Risk Mismanagement: Model Fails To Take Into Account Real Risks

The NY Times recently ran an intriguing article discussing the primary risk model (or collection of models) used by the banks during the credit boom, with a particular focus on the model’s short-comings and how they fail to take into account the real risks that can bring the house down.

From the NY Times:

There are many such models, but by far the most widely used is called VaR - Value at Risk. Built around statistical ideas and probability theories that have been around for centuries, VaR was developed and popularized in the early 1990s by a handful of scientists and mathematicians - “quants,” they’re called in the business - who went to work for JPMorgan . VaR’s great appeal, and its great selling point to people who do not happen to be quants, is that it expresses risk as a single number, a dollar figure, no less.

VaR isn’t one model but rather a group of related models that share a mathematical framework. In its most common form, it measures the boundaries of risk in a portfolio over short durations, assuming a “normal” market. For instance, if you have $50 million of weekly VaR, that means that over the course of the next week, there is a 99 percent chance that your portfolio won’t lose more than $50 million. That portfolio could consist of equities, bonds, derivatives or all of the above; one reason VaR became so popular is that it is the only commonly used risk measure that can be applied to just about any asset class. And it takes into account a head-spinning variety of variables, including diversification, leverage and volatility, that make up the kind of market risk that traders and firms face every day.

Another reason VaR is so appealing is that it can measure both individual risks - the amount of risk contained in a single trader’s portfolio, for instance - and firmwide risk, which it does by combining the VaRs of a given firm’s trading desks and coming up with a net number. Top executives usually know their firm’s daily VaR within minutes of the market’s close.

Risk managers use VaR to quantify their firm’s risk positions to their board. In the late 1990s, as the use of derivatives was exploding, the Securities and Exchange Commission ruled that firms had to include a quantitative disclosure of market risks in their financial statements for the convenience of investors, and VaR became the main tool for doing so. Around the same time, an important international rule-making body, the Basel Committee on Banking Supervision, went even further to validate VaR by saying that firms and banks could rely on their own internal VaR calculations to set their capital requirements. So long as their VaR was reasonably low, the amount of money they had to set aside to cover risks that might go bad could also be low.

Given the calamity that has since occurred, there has been a great deal of talk, even in quant circles, that this widespread institutional reliance on VaR was a terrible mistake. At the very least, the risks that VaR measured did not include the biggest risk of all: the possibility of a financial meltdown. “Risk modeling didn’t help as much as it should have,” says Aaron Brown, a former risk manager at Morgan Stanley who now works at AQR, a big quant-oriented hedge fund. A risk consultant named Marc Groz says, “VaR is a very limited tool.” David Einhorn, who founded Greenlight Capital, a prominent hedge fund, wrote not long ago that VaR was “relatively useless as a risk-management tool and potentially catastrophic when its use creates a false sense of security among senior managers and watchdogs. This is like an air bag that works all the time, except when you have a car accident.” Nassim Nicholas Taleb, the best-selling author of “The Black Swan,” has crusaded against VaR for more than a decade. He calls it, flatly, “a fraud.”

The article is a rather detailed ten pages so I think it’s more sense to just point everyone to it, as I could easily write a multi-page review/assessment of it - namely, it’s not something that lends well to the blogging format. However I will say that it’s definitely your time to read it as you can not only gain some insights into the risk models used by various banks, but also understand how they only exclude certain key risks, and aren’t as “objective” as one might think since they tend to be viewed through the prism of the user’s desired or expected outcomes.

You can read the article in full here.

Source:

The NY Times: “Risk Mismanagement” - Joe Nocera, January 2, 2009.

Disclosure: at the time of publishing the author didn’t own a position in any of the companies mentioned in this article; the ideas expressed are solely the opinions of the author and shouldn’t be viewed as financial or investment advice.

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