been “moderate” — break out not only to affect other mortgages but also to widen credit spreads worldwide. And from there, subprime somehow links to the equity markets. Stock market volatility doubles, the major indexes tumble by 10 percent and, most improbable of all, a host of quantitative equity hedge funds — which use computer models to try scrupulously to be market neutral — are hit by a “100 year” event.

When we see this sort of thing happening, our not very helpful reaction is to shake our heads as if we are looking over a fender bender and point the finger at statistical anomalies like fat tails, 100-year events, black swans, or whatever. This doesn’t add much to the discourse or to our ultimate understanding. It is just more sophisticated ways of saying we just lost a lot of money and were caught by surprise. Instead of simply stating the obvious, that big and unanticipated events occur, we need to try to understand the source of these surprising events. I believe that the unexpected shifts in correlation are caused by the same elements I point to in my book as the major cause of market crises: complexity and tight coupling.

Complexity

Complexity means that an event can propagate in nonlinear and unanticipated ways. An example of a complex system from the realm of engineering is the operation of a nuclear power plant, where a minor event like a clogged pressure-release valve (as occurred at Three Mile Island) or a shift in the combination of steam production and fuel temperature (as at Chernobyl) can cascade into a meltdown.

For financial markets, complexity is spelled d-e-r-i-v-a-t-i-v-e-s. Many derivatives have nonlinear payoffs, so that a small move in the market might lead to a small move in the price of the derivative in one instance and to a much larger move in the price in another. Many derivatives also lead to unexpected and sometimes unnatural linkages between instruments and markets. Thanks to collateralized debt obligations, this is what is at the root of the first leg of the contagion we observed from the subprime market. Subprimes were included in various CDOs, as were other types of mortgages and corporate bonds. Like a kid who brings his cold to a birthday party, the sickly subprime mortgages mingled with these other instruments.

The result can be unexpected higher correlation. Investors that have to reduce their derivatives exposure or hedge their exposure by taking positions in the underlying bonds will look at them as part of a CDO. It doesn’t matter if one of the underlying bonds is issued by a AA-rated energy company and another by a BB financial; the bonds in a given package will move in lockstep. And although subprime happens to be the culprit this time around, any one of the markets involved in the CDO packaging could have started things off.

Tight Coupling

Tight coupling is a term I have borrowed from systems engineering. A tightly coupled process progresses from one stage to the next with no opportunity to intervene. If things are moving out of control, you can’t pull an emergency lever and stop the process while a committee convenes to analyze the situation. Examples of tightly coupled processes include a space shuttle launch, a nuclear power plant moving toward criticality and even something as prosaic as bread baking.

In financial markets tight coupling comes from the feedback between mechanistic trading, price changes and subsequent trading based on the price changes. The mechanistic trading can result from a computer-based program or contractual requirements to reduce leverage when things turn bad.

In the ’87 crash tight coupling arose from the computer-based trading of those running portfolio insurance programs. On Monday, October 19, in response to a nearly 10 percent drop in the U.S. market the previous week, these programs triggered a flood of trades to sell futures to increase the hedge. As those trades hit the market, prices dropped, feeding back to the computers, which ordered yet more rounds of trading.

More commonly, tight coupling comes from leverage. When things start to go badly for a highly leveraged fund and its collateral drops to the point that it no longer has enough assets to meet margin calls, its manager has to start selling assets. This drops prices, so the collateral declines further, forcing yet more sales. The resulting downward cycle is exactly what we saw with the demise of LTCM.

And it gets worse. Just like complexity, the tight coupling born of leverage can lead to surprising linkages between markets. High leverage in one market can end up devastating another, unrelated, perfectly healthy market. This happens when a market under stress becomes illiquid and fund managers must look to other markets: If you can’t sell what you want to sell, you sell what you can. This puts pressure on markets that have nothing to do with the original problem, other than that they happened to be home to securities held by a fund in trouble. Now other highly leveraged funds with similar exposure in these markets are forced to sell, and the cycle continues. This may be how the subprime mess expanded beyond mortgages and credit markets to end up stressing quantitative equity hedge funds, funds that had nothing to do with subprime mortgages.

All of this means that investors cannot put too much stock in correlations. If you depend on diversification or hedges to keep risks under control, then when it matters most it may not work.

When a market is under stress, prices come untethered from value, driven instead by the liquidity demand of those who have to get out – for example, funds that are leveraged and have the banks breathing down their necks – and those who simply cannot face the mounting losses and find it prudent to cut and run. But if the breakdown is coming from the liquidity needs of the leveraged fund, cut-and-run may not be the right strategy; profits can come to those who are willing to provide the other side of the trade for those who must liquidate.

This is a role we have seen Citadel take in the past couple of years, once with Amaranth and once with Sowood. They provided liquidity to the market when it was needed, and in providing this service they scooped up the assets that were going begging for pennies on the dollar. Good for them. I think this can be a great business for a fund to be in.

No one seems to begrudge Citadel, no one is chastising them for providing a bailout. The reason, of course, is that while they did bail out the markets – that is, while they helped stem a problem from getting worse or propagating out further to affect other firms – they are the ones who put up the capital, took the risk, and ultimately will earn the profits from their action. And Sowood and Amaranth are still out of business.

