Quadratic optimization Problem

[phil_prismtc]

In essence the problem is this:

I need a solver to change the weightings x to find the maximum value of the formula above (ie find the Tangent Portfolio TP). The numerator is the vector of expected returns mu(x), which is a linear function of x, rf is a constant value. The denominator is the standard deviation of the portfolio sigma(x) which is a quadratic function of x.

Is there any way to use any solver in LV to find x that maximises [ mu(x) - rf ] / sigma(x)

[phil_prismtc]

I have "solved" the problem in that I eventually found a convex form of the Sharpe ratio that can be solved via QP techniques. After a couple of days I got it working in LV. I say "solved" because there are some limitations with this method that have an unforeseen flow on effect that has forced me to use my original approach to the problem which is roughly as efficient, but thorough and more practical.

Oh well, At least I am now an "expert" on modern portfolio theory 😉

Thanks for the interest/help folks.