March 28, 2009


Markets again bet the worst is past: This is the fifth time U.S. blue-chip stocks have risen more than 10% since October 2007. The previous four rallies all gave way to more selling and new market lows. (Tom Petruno, March 28, 2009, Los Angeles Times)

Did they cancel Great Depression II? So soon?

That's one message investors might choose to take away from the sharp rebound in stock markets worldwide over the last three weeks.

The Standard & Poor's 500 stock index has pared its year-to-date loss from a stunning 25% as of March 9 to just under 10% at Friday's close. [...]

This shock-and-awe campaign impresses Jim McDonald, chief investment strategist at Chicago-based Northern Trust, which manages $560 billion for clients.

"We think that what the Fed and the Treasury have done has reduced the risk of the worst happening" to the financial system and the economy, McDonald said. Enough so, he said, that he shifted a chunk of Northern Trust's portfolio out of cash and into stocks and other investments this month, trimming his cash holdings to 11% of assets from 16%.

Also still mostly in the pipeline are the effects of the nearly $800-billion economic stimulus bill Congress approved in February. Ditto for this year's mortgage refinancing wave, with home loan rates at record lows.

At a minimum, if the financial and economic meltdowns have been arrested it makes sense that investors would have to think twice about sending stocks down further, after taking the S&P 500 and the Dow industrials to 12-year lows March 9.

Once a market bounce begins it can fuel buying by bearish "short sellers" who had borrowed stock and sold it, betting on lower prices. As they rush to buy shares to close out their trades they feed the rebound.

Short-covering helped drive the previous four rallies. But the effect wasn't long-lived.

The difference this time, however, is that even the short sellers have to wonder if they're overestimating how much more damage the economy and the stock market are likely to sustain.

Reports this week showed that sales of both new and existing homes rose in February, albeit from deeply depressed levels in January. Likewise, orders for big-ticket manufactured goods were up last month, the first increase since July. On Friday the government reported that consumer spending inched up in February, the second consecutive gain.

Economy Raises Tentative Hopes a Trough Is Finally in Sight (KELLY EVANS, 3/28/09, WSJ)
This week, though, has brought a spate of good economic news. Consumer spending rose marginally in February, the Commerce Department said Friday, as did consumer sentiment in a household survey by Reuters and the University of Michigan. The housing market also appears to have stabilized from its free fall, and an uptick in orders for big-ticket items is helping raise hopes of a future pickup in manufacturing.

During a meeting with President Barack Obama and other bank executives Friday at the White House, Bank of America Corp. Chief Executive Ken Lewis and Northern Trust Corp. CEO Rick Waddell expressed cautious optimism that the economic downturn was either at or near the bottom of the cycle, according to people at the meeting.

Click on the image for state-by-state unemployment data from the Bureau of Labor Statistics, with year-over-year change in percentage points.

"There's growing evidence supporting the optimists' view, and I am surprised at that," said Robert J. Gordon, an economist at Northwestern University and a member of the National Bureau of Economic Research committee that is the official arbiter of when recessions begin and end. "I was sort of in the pessimists' camp until I started looking at things."

He points to one indicator in particular with a remarkable track record: the number of Americans filing new claims for unemployment benefits. In past recessions, it has hit its peak about four weeks before the economy hit a trough and began to grow again. As of right now, the four-week average of new claims hit its peak of 650,000 in the week ended March 14. Based on the model, "if there's no further rise, we're looking at a trough coming in April or May," he said, which is far earlier than most forecasts currently anticipate.

The most important thing to keep in mind about the credit crisis is that it has nothing (or little) to do with underlying economic conditions. As Richard Bookstaber writes in his extraordinarily useful book, A Demon of Our Own Design:
Stunning as such crises (the 1987 crash and the Long-Term Capital Management debacle) are, we tend to see them as inevitable. The markets are risky, after all, and we enter at our own peril. We take comfort in ascribing the potential for fantastic losses to the forces of nature and unavoidable market uncertainty.

But that is not the case. More often than not, crises aren't the result of sudden economic downturns or natural disasters. Virtually all mishaps over the past decade had their roots in the complex structure of the financial markets themselves. [...]

One of the curious aspects of worsening market crises and financial instability is that these events do not mirror the underlying real economy. In fact, while risk has increased for the capital markets, the real economy, the one we live in, has experienced the opposite. In recent decades the world has progressively become a less risky place, at least when it comes to economics. [...]

