... hear the words of Paul Volker, quoted the other day in the Wall Street Journal: "The market was being run by mathematicians that didn't know financial markets. And you keep hearing, you know, god, that event should only happen once every hundred years, according to my model. But those every hundred years events are coming along every two or three years, which should raise some questions."
Commentary on the model developed for layering debt: "Trouble awaits those who blindly trust the model's output instead of recognizing that they are making a bet based partly on what they told the model they think will happen. [Model creator David Li] worries that 'very few people understand the essence of the model.'"
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One usually resorts to a model when it's about something new and not well understood. Eventually, as data becomes available, the model accuracy can be verified, but not before.
How someone claims a probability of hundreds of years for a model that's months old is beyond me.
Or perhaps it's just snake-oil tactics, when the error margin for the stated probability is larger than itself. For instance, the probability for this to happen is 100 years, give or take 200 years. :-)
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Isn't what you wrote above the mathematics of probability?
**** Isn't what you wrote below analysis of cause and effect?
I'm not trying to be facetious or lay "traps" here - I really would like to clarify this.
I see the probabilities as a mathematical game not unlike roulette. I see analysis as absolutely critical to financial planning and investment.
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You're drifting over to my point of view! I see you!:-)
I'm still waiting for you to say "30 to 1 leverage on those credit derivatives!" C'mon ... I know you can say it!:-) Try it once where nobody can hear you! It won't hurt!
I do not disagree with you on what you wrote below - a bubble tends to catch an awful lot of people up in it's frenzy. There were loans made to those who could not, it turns out, afford them. No doubt some were really hurt by it - a young married couple, afraid to miss out on ever owning a home, and a lender believing house prices would only go higher bending over backwards to get them in. That makes me sad and angry - I'm not sure at whom - but basically it's at those who were in the housing market only seeking windfall profits.
On Mar 19, 4:45 pm, "Elle" wrote: [trim]
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Well sure. :-) I absolutely agree with your point that leveraging has aggravated the problem "greatly." Though I put the last word in quotation marks because it is hard to say anything with precision here, regarding the precise effects of the leveraging, and relative to the period around
1991, and just as the August 07 Fidelity report that you cited points out.
The magnitudes of which you (and Fidelity's paper, etc.) speak and other reports have me worried that this could be a mother of a recession. Hopefully I will be eating my words within a year. Whence I hope younger folks here and myself will have under our belts one more period of serious market correction to temper our thoughts on long term investing.
I do like that my IRA's reinvested dividends pick up more shares at bargain prices.
snip for brevity but all points noted
I think there's also a nasty myth going around, promoted by our government among others, that owning a home should be everyone's goal. As has been much discussed here, renting is often the better financial choice. Renting does not necessarily mean having less square feet.
Still, I put a lot of blame on those calling themselves "mathematicians" who participate in the financial industry. Unfortunately I suspect too often they do so thinking they can get rich quick through manipulation of numbers, when studies attest otherwise.
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True. Mathematical models for making predictions about the future have to assert something like "If a, b, c, ... are present, then the probability that x will happen is such-and-such." This may work for a while and lead to some accurate predictions, but almost always some further conditions not taken into consideration (d or e) will come along and make the model useless. This is especially likely to happen in long-term financial predictions, because so many unexpected variables can enter the picture as governments change, new things are invented, wars occur, etc.
The same principle applies not only to detailed mathematical models, but also to a lot of generally accepted wisdom such as "stocks return more in the long run than real estate," or "banks are secure," or "government bonds are safe," and so on. That is a reason I would argue that diversification among asset classes is just as important, if not more important, as diversification among stocks.
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Thanks for your reply. Your point about diversification among asset classes is well taken - the neglect of that was a fatal flaw in LTCM's blow up.
Augustine (on this thread) brought up a couple of good point that I think apply to the "derivatives" models. He refers to what have been called "fat tails" of the standard bell curve (the 'snake oil':-).
Have you (or has anyone here) read anything about the specifics of any "derivatives risk model" that would give specific insight into their construction?
On Mar 20, 11:50 am, Don wrote: [trim]
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Such events do occur, so such a statement can be true. What you are really objecting to is the second statement (below), I think.
Compared to what? Financial time series are go back further and have less estimation error than the data used in most other social sciences.
As a prominent statistician has said, "all models are wrong, some models are useful". A financial planner who wants to simulate the probability that a client will not run out of money in retirement must have a distribution of stock returns to draw from, for example, annual returns normally distributed with a mean of 10% and a standard deviation of 18%. If he samples from historical annual returns over the last 80 years instead of assuming normality, there is still an implicit return distribution. What is the alternative to some kind of model?
Shifting to Elle's message, mathematicians or "quants" are needed on Wall Street and in banks to determine interest rates on fixed rate and adjustable mortgages that still leave the lender a profit margin. Mortgages have considerable optionality, including the (1) ability of the borrower to prepay when rates fall (2) cap on interest rates often found on adjustable mortgages (3) ability of the borrower to walk away when "underwater", especially in non-recourse states such as California.
These options of the borrower make mortgage loans less attractive to the lender than investing a non-callable Treasury bond, and valuing them takes a quant. I think quants misvalued option (3), because that option rises in value when house prices fall nationwide.
Since models of mortgages will have uncertain inputs, highly leveraged structures of mortage-backed securities will be risky. I think the lesson of the mortgage crisis is not to avoid mathematical modeling but to limit leverage and ensure that modelers periodically examine their assumptions.
Ideally, there would be software to help borrowers determine what is the best loan for them, based on features in the checklist at
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. Forexample, if one ARM has a floating rate of 2% above LIBOR with a cap10%, and another has a floating rate of 3% above LIBOR but a cap of7%, a mathematical model is needed to determine which loan is better.The mortgage calculators I have seen are simplistic and do not makesuch comparisons.
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It is interesting that diversification among different assets is usually practiced by people with a whole lot of money to invest, but is not so often recommended to small investors. For example, where I live there are many large apartment buildings, office towers, high-end condos, etc. owned by wealthy offshore investors. I wonder what a Hong Kong billionaire with real estate holdings would say if someone suggested he get out of real estate and put everything into mutual funds. Or if someone told a Saudi Prince, "Take out a home equity loan on your palace and put the money into this great limited partnership."
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