[EMAIL PROTECTED] (Kristian Moe) wrote: > [...] I'm working on a finance thesis, focusing on > options and value at risk.
Given this, the error of the interpolation scheme probably won't have any noticeable effect. The numbers you quote seem to be some empirical results -- if so, the error introduced by using the wrong model (e.g., assuming independence and/or Gaussian distribution of some important quantity) are going to greatly outweigh the error of the interpolation scheme. If there is some theory about the distribution of the results (e.g., results should be Poisson distributed or something) then, by all means, determine the parameters of a theoretical distribution and integrate w.r.t. that distribution. This is equivalent to implementing an interpolation scheme based on the theory. Failing that, linear interpolation will likely work as well as anything. It seems likely that you've presented only a small part of a large, broad problem. My advice is that you should work on covering all parts of the problem in a reasonable way, rather than spending a lot of time on an unimportant detail at the expense of other parts. For what it's worth, Robert Dodier -- Far better an approximate answer to the right question, which is often vague, than an exact answer to the wrong question, which can always be made precise. -- John W. Tukey . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
