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Notes from James Montier's The Flaws of Finance speech (given before the JPM news): "If you give...
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Sunday, May 13, 2012, 9:08 AM ETNotes from James Montier's The Flaws of Finance speech (given before the JPM news): "If you give CAPM and VaR to monkeys, they're going to create a financial crisis ... VaR (Value-at-Risk) is like a vest that is 95% bulletproof (fails when you need it) ... Bad models and bad assumptions tend to replace common sense ... The more abstruse the maths, the more uncertain the results." (full speech starting at about 18 min. mark; h/t Josh Brown)
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JPMorgan also restated its “value at risk”, a measure of maximum possible daily losses, of the CIO [the unit that executed the trading strategy that blew up] in the first quarter from $67m to $129m
As Yves Smith observes “Restating” greatly underplays the significance of what happened. VaR is a prospective risk metric. From ECONNED:
…the objective was to come up with a single figure that captured all the risks in a simple statistical fashion: what was the risk that the bank would lose a certain amount of money, specified to a threshold level of probability, in, say, the next 24 hours? The model output would say something like: “We have 95% odds of losing no more than $300 million dollars in the next 24 hours.”
She goes on to observe "There is a tremendous bias towards scientism, towards undue faith in quantification and statistics But VaR is a particularly troubling example, more so because it is sufficiently, dangerously simple minded enough that regulators and managers a step or two removed from markets have become overly attached to its deceptive simplicity
It took seven years of refinements to reach that goal, which should have been seen as a warning that it might not be such a good idea.
Perhaps we should have a "holy shit could this happen" metric in use by the fed as a cap on the "maximum monetized egotistical stupidity at work" on Wall STreet.
Having said that I don't believe Finance has "physics envy" any more than marketing or Economics. Finance does need models and various tools to help understand exposure and investment risk. It cannot be gut feel and finger to the wind stuff. The trick IMO is to understand the weaknesses and strengths of the tools involved and then layer in experienced traders and oversight so that 20 or 30 somethings are not making massive decisions with relatively no experience to understand what might go wrong. A company also needs it skeptics to constantly look for the downside and most companies get rid of those people as they are not "team players." That is a mistake. A bigger mistake is to trust the tools as if they are reality. They are only tools or frameworks for analysis if you will that are on the dashboard. They are not the view through the windshield and it seems a lot of people don't think about this deep enough in the public or private sector.
Another good book on this problem is Black Swan by Nassim Taleb.
There is a time and a place for everything. As a very long term trader who has seen most everything, you can feel when things are not going well. The hardest trade in the world is the one which cuts the position and locks in the loss. It also allows you to fight again another day. Sort of like that description of porn, without a 'model' definition: you know (a bad trade) when you see it. There are alarm bells going off everywhere in your gut. Maybe the young guns who slice these enornmous balonies, and who fancy themselves 'traders', just don't have that 'feeling in their gut'. Yet.
You are experienced by your own description which is your advantage. I should have said "solely" on gut feel as that can just be paranoia and exuberance driving strategies.
James Suroweicki's excellent book 'The Wisdom of Crowds' cites four criteria necessary for a crowd-based analysis (such as a market) to be accurate:
1) Diversity of opinion (each participant should have some private information, even if it's just an unusual interpretation of known facts)
2) Independence (participants' opinions are not determined by the opinions of other participants)
3) Decentralization (participants can specialize and draw on local knowledge)
4) Aggregation (something turns private assessments into a collective answer)
Our modern markets fail miserably in #2, Independence. Too often, stocks are bought or sold not because the price is too high or low from the estimated actual value, but because models or opinions indicate that /other/ people will think the price is high or low. Or because people think that other people will think that other people will think (and so on) that the price is too high or low. Sometimes the decoupling gets pretty far out there.
In addition, with the "benefit" of widely available disclosed information, #1 (diversity of opinion) and #3 (decentralization) are not terribly reliable either -- certainly inside information held by a few is bad for accuracy, but so is a herd mentality.
Simply put, all models are wrong, some models are useful. A a corollary to that is that the more precise the model tries to be, the less useful it usually is. :)
What do you mean "all models are wrong"
http://bit.ly/McPLD8
Basically, any statistical model will fail to match the real world exactly, for many reasons, not the least of which is that a model is inherently a simplification of the real world.
Some models are still "useful" simply because they are close enough, but only if given the proper assumptions and proper uses. For example, assuming that you 95% confidence model will make you money 100% of the time, is probably /not/ a good assumption. :)
Thanks. That statement should be sobering for anyone using models to not blindly follow them.
Clearly such probabilistic models can never be tested in practice.
1) JM pretends to be an investment guru, while he himself has started managing money only recently. Most of his life has been spent writing from the sidelines...in order to be a real "behavioral finance" expert, you really have to manage money for a long time, know what is like to lose/make money, get the gut ripped out, face the ego issues, etc.. He hasn't done it. Like a classic wall street expert, he is very good at presentations/writing and claiming superiority.
2) He contradicts himself. After 2008 he is talking about "bad models' Pre-crisis, he was praising the superiority of pure quant models.
http://bit.ly/LMLqTu.
3) He rightly points out that investing is about the long term. Let him first manage money for 10-20years before pontificating.
May be he should add an oath at the end "Thou shall not pontificate or pretend to be an expert on what I have not done myself".