[ojAlgo-user] MarkowitzModel - what is optimal?

[Anthony E. <ant...@al...>]

Hi
I’m still no nearer in understanding from any of the documentation or javadocs what is optimal.  When I specify a target return, I get a set of weights and various stats like ShapreRatio, Variance etc.  What is the optimiser maximising/minimising to arrive at this portfolio?  Is it maximising the sharp? or maximising mean return / variance?
We are trying (with no joy at all) to compare an excel based solver with ojalgo, but cant get anywhere near the same results for the same inputs ....
Below is the covar and expected returns
Covar()
7.84% 1.09% 0.26% 0.15% -0.75% 
1.09% 1.06% 0.91% 0.76% -0.07% 
0.26% 0.91% 1.94% 0.98% 0.19% 
0.15% 0.76% 0.98% 0.80% -0.07% 
-0.75% -0.07% 0.19% -0.07% 2.12% 
er[0] --> 0.08468993625647991
er[1] --> 0.05571192270463743
er[2] --> -0.053384899277547415
er[3] --> 0.0363486250229359
er[4] --> -0.10226497575724715
The highest mean return solution we get is 4.4% with limits set at 0 to 0.5 for all 5 assets.   Clearly that is wrong. There is obviously a solution at the mean of 8.4% and 5.5% with 50% in assets 1 and 2 and the other weights at zero.  When I run for a higher target return there is no optimal solution (and weights that outside limits then).  The covar looks ok, the expected returns look ok, all assets are limited weights from 0 to 0.5 and the only variable I can control is the targetReturn(), so I’m at a loss here to know what else I can do.
Any ideas?  Thanks in advance ...
Tony