Re: [ojAlgo-user] MarkowitzModel - what is optimal?

[Anders P. <an...@op...>]

Have you read the javadoc for the MarkowitzModel class and its methods? I think it does specify how it optimizes.

The results you describe seems "wrong" but without a test case where I can see exactly what you do I cannot comment.

If you don't like the MarkowitzModel class you can build your own optimization models directly using ExpressionsBasedModel

http://ojalgo.org/generated/org/ojalgo/optimisation/ExpressionsBasedModel.html

/Anders


On 24 okt 2013, at 11:09, Anthony Edwards <ant...@al...> wrote:

> 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
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