QuoteOriginally posted by: rcohenQuoteOriginally posted by: DogonMatrixMostly misinformed point of view.I strongly disagree. I have graduate degrees in both engineering (mechanical & chemical) and economics and I have also worked extensively in both areas. So I could confidently claim that I have been on "both sides of the fence." Can you say the same about yourself?QuoteOriginally posted by: DogonMatrixFirst thing, option pricing belongs to the field of financial theory or mathematical finance, not econometrics. You can have to solve some econometrics problems related to option pricing like estimating the parameters of a stochastic vol models, but the two are distinct.Option pricing is NOW a part of mathematical finance, after the development of Black-Scholes. Look at how equities and the risk premium are priced via APT. For this you can refer to many of Fama's well-cited works, among many others. From this, also, it's not difficult to conclude that, in the absence of some form of underlying rule or law (i.e. which may be represented by, let's say, some sort of a pde) econometrics is still the norm in many areas of finance.QuoteOriginally posted by: DogonMatrixSecond thing, I can not think of one methodology developed in engineering that is useful today in finance. The only example that may come to mind is kalman filter or frequency domain type of estimation methodology, but they become useful only once one has translated them in econometrics terms.Engineering grew out of physics and, admittedly, it could be classified as applied physics. For example, while physicists are concerned about statistical thermodynamics, engineers are more involved in its continuum form, which is classical thermodynamics. Do you know what the heat, the viscous diffusion or the soil consolidation equations are? They are all the diffusion equation, which forms the very logic behind Black Scholes. These equations, along with neural networks, Laplace transforms, Fourier transforms, etc., are all part of the everyday language in engineering. If you claim that, except the Kalman Filter and frequency domain estimation, engineering has had little impact on finance, I suggest you go read some books outside your area of expertise.QuoteOriginally posted by: DogonMatrixThird thing, econometrics is not hung up on testing, but rather on the significance of the relationships that are estimated. Without property and results related to statistical distributions I really don't see how one can choose one parameterization of a relationship over another. To me, a tool that allows you to choose one parameter over another (i.e. which one is more significant) is nothing but a testing tool. QuoteOriginally posted by: DogonMatrixFourth thing, linear models are usually favored by practitioners over non linear ones, just because practitioners favor parsimonious models. But academia has moved to and studied more complex non-linear models for more than 20 years ( where they perform well, and can be estimated in a robust fashion). It doesn't matter how complicated things can become in econometrics. You could make the equations nonlinear and increase the number of independent parameters from 6 to 26. At the end what counts is the lack of a governing law. For example, in dynamics you have F=ma; in solid mechanics you have Hook's law, which relates the applied force to deformation; in thermodynamics you have conservation of mass and energy; Brownian motion is governed by the diffusion equation, etc. I just fail to see any underlying rule that is applied in econometrics, except for choosing as many parameters as possible and massaging the equations to the point of getting a good fit.Once again a lot of confusion here. First thing about Laplace, Fourier transform, stochastic processes, etc, these are principles and methods out of theoretical physics not specifically engineering methodologies. So it's little bit of a short cut to claim that there are(theoretical physics and engeneering are distinct). But that's probably a sterile debate...Second thing, on the " absence of governing laws" in econometrics. I almost want to say, " who cares about governing laws!". What matters is trading performance, and that comes along with models that will capture most of the stylized facts out of the market. But what's more, econometrics in many aspects is a methodology to tie a model to reality, it is not in iteself a model. Example I can have a stochastic volatility model which in my mind is distinct from the maximum entropy or kalman filter or generalized method of moments that I will use to estimate the parameters of that model. If you are looking for what will resemble to most the governing laws that you find in Physics , then you probably need to go upstream an look at economics: things like no-arbitrage argument ( which is probably as important to the Black Scholes argument as the GBM process), or Say's law, etc.But I want to emphasize that for me the ultimate criteria is trading performance: if you are " massaging the equations to the point of getting a good fit", first, you are probably a very bad econometrician, second , chances are you will not get any trading performance out of that. Period.You are right I can't claim to know anything about engeneering, but never had any interest because never appeared to me as being the best way to understand the market.
Last edited by DogonMatrix
on June 30th, 2004, 10:00 pm, edited 1 time in total.