In financial mathematics and financial risk management, Value at Risk (VaR) is a widely used measure of the risk of loss on a specific portfolio of financial assets. For a given portfolio, probability and time horizon, VaR is defined as a threshold value such that the probability that the mark-to-market loss on the portfolio over the given time horizon exceeds this value (assuming normal markets and no trading) is the given probability level.[1]VAR has been criticised;
For example, if a portfolio of stocks has a one-day 5% VaR of $1 million, there is a 5% probability that the portfolio will fall in value by more than $1 million over a one day period, assuming markets are normal and there is no trading. Informally, a loss of $1 million or more on this portfolio is expected on 1 day in 20. A loss which exceeds tha VaR threshold is termed a “VaR break.
VaR has been controversial since it moved off of trading desks and into the public eye in 1994. A famous 1997 debate between Nassim Taleb and Philippe Jorion set out some of the major points of contention. Taleb claimed VaR:[20]
- Ignored 2,500 years of experience in favor of untested models built by non-traders
- Was charlatanism because it claimed to estimate the risks of rare events, which is impossible
- Gave false confidence
- Would be exploited by traders
More recently David Einhorn and Aaron Brown debated VaR in Global Association of Risk Professionals Review[12] [21] Einhorn compared VaR to “an airbag that works all the time, except when you have a car accident.” He further charged that VaR:New York Times reporter Joe Nocera wrote an extensive piece Risk Mismanagement[22] on January 4, 2009 discussing the role VaR played in the Financial crisis of 2007-2008. After interviewing risk managers (including several of the ones cited above) the article suggests that VaR was very useful to risk experts, but nevertheless exacerbated the crisis by giving false security to bank executives and regulators. A powerful tool for professional risk managers, VaR is portrayed as both easy to misunderstand, and dangerous when misunderstood
- Led to excessive risk-taking and leverage at financial institutions
- Focused on the manageable risks near the center of the distribution and ignored the tails
- Created an incentive to take “excessive but remote risks”
- Was “potentially catastrophic when its use creates a false sense of security among senior executives and watchdogs.”
The following is from the above mentioned NYT Nocera article;
Eventually, though, you do start to get the point. Taleb says that Wall Street risk models, no matter how mathematically sophisticated, are bogus; indeed, he is the leader of the camp that believes that risk models have done far more harm than good. And the essential reason for this is that the greatest risks are never the ones you can see and measure, but the ones you can’t see and therefore can never measure. The ones that seem so far outside the boundary of normal probability that you can’t imagine they could happen in your lifetime — even though, of course, they do happen, more often than you care to realize. Devastating hurricanes happen. Earthquakes happen. And once in a great while, huge financial catastrophes happen. Catastrophes that risk models somehow always manage to miss.