[B]reakdowns come about not in spite of our efforts at improving market design, but because of them. The structural risk in the financial markets is a direct result of our attempts to improve the state of the financial markets; its origins are in what we would generally chalk up as progress. The steps that we have taken to make the markets more attuned to our investment desires--the ability to trade quickly, the integration of the financial markets into a global whole, ubiquitous and timely market information, the array of options and other derivative instruments--have exaggerated the pace of activity and the complexity of financial instruments that makes crises inevitable. Complexity cloaks catastrophe.

Thus, we have the unfortunate spectacle of the Right trying to blame subprime borrowers, or Democrat congressmen, or federal rules and regulations, or budget deficits or whatever for a crisis that was actually brought on by the "capitalists" they consider their own natural constituency. The problem was not that the drive to increase home ownership requires lending to inherently riskier borrowers but that Wall Street used complex instruments to try to disperse said risks--if we put a charitable face on it--or disguise that risk from unwary investors, in the worst reading of their actions.

Mapping the Market Genome (Rick Bookstaber, 2/28/09)

A market crisis occurs when there are highly leveraged investors in a market that is under stress. These investors are forced to sell to meet their margin requirements. Their selling drops prices further – especially because the market was under stress to begin with. So you get a cascade down in the price of that market. A shock that might have initially led to only a five percent drop gets amplified, and the market might drop multiples of that. We have seen this in various guises in the current crisis, from the banks' 'toxic waste', to the downward spiral in housing prices, to the deleveraging of the carry trade, to the quant fund crisis in August 2007.

And the dynamic gets worse. Many of those under pressure to liquidate will discover they no longer can sell in the market that is under stress. If they can’t sell what they want to sell, they sell whatever else they can. So now they move to a second market where they have exposure and start selling there. If many of those who are in the first market also are in the second one, and if the investors in that market are also leveraged, then we see the contagion occur.

Here are two examples of what I am talking about.

Example one is LTCM. The proximate cause of LTCM’s demise was the Russian default in August, 1998. But LTCM was not highly exposed to Russia. A reasonable risk manager, aware of the Russian risks, might not have viewed it as critical to the firm. So how did it hurt them? It hurt them because many of those who did have high leverage in Russia also had positions in other markets where LTCM was leveraged. When the Russian debt markets failed and these investors had to come up with capital, they looked around and sold their positions in, among other things, Danish mortgage bonds. So the Danish mortgage bond market went into a tail spin, and because LTCM as big in that market, it took LTCM with it.

Example two is what happened with the Hunt silver bubble. When the bubble burst in 1980, guess what market ended up being correlated almost one-to-one with silver. Cattle. Why? Because the Hunts had to come up with margin for their silver positions, and they happened to have large holdings of cattle that they could liquidate.

Could we have ever anticipated beforehand that we would see a huge, correlated drop in both Russian MinFins and Danish Mortgage bonds? Or in silver and cattle? There is no way these dynamics can be uncovered with conventional, historically based VaR type of analysis. The historical return data do not tell us much if anything about leverage, crowding and linkages based on position holdings.

This is not to say VaR is not of value. I think everyone who is involved in risk management understands the limitations of VaR, what it can and cannot do. It is sometimes put up as a straw man because it is not doing things it was not designed to do, things it cannot do, such as assess these sorts of liquidity crisis events and the resulting cascade of correlations that result.

But the proper use of mark up languages along the lines of XBRL can give us the data we need to address market crises as they start to form. What we must do is have a regulator that extracts the relevant data – in this case position and leverage data – from major investment entities. These would include, as a start, the large banks and largest hedge funds. With assurances of data security – the data would not be revealed beyond the regulator – a government risk manager would then be able to know what currently cannot be known: where is there crowding in the markets, where are there ‘hot spots’ of high leverage, what linkages exist in the event of a crisis based on the positions these investors hold?

For these reasons, the first recommendation in both my Senate and House testimony was “get the data”. How can we do that? Well, first, by legislative demands to require investment firms -- including large hedge funds -- to provide the data. Then by the proper application of a mark up language so it can be done in a consistent, aggregatable way.

To give an analogy for this, one that came out in the conference and that illustrates how far behind we are in financial markets, a mark up language for risk would do for the financial products what bar codes already do for real products. If we discover a problem with peanuts being processed in some factory, we can use the bar codes to know where each product containing those peanuts is in the supply chain, all the way down to the grocery store shelf.

