twofish-quant
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If you want to explain my philosophy of truth. Truth=survival. If you jump off a 100 story building, you aren't going to leave too many descendants. If you jump off a five story building, you break some bones and learn never to do that again. Over time (i.e. hundreds of millions of years), organisms become programmed to look for truth.
This matters with modeling, because in the last year the world just took an economic jump off a five story building, and so people have concluded that it's not a good idea to do that again. A lot of the problems involved taking models that were perfectly good for one domain and applying it where there was no data to support them. People took models of collaterialized default obligations that work beautifully with junk bonds and applied them to mortgage securities, which was a really really bad idea. (The basic problem is that when say an electronics factory goes bust, then the odds are that the concrete factory next to it still works. If one subprime mortgage goes bad, then chances are that all of the subprime mortgages in the world are also going bad at the same time.)
A lot of what I do involves thinking about probability and correlations, and there are some arguments that you use that get you punched in the gut by reality and some arguments that don't, and the probability arguments that the OP are using are a bit too much like the probability arguments that people used to justify a lot of the CDO non-sense. Certainty will get you killed in the markets. If you can model interest rates with 70% certainty, you are going to be a billionaire. The thing is that most people can't and the one's that seem to usually just got lucky.
It's actually curious but the mathematics of finance resemble a lot the mathematics of general relativity. There is a lot of modelling surfaces and curvative.
This matters with modeling, because in the last year the world just took an economic jump off a five story building, and so people have concluded that it's not a good idea to do that again. A lot of the problems involved taking models that were perfectly good for one domain and applying it where there was no data to support them. People took models of collaterialized default obligations that work beautifully with junk bonds and applied them to mortgage securities, which was a really really bad idea. (The basic problem is that when say an electronics factory goes bust, then the odds are that the concrete factory next to it still works. If one subprime mortgage goes bad, then chances are that all of the subprime mortgages in the world are also going bad at the same time.)
A lot of what I do involves thinking about probability and correlations, and there are some arguments that you use that get you punched in the gut by reality and some arguments that don't, and the probability arguments that the OP are using are a bit too much like the probability arguments that people used to justify a lot of the CDO non-sense. Certainty will get you killed in the markets. If you can model interest rates with 70% certainty, you are going to be a billionaire. The thing is that most people can't and the one's that seem to usually just got lucky.
It's actually curious but the mathematics of finance resemble a lot the mathematics of general relativity. There is a lot of modelling surfaces and curvative.

) Attempt to save my intellectual a*s.