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The Perils of Simplifying Risk To a Single Number
A few weeks back we discussed the perspective that the economic meltdown could be viewed as a global computer crash. In the NYTimes magazine, Joe Nocera writes in much more depth about one aspect of the over-reliance on computer models in the ongoing unpleasantness: the use of a single number to assess risk. Reader theodp writes: "Relying on Value at Risk (VaR) and other mathematical models to manage risk was a no-brainer for the Wall Street crowd, at least until it became obvious that the risks taken by the largest banks and investment firms were so excessive and foolhardy that they threatened to bring down the financial system itself. Nocera explores the age-old debate between those who assert that the best decisions are based on quantification and numbers, and those who base their decisions on more subjective degrees of belief about the uncertain future. Reliance on models created a 'false sense of security among senior managers and watchdogs,' argues Nassim Nicholas Taleb, who likens VaR to 'an air bag that works all the time, except when you have a car accident.'"
For an EXCELLENT article about this, read Malcolm Gladwell's "Blowing up", which you can find online for free:
http://www.gladwell.com/2002/2002_04_29_a_blowingup.htm
Watch the Teaser Trailer for "The Lightning Thief" Her
Nocera explores the age-old debate between those who assert that the best decisions are based on quantification and numbers, and those who base their decisions on more subjective degrees of belief about the uncertain future.
Why is anyone still making this distinction, as we now know that the only self-consistent numerical representation of risk follows directly from our subjective degrees of belief about the uncertain future? Furthermore, we have known this for over a generation... isn't it about time that the knowledge start filtering into the popular discourse?
While Bayesian methods are not always all that useful for practical problems (I use them on occasion in my work) the conceptual foundations and deeper understanding of the nature of plausible reasoning and its relation to probability theory needs to be more widely understood.
One of the big take-home messages from the Bayesian revolution is that probability theory is nothing but quantification of what we do subjectively, insofar as our subjective impressions are self-consistent, so the only people who are still debating quantitative vs subjective approaches as such are people who do not understand the question.
Blasphemy is a human right. Blasphemophobia kills.
Risk models are largely irrelevant because the only risk anyone in the financial sector is really interested in minimizing is the risk that they will get fired. The way to do that is to do almost exactly the same thing as everybody else, no matter how mind blowing stupid it is. Plenty of people realized that banks etc were not nearly as sound as commonly believed years ago. Those that tried to act on this were fired long ago since they weren't making as high a ROI as those willing to invest in dodgy hedgefunds etc. Rational market my ass.
http://rareformnewmedia.com/
If the Government becomes a lawbreaker, it breeds contempt for law;
After seeing the rampant fraud committed by the global financial elite, I'm very inclined to agree with you. What we need isn't just a number that quantifies risk, but also a number that quantifies trust.
I would pay for a service that tracks every person involved in business that was ever convicted, under indictment, or subject of a complaint. It should also track which firms employed them and where they are working now. It should also cover which "civil servants" were "on watch" at the time.
In the land of the blind, the one-eyed man is usually crucified.
As an example, suppose that the distribution suggests the chance of losing 50 million dollars is +3 sigma for some measure. The problem is that there is a subtle effect - say panic, herd effect or some interaction of derivative models - which only becomes significant around the 3 sigma mark. The result could be that the exposure at a 4 sigma event is billions of dollars. A proper risk model would need to take this into account
My conclusion based on what I have read so far is that the physicists (in particular) involved in developing quantitative models would have benefited from a lot more exposure to real world experiment. They would then have had more of a clue about the unreliability of data away from the mean, scatter, and the importance of the fact that in physics subtle errors turn out to be signs that the model is wrong - e.g. relativistic effects only become important at a significant fraction of c.
From scarped cliff or quarried stone she cries "A thousand types are gone, I care for nothing, no not one."
A friend of mine is a risk assessment quant who was working at Lehman right up to the point where they declared bankruptcy. I asked him about this article the other day. He said that their models started telling them something was very wrong back in 2007. The problem was that Fuld (the CEO) refused to believe what the models were saying.
