I was wondering if anyone has any experience with conic optimization (ie Mosek)
to solve large scale portfolio optimization problems. It all seem so complicated.
It should be possible to call such an optimization engine from Maple right?!

If you work with Maple on a daily basis sometimes you come across
things that seem impossible to do. Yesterday I tried to have two colors
in a histogram ie -3..-1 = red and -1..3 =blue but I could not figure
out how to do it...hummm.....any suggestions?

restart:
with(Statistics):
with(plots):

n:=5000:
A:=Sample(RandomVariable(Normal(0,1)),n):

Histogram(A,bincount=100, color=blue);

Can anyone explain the below printscreen in simple terms ?

It is taken from http://www.lgt.com/export/sites/inta_lgtcom/fr/institutionelle_kunden/kompetenzen/traditionelle_anlagen/lgt_and_science/aktuelle-projekte/quantitative-finance/Projekt_EfeAksueyek_en.pdf

on pages 24. Why do we have such a ratio (second formula) ?

I just wonder what you guys thing about the direct search optimization package
written by Dr. Sergey Moiseev which is available at the Application center

www.maplesoft.com/applications/view.aspx

Can it be used as a substitute for the global optimization toolbox ? 
 

One thing I am struggling to understand is the following:

If you have three randomvariables (similarities to the hat puzzle) then you
can get a positive expected value if you for example bet that r1 will be negative
when r2>0 and r3>0 and that r1 will be positive when r2<0 and r3<0. It follows
because the probability of getting [+,+,+] + [-.-.-] = 0.5^3+0.5^3=0.25. Which
means that the probability of success for our introduced betting strategy is 0.75.