I put my version of the MATLAB demonstration of the Michaud re-sampled allocation from the lab this evening in the docs folder for your reference.

I have posted a brief tutorial on the TGARCH model for timeseries conditional heteroskedasticity.

I have updated the case from yesterday to demonstrate the failure of the Cholesky method for simulating large vectors, and the alternate historical simulation method. I have also posted a note defining and justifying the method.

I have posted two versions of the solutions I worked, one in Mathematica 6.0 and the other in MATLAB R2007b. If you need me to re-work the Mathematica solution for a previous version, please let me know. In both cases, I used trial and error to identify that the optimal portfolio was 55% risky asset and 45% riskless asset.

Here is the diagram that I shared in class from Casella & Berger that shows the relationships between the major classical distributions.

The files we use in the lab such as the M-file for `binomial()` will be kept in the directory http://www.math.umn.edu/~dodso013/fm503/docs/.

You can load a sample of random variables into MATLAB using the command

sscanf(urlread('http://www.math.umn.edu/~dodso013/fm503/case1.dat'),'%f')

These are drawn uniformly between zero and some unknown upper bound. Please provide an interval estimate for the upper bound.

The objective is to have the narrowest interval that includes the true value. This is a contest; the winning team members will take home a Sven & Ole's bumper sticker!

Feel free to leave comments for the instructor and other visitors.