Having the proper tags – the proper bar code, if you will – for financial products, ranging from bonds and equities to structured products and swaps will allow us to understand the potential for crisis events and system risk. It will help us anticipate the course of a systemic shock. It will identify cases where many investors might be acting prudently, but where their aggregate positions lead to a level of risk which they on their own cannot see.

They Tried to Outsmart Wall Street (DENNIS OVERBYE, 3/10/09, NY Times)

The Physics of Money

Physicists began to follow the jobs from academia to Wall Street in the late 1970s, when the post-Sputnik boom in science spending had tapered off and the college teaching ranks had been filled with graduates from the 1960s. The result, as Dr. Derman said, was a pipeline with no jobs at the end. Things got even worse after the cold war ended and Congress canceled the Superconducting Supercollider, which would have been the world’s biggest particle accelerator, in 1993.

They arrived on Wall Street in the midst of a financial revolution. Among other things, galloping inflation had made finances more complicated and risky, and it required increasingly sophisticated mathematical expertise to parse even simple investments like bonds. Enter the quant.

“Bonds have a price and a stream of payments — a lot of numbers,” said Dr. Derman, whose first job was to write a computer program to calculate the prices of bond options. The first time he tried to show it off, the screen froze, but his boss was fascinated anyway by the graphical user interface, a novelty on Wall Street at the time.

Stock options, however, were where this revolution was to have its greatest, and paradigmatic, success. In the 1970s the late Fischer Black, then at the University of Chicago, and Myron S. Scholes and Robert C. Merton, both then at M.I.T., had figured out how to price and hedge these options in a way that seemed to guarantee profits. The so-called Black-Scholes model has been the quants’ gold standard ever since.

In the old days, Dr. Derman explained, if you thought a stock was going to go up, an option was a good deal. But with Black-Scholes, it doesn’t matter where the stock is going. Assuming that the price of the stock fluctuates randomly from day to day, the model provides a prescription for you to still win by buying and selling the underlying stock and its bonds.

“If you’re a trading desk,” Dr. Derman explained, “you don’t care if it goes up or down; you still have a recipe.”

The Black-Scholes equation resembles the kinds of differential equations physicists use to represent heat diffusion and other random processes in nature. Except, instead of molecules or atoms bouncing around randomly, it is the price of the underlying stock.

The price of a stock option, Dr. Derman explained, can be interpreted as a prediction by the market about how much bounce, or volatility, stock prices will have in the future.

But it gets more complicated than that. For example, markets are not perfectly efficient — prices do not always adjust to right level and people are not perfectly rational. Indeed, Dr. Derman said, the idea of a “right level” is “a bit of a fiction.” As a result, prices do not fluctuate according to Brownian motion. Rather, he said: “Markets tend to drift upward or cascade down. You get slow rises and dramatic falls.”

One consequence of this is something called the “volatility smile,” in which options that benefit from market drops cost more than options that benefit from market rises.

Another consequence is that when you need financial models the most — on days like Black Monday in 1987 when the Dow dropped 20 percent — they might break down. The risks of relying on simple models are heightened by investors’ desire to increase their leverage by playing with borrowed money. In that case one bad bet can doom a hedge fund. Dr. Merton and Dr. Scholes won the Nobel in economic science in 1997 for the stock options model. Only a year later Long Term Capital Management, a highly leveraged hedge fund whose directors included the two Nobelists, collapsed and had to be bailed out to the tune of $3.65 billion by a group of banks.

Afterward, a Merrill Lynch memorandum noted that the financial models “may provide a greater sense of security than warranted; therefore reliance on these models should be limited.”

That was a lesson apparently not learned.

Respect for Nerds

Given the state of the world, you might ask whether quants have any idea at all what they are doing.

Comparing quants to the scientists who had built the atomic bomb and therefore had a duty to warn the world of its dangers, a group of Wall Streeters and academics, led by Mike Brown, a former chairman of Nasdaq and chief financial officer of Microsoft, published a critique of modern finance on the Web site last fall calling on scientists to reinvent economics.

Lee Smolin, a physicist at the Perimeter Institute for Theoretical Physics in Waterloo, Ontario, who was one of the authors, said, “What is amazing to me as I learn about this is how flimsy was the theoretical basis of the claims that derivatives and other complex financial instruments reduced risk, when their use in fact brought on instabilities.”

Posted by Orrin Judd at March 28, 2009 7:55 AM
blog comments powered by Disqus