The point is that there are two types of bailouts. There are bailouts that keep the offending fund on it feet and in business. Arguably these sorts of bailouts create a moral hazard problem. But there is another sort of bailout that does not stand in the way of failure, but that still reduces the collateral damage. What I have described above are bailouts of the latter type. And the government should start to think of financial bailouts in these terms.

To be specific, what if the government maintained a pool of capital on the ready to buy up assets of firms that are failing, much as Citadel did for Amaranth and Sowood? Of course, if a private entity is willing to step up to the plate, all the better. But as a last resort, what if the government took on the role that Citadel did in these instances. There would be no moral hazard problems, since the firm still fails. But the collateral damage would be contained; the market would be kept from going into crisis, the dominos would be kept from falling. And the taxpayer would have good odds of pocketing some profits.

We have seen other cases that were ripe for this type of bailout. Take the Bear Stearns hedge funds; in their case a bailout of sorts occurred through the banks, which in an exercise of price suppression (as opposed to the usual function of the market, which is price discovery) agreed not to push their collateral into the market. Or take LTCM, where the Fed in effect used the banks as a surrogate for performing the second type of bailout.

Lower volatility can mean higher risk. Here is how I think we get to this paradoxical result.

With the growth of hedge funds over the past few years, more and more capital has been scavenging for alpha opportunities. When anything moves a little out of line, there is plenty of money ready to pounce on it. That is, there is more liquidity. And this is great for the liquidity demanders – for example a pension fund that has to invest a recent inflow – because they don’t have to move prices very far to elicit the other side of the trade. And that means lower price volatility.

The lower volatility in turn leads to higher leverage. One reason is that many funds base their leverage on value at risk, and they calculate value at risk using historical volatility. So when there is lower volatility they can lever more and still stay within their VaR limits. A second reason is that as more capital flows into the market and as leverage increases, there is more money chasing opportunities. Alpha from the opportunities is thus dampened, so a hedge fund now has to leverage up more in order to try to generate its target returns. And so the cycle goes – more leverage leads to more liquidity and lower volatility and narrower opportunities, which then leads to still higher leverage. This cycle is not much different than the classical credit cycle – which it is a part of this time around – where financial institutions make credit successively easier and easier because of competitive pressure and an environment that has, up to that point, been clear sailing.

This then gets to the higher risk. Because the real risk in the markets is not the day-to-day volatility, it is the risk of a crisis. And as I argue in A Demon of Our Own Design, high leverage is one root cause of crisis.

Bernanke has said the hedge funds “provide a good deal of liquidity in the markets and help the markets work more efficiently.” And that should be good, right? Well, it depends on how they are getting that liquidity. If it is through leverage, there may be a cloud inside that silver lining.

This relationship between liquidity, volatility versus risk is hard to observe, because there is nothing in the day-to-day markets to suggest anything is wrong. In fact, with volatility low, everything looks just great. We don’t know that leverage has increased, because nobody has those numbers. We don’t know how much liquidity will be forthcoming if there is a market stress, nor do we know how many of those who are the liquidity providers in the normal, quiet market times will move to the sidelines, or turn into liquidity demanders themselves. On the surface, the water may be smooth as glass, but we cannot fathom what is happening in the depths.

I was asked to write a column for Time Magazine on what is causing the subprime mortgages to have so broad an impact. Since you can see it there via the link, I am not also putting it here. But comments here are welcome. (To make a comment, click on the title so that the post appears on its own page).

One part of the solution to the quant hedge fund problem is to use a strategy no one else is using. (The other part, in case you are wondering, is not to lever so much). Of course, it is hard to know if you are really differentiated from what other quant shops are doing – it is not like everyone gets together and presents papers at hedge fund symposiums. But, in any case, I think this is hard to accomplish.

The reason I think this is for the same reason the quant funds ended up with very similar strategies in the first place: they use the scientific method.

The key to the success of the scientific method is the reproducibility of results. If you do the same experiment I do, you will reach the same conclusion. More than that, if you and I start with the same hypothesis and apply the same data, you will discover what I discover. That is why we see so many races for the prize in the pure sciences. Even with the spectacular discovery by Watson and Crick, there were others nipping at their heels.

With the quant funds, we have well-trained professionals applying the scientific method to capture anomalies in the market. Most are trained at the same handful of institutions, they have read the same academic literature, and they are applying the same statistical tests, using the same analytical tools, to the same sets of data. So it is no surprise they come up with similar models.

That is not to say you can’t be successful doing this sort of thing. Think of Jim Simmons and Renaissance. Granted his longer-term fund has been in the same boat as Goldman and others, but his high frequency fund has made money with uncanny consistency for years. But he has a number of things working for him. First of all, he has huge scale; there are about two hundred top-notch scientists in his firm. He also has had years to amass a proprietary knowledge base, so he does not need to rely as heavily on the existing academic research. So it is reasonable to think he could stay ahead of the curve – others might get to where he has been, but by then he is another step ahead.