Financial Models and Market Volatility

As anybody who pays attention to the stock market will tell you, these past few weeks have been particularly volatile. Volatility is what drives a market really. Volatility creates opportunity; it also destroys wealth if one is not careful.

The past few years have seen a major sea-change wash over Wall Street regarding the way it conducts business. Many jobs that were formerly carried out by a living, breathing person are now being done by a computer model, especially in the equities arena. But models are only as smart as the person programming them, and these past few weeks have been humbling for many "quant" guys to say the least.

I could never shake the feeling that the almost countless number of hedge funds popping up virtually each day were all using essentially the same algorithms to employ the same strategies across the same markets. Taking this feeling to it's logical end will lead one to conclude that the marketplace is crowded with many people doing the same thing, just like sheep.

Since I am one of a declining number of living, breathing bodies left on Wall Street, I can not help but feel a bit of schadenfreude at the misfortune many of these quantitative hedge funds are experiencing at the moment. Math Ph.d's and statistical geniuses have their place in finance to be sure, but perhaps they may want to take a moment to reflect on a few of the things I have learned over the course of my career:

• The stock market is a fickle dance partner
• If you are in a "crowded" trade, you better be the first one out of it when things go bad
• You may think something is worth X, but it's really only worth as much as somebody else is willing to pay for it. Don't be surprised if it's 20 cents on the dollar.
  
• If I'm a seller and there's no buyer around, the smartest algorithm in the world isn't going to find me a buyer
• Nobody can accurately predict, let alone factor human emotion into a trade
• All models work, until they don't
  

The following snippets from a Financial Times article (subscription only) perfectly illustrate the hubris that many quant funds fell prey to.

Limitations of computer models

By Gillian Tett and Anuj Gangahar

Published: August 14 2007 19:28 | Last updated: August 14 2007 19:28

In recent years, Goldman Sachs has become renowned as one of the savviest players on Wall Street. This week, however, the mighty US bank was forced into an embarrassing admission.

In a rare unplanned investor call, the bank revealed that a flagship global equity fund had lost over 30 per cent of its value in a week because of problems with its trading strategies created by computer models. In particular, the computers had failed to foresee recent market movements to such a degree that they labelled them a “25-standard deviation event” – something that only happens once every 100,000 years or more.

The credit crunch caused by the sub-prime meltdown was an event that nobody saw coming. The resulting fallout was something that was 25 standard deviations beyond the realm of reasonable possibilities--something that could only occur once in 100,000 years. Please, pass the doobie my way! Acknowledging that hindsight is 20/20 and all that, even I saw the sub-prime meltdown coming last April; and I am far from the savviest guy on the Street.

“We are seeing things that were 25-standard deviation events, several days in a row,” said David Viniar, Goldman’s chief financial officer. “There have been some issues [before] in some of the other quantitative spaces, but nothing like what we saw last week.”

So something that should only occur once every 100,000 years is actually happening several days in a row. I wish I had that kind of luck playing the lottery. I might buy a ticket from time to time.

By any standards, it is a striking admission, given that these losses at the Goldman fund could top $1.5bn (£750m, €1.1bn). But what is more startling still is that Goldman Sachs is not alone in seeing its models go haywire. On the contrary, in recent days a host of other funds have experienced similar difficulties, including highly renowned funds at Renaissance Technologies.

James Simons, founder of Renaissance and one of the most respected quantitative fund managers, last week wrote a letter to investors saying losses were about 9 per cent in the first few days of August (the funds have since recovered at least some of the losses). He also tellingly wrote that “we cannot predict the duration of the current environment,” highlighting the fact that even a group such as Renaissance – whose flagship fund, Medallion, has had an annual return of 30 per cent since 1988 – is suffering badly from recent movements.

An annual return of 30% since 1988 is stellar I'd say. Taking into account the standard hedge fund fee of 2% of total assets plus 20% of profits, somebody that invested $100,000 19 years ago and let the profits ride each year would be $4.3 million richer today. Of course that's before taxes. I wonder how Medallion would quantify, "suffering badly" in that context?

A glance at recent financial history shows that this type of “rare” event is not so unusual at all. Back in 1998, for example, a key reason for the near-implosion of Long Term Capital Management was that the fund’s economic whizzkids – who included some Nobel prize-winning economists – had devised model-based trading strategies that turned sour when markets moved in unforeseen ways. Similarly, two years ago the financial industry received a shock when General Motors, the US car group, was downgraded – a move that left the price of financial assets gyrating in relation to each other in ways computers had not predicted.

The question now being asked by some bankers – and regulators – is whether this week’s events show that the modern financial industry is foolish to be placing so much faith in these complex computer-driven models.

“People say these are one-in-a-100,000-years events but they seem to happen every year,” says Satyajit Das, a consultant to hedge funds and investment banks. “This episode should make people ask questions about models – I think it could lead to a real reassessment.”

Finally, a voice of reason. Truth be told though, the market can handle blow ups like this from time to time. I think it's a good thing actually. Call it the Darwinism of the marketplace; it keeps people honest, and it washes out the poseurs. Heck, it may even keep me relevant for a few more years.

The whole story reminds me of the Maginot Line. Essentially when the Germans reached France, they saw the complex fortifications the French had meticulously built, and simply went around them.

I wonder what those who are modeling climate change think of all this?