The most accurate model in the world won't help if you don't pay atention to the results it produces.
There's also apparently an issue with the classical VaR models depending on transparent pricing, which these real estate instruments lack. So some of the most troublesome assets apparently weren't in the model.
You might think that if you have three investments with a 10% risk of losing £1,000,000 the chances of all three of them losing £1,000,000 is 0.1*0.1*0.1 = 0.001 or 0.1%.
No, no-one who actually calculates and uses VaR thinks that. Anyone who has done any statistics, like all finance quants, will correctly take into account covariances. The actual problem is the interpretation of the "correct" VaR, and relying on it too heavily.
I'll give you the actual definition of VaR. If you calculate the VaR(10 day, 5%) to be $100,000, this means that there is a 5% chance that the loss on your portfolio over a 10 day period will be larger than $100,000, or that your profit will be larger than $100,000 assuming a symmetric distribution. It's when people think "Oh that's great, we can ONLY lose $100,000" when you have a problem. The actual loss could be ANY value larger than $100,000.
It's hardly a perfect statistic, since there are still many assumptions involved. However, it's still a decent estimator and it's better than making a wild guess based on gut feelings. Despite what most people currently believe, a lot of brainpower has gone into developing financial theories and some stuff is pretty damn good. The financial industry deserves some bashing, but it frustrates me when people spread incorrect information; at least complain about the right things.
You're assuming that the bet you're making when entering the stock market is "The price per share of the stock in [insert company here] will go up before I have reason to sell my shares." If that's the way you want to bet, fine - but you'd be an idiot to bet that way. You should be entering the stock market with this bet: "The combined value of change in price of the stock plus the dividends paid will be more than the value of what I paid for the stock." Note that I mentioned only value, not price. Although money has been described as "the universal symbol for value received", most currencies in use at this point are fiat currencies that have no fixed value, either in non-fiat currencies or in commodities. Therefore, what costs $1 today might cost $10 a week later. (In fact, Zimbabwe's economy has been doing this kind of thing recently.)
So, depending on how the rest of the economy changes - buying a stock at $100/share and selling it a year later at $10/share might actually be a good idea - if the stock paid out $95/share in dividends and the economy is otherwise unchanged, or if that $10 will buy more than $100 would have a year earlier.
Loose things are easy to lose. You're getting your hair cut. They're going there to see their aunt.
Wow. It looks like most people don't get it.
If Mr A gave Mr B billions of dollars of The Public's Money to play at a casino and both Mr A and Mr B got filthy rich when times were good, and when it blows up all that happens is Mr B loses his job and Mr A keeps his job by blaming Mr B or saying BS like "perfect storm/everyone was doing it".
Why then should Mr A and Mr B be doing things differently?
After all, in the following year, Mr A passes billions to Mr C who does pretty much the same thing as Mr B. And Mr B? He's hired by Mr D who wants Mr B to make him richer (just like he did for Mr A).
AFAIK, not long after LTCM blew up, its founder John Meriwether still managed to get hundreds of millions of dollars to start a hedge fund.
What I see are individuals making pretty rational decisions, those decisions sometimes just happen to be bad for a lot of other people. But why should those individuals care?
Their conscience should bother them? The last I checked the Economists leave the conscience stuff to "The Invisible Hand". People laugh at the religious, guess who really has even less of a clue on how things work? At least the religious have some idea about the "Invisible Hand" sort of stuff.
It's hilarious that you have all those people saying/writing stuff like "When Genius Failed".
That's like the sheep saying the wolves have failed just because the wolves dropped 95% of a billion sheep over a cliff, whilst "only" managing to stuff themselves to the brim with 1% of the billion sheep. I'm sure the wolves were a bit upset about the whole thing, but hey there are billions more sheep...
Yeah I see failure alright. Go figure where.
You want to reduce the risk of stuff blowing up, and how big they blow up? It has nothing to do with creating better financial models or better economic theories.
It has to do with making and enforcing rules like: if too many sheep die, we shoot and skin the wolves responsible. Simple as that.
All that transparency and regulation is worthless if at the end of the day the wolves get away.