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Jul. 21, 2009
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Value at Risk – How One Formula Paved the Way to Hell

It was in August 2008 that Malcolm Casey*, a resident of Highland Park (New Jersey, US), was getting a little worried. For months and months his portfolio, consisting mostly of “defensive” structured products, has been generating losses and being just a few years away from retirement, he felt that his life savings were in danger.

He went to his bank in nearby New York City, a bank that since ceased to exist, swallowed by another Wall Street giant. His adviser, a smart thirty-something with a Harvard Business School MBA plus CFA, calmed him down saying: “Don’t worry, Mac. Our risk management is working well. Just have a look at this ONE number: VaR (Value at Risk). It tells the whole story. There is only an extremely low probability that you might lose more than USD 10,000.” Casey calmed down. He had no mathematical training except from some high school math, dating back about 35 years. But he trusted the number guys. He always trusted hard facts. Based on a vast collection of data from 20 years there was no chance that they would not predict a possible crash. Just watch this one number, VaR. That was what they told him.

Then came Lehman Brothers. It was like Armageddon to Casey’s Portfolio. For days, there was not even a liquid market for all the structured products he had in his portfolio. By November 2008 he was down another 48%. His adviser had disappeared without a trace. His bank now had a different name. Casey was naturally furious about the whole situation. And he started to ask a lot of furious questions about VaR.

VaR (Value at Risk) is one of the most important risk measures used for measuring potential losses of your portfolio. It basically says: There is an X% probability that you lose USD Y during a specified period of time. Usually the probability level is 1% and the time horizon is from one to seven days. This number is based on the observance of past financial data, normally going back one or two decades. VaR was created and popularised in the 1990s by some scientists and mathematicians — “quants” is their nickname — who went to work for JP Morgan. VaR’s great advantage, and its great selling point to people who do not happen to be mathematicians, in that it expresses risk as a single number, an amount of dollars to be specific.

Despite its popularity, VaR has had its critics for a long time. Business professor Nassim Taleb has pointed out the shortcomings of VaR since the 1990s. His point is very simple: With our usual statistical tools we cannot predict rare but catastrophic events. He calls them Black Swan events. Because VaR is based on just those normal statistical distributions it fails to predict the “big one”. If you look at it from a mathematical point of view, VaR looks only at the centre of a probability distribution, things that happen relatively frequently, but it misses the tails of the distribution. It does not catch the outliers or freak events that may have a truly devastating impact.

This is also the reason why David Einhorn, a famous hedge fund manager, who shorted Lehman Brothers long before the firm went down, compared VaR to “an airbag that works all the time, except when you have an accident.”

On top of these inherent technical problems of VaR comes the fact that most wealth advisers are sales people not financial mathematicians. They had no clue on how to interpret VaR numbers correctly and just tell their wealthy clients that this number was the maximum loss that would be possible. And this is a fatal error. VaR does not reflect the maximum loss rather it gives a probability of a relatively likely, modest loss. But the wealth advisers used the number as a sedative rather than an analytical tool. And their clients fell asleep.

What should be the consequences for private investors?

  • Firstly, do never ever trust one single risk metric. It possibly can never reflect all different real world risks your portfolio faces.

  • Insist that your adviser explains in very plain words the meaning and relevance of your VaR number and all other risk metrics he may present to you.

  • Prepare for the worst case, even if that case has a probability below 1%. For example, do not buy structured products from only one or two issuers. Because structured products carry the risk that an issuer goes bankrupt (even though that probability may be very low).

  • Look for qualitative signs that a market is overheating and running the risk of a crash: If your cab driver gets excited about real estate in Florida take it as a red flag. If your wealth adviser sends you all those mails about Chinese tech stocks, listen to the alarm bell ringing.

*for reason of privacy we have kept the real name confidential

 

 

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Products: How Risky Are Your Financial Products?

Value at Risk – How One Formula Paved the Way to Hell

  Jul. 21, 2009

It was in August 2008 that Malcolm Casey*, a resident of Highland Park (New Jersey, US), was getting a little worried. For months and months his portfolio, consisting mostly of “defensive” structured products, has been generating losses and being just a few years away from retirement, he felt that his life savings were in danger.

He went to his bank in nearby New York City, a bank that since ceased to exist, swallowed by another Wall Street giant. His adviser, a smart thirty-something with a Harvard Business School MBA plus CFA, calmed him down saying: “Don’t worry, Mac. Our risk management is working well. Just have a look at this ONE number: VaR (Value at Risk). It tells the whole story. There is only an extremely low probability that you might lose more than USD 10,000.” Casey calmed down. He had no mathematical training except from some high school math, dating back about 35 years. But he trusted the number guys. He always trusted hard facts. Based on a vast collection of data from 20 years there was no chance that they would not predict a possible crash. Just watch this one number, VaR. That was what they told him.

Then came Lehman Brothers. It was like Armageddon to Casey’s Portfolio. For days, there was not even a liquid market for all the structured products he had in his portfolio. By November 2008 he was down another 48%. His adviser had disappeared without a trace. His bank now had a different name. Casey was naturally furious about the whole situation. And he started to ask a lot of furious questions about VaR.

VaR (Value at Risk) is one of the most important risk measures used for measuring potential losses of your portfolio. It basically says: There is an X% probability that you lose USD Y during a specified period of time. Usually the probability level is 1% and the time horizon is from one to seven days. This number is based on the observance of past financial data, normally going back one or two decades. VaR was created and popularised in the 1990s by some scientists and mathematicians — “quants” is their nickname — who went to work for JP Morgan. VaR’s great advantage, and its great selling point to people who do not happen to be mathematicians, in that it expresses risk as a single number, an amount of dollars to be specific.

Despite its popularity, VaR has had its critics for a long time. Business professor Nassim Taleb has pointed out the shortcomings of VaR since the 1990s. His point is very simple: With our usual statistical tools we cannot predict rare but catastrophic events. He calls them Black Swan events. Because VaR is based on just those normal statistical distributions it fails to predict the “big one”. If you look at it from a mathematical point of view, VaR looks only at the centre of a probability distribution, things that happen relatively frequently, but it misses the tails of the distribution. It does not catch the outliers or freak events that may have a truly devastating impact.

This is also the reason why David Einhorn, a famous hedge fund manager, who shorted Lehman Brothers long before the firm went down, compared VaR to “an airbag that works all the time, except when you have an accident.”

On top of these inherent technical problems of VaR comes the fact that most wealth advisers are sales people not financial mathematicians. They had no clue on how to interpret VaR numbers correctly and just tell their wealthy clients that this number was the maximum loss that would be possible. And this is a fatal error. VaR does not reflect the maximum loss rather it gives a probability of a relatively likely, modest loss. But the wealth advisers used the number as a sedative rather than an analytical tool. And their clients fell asleep.

What should be the consequences for private investors?

  • Firstly, do never ever trust one single risk metric. It possibly can never reflect all different real world risks your portfolio faces.

  • Insist that your adviser explains in very plain words the meaning and relevance of your VaR number and all other risk metrics he may present to you.

  • Prepare for the worst case, even if that case has a probability below 1%. For example, do not buy structured products from only one or two issuers. Because structured products carry the risk that an issuer goes bankrupt (even though that probability may be very low).

  • Look for qualitative signs that a market is overheating and running the risk of a crash: If your cab driver gets excited about real estate in Florida take it as a red flag. If your wealth adviser sends you all those mails about Chinese tech stocks, listen to the alarm bell ringing.

*for reason of privacy we have kept the real name confidential