[ojAlgo-user] 答复: ojAlgo-user Digest, Vol 79, Issue 3

[<lvz...@gt...>]

Hi,
What is the definition of risk aversion factor? 

Lvzifeng
 



oja...@li... 
2017/05/10 20:05
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ojAlgo-user Digest, Vol 79, Issue 3






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Today's Topics:

   1. ??:  Report A Bug Of ojalgo finace library (yifa wang)
   2. Re: ??:  Report A Bug Of ojalgo finace library (Anders Peterson)
   3. Re: Report A Bug Of ojalgo finace library (Anders Peterson)


----------------------------------------------------------------------

Message: 1
Date: Tue, 9 May 2017 15:15:36 +0000
From: yifa wang <fag...@ho...>
Subject: [ojAlgo-user] ??:  Report A Bug Of ojalgo finace library
To: "oja...@li..."
                 <oja...@li...>
Message-ID:
 
<SG2...@SG...>
 
Content-Type: text/plain; charset="gb2312"

hi,


I try to use ojalgo to do a portfolio optimization. The target is find an 
efficient frontier for 15 securities or more. I generate random returns 
for simulation. However, when I run the program, I get the state as 
"UNEXPLORED". Usually, we get OPTIMAL.  What does this mean? Is it 
possible to get the optimal weight for more than 50 securities?


Thanks.

Jerry





________________________________
???: lvz...@gt... <lvz...@gt...>
????: 2017?5?8? ?? 8:20:21
???: oja...@li...
??: [ojAlgo-user] Report A Bug Of ojalgo finace library


Hi,
      I have a problem when calculate best invest group by using 
markowitzModel in ojalgo with code below(for test);




          for(int j = 0; j < 100; j ++)
         { Builder<PrimitiveMatrix> tmpBuilder = 
PrimitiveMatrix.FACTORY.getBuilder(2, 2);
    tmpBuilder.add(0, 0, 0.040000);
    tmpBuilder.add(0, 1, 0.1000);
    tmpBuilder.add(1, 0, 0.1000);
    tmpBuilder.add(1, 1, 0.250000);
        BasicMatrix covariances = tmpBuilder.build();
        tmpBuilder = PrimitiveMatrix.FACTORY.getBuilder(2);
        tmpBuilder.add(0, 0.20000);
        tmpBuilder.add(1, 0.40000);
        BasicMatrix expectedExcessReturns = tmpBuilder.build();

       MarketEquilibrium equilibrium = new MarketEquilibrium(covariances);
        MarkowitzModel markowitzModel = new MarkowitzModel(equilibrium, 
expectedExcessReturns);
        markowitzModel.setShortingAllowed(false);
       // markowitzModel.optimiser().validate(true);
        markowitzModel.setTargetReturn(new BigDecimal(0.2 + (0.002 * j)));
        for (int i = 0; i < 2; i++) {
            markowitzModel.setLowerLimit(i, new BigDecimal(0.00000));
            markowitzModel.setUpperLimit(i, new BigDecimal(1.00000));
        }
        System.out.println(0.2 + (0.002 * j) + "," + 
markowitzModel.getReturnVariance() + " , "  + 
markowitzModel.getMeanReturn()  + "," + markowitzModel.getWeights());


}


      when TargetReturn equal to 0.206,Variance equal to 0.04 , weights 
equal to [1.0, 0.0]
      when TargetReturn  equal to  0.208, Variance equal to 0.25,weights 
equal to [0.0, 1.0]
      Below  Relationship of TargetReturn And Target Variance?Y-Axis 
TargetReturn,X-AXis standard deviation?



???

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Message: 2
Date: Tue, 9 May 2017 22:34:46 +0200
From: Anders Peterson <an...@op...>
Subject: Re: [ojAlgo-user] ??:  Report A Bug Of ojalgo finace library
To: oja...@li...
Message-ID: <9FD...@op...>
Content-Type: text/plain; charset=utf-8

UNEXPLORED would mean the optimisation has not been executed (since you 
last modified the model). How did you get that?

/Anders




> On 9 May 2017, at 17:15, yifa wang <fag...@ho...> wrote:
> 
> hi,
> 
> I try to use ojalgo to do a portfolio optimization. The target is find 
an efficient frontier for 15 securities or more. I generate random returns 
for simulation. However, when I run the program, I get the state as 
"UNEXPLORED". Usually, we get OPTIMAL.  What does this mean? Is it 
possible to get the optimal weight for more than 50 securities?
> 
> Thanks. 
> Jerry 
> 
> 
> 
> 
> ???: lvz...@gt... <lvz...@gt...>
> ????: 2017?5?8? ?? 8:20:21
> ???: oja...@li...
> ??: [ojAlgo-user] Report A Bug Of ojalgo finace library
> 
> 
> Hi,
>       I have a problem when calculate best invest group by using 
markowitzModel in ojalgo with code below(for test);
> 
> 
> 
> 
>           for(int j = 0; j < 100; j ++)
>          { Builder<PrimitiveMatrix> tmpBuilder = 
PrimitiveMatrix.FACTORY.getBuilder(2, 2);
>     tmpBuilder.add(0, 0, 0.040000);
>     tmpBuilder.add(0, 1, 0.1000);
>     tmpBuilder.add(1, 0, 0.1000);
>     tmpBuilder.add(1, 1, 0.250000);
>         BasicMatrix covariances = tmpBuilder.build();
>         tmpBuilder = PrimitiveMatrix.FACTORY.getBuilder(2);
>         tmpBuilder.add(0, 0.20000);
>         tmpBuilder.add(1, 0.40000);
>         BasicMatrix expectedExcessReturns = tmpBuilder.build(); 
> 
>        MarketEquilibrium equilibrium = new 
MarketEquilibrium(covariances);
>         MarkowitzModel markowitzModel = new MarkowitzModel(equilibrium, 
expectedExcessReturns);
>         markowitzModel.setShortingAllowed(false);
>        // markowitzModel.optimiser().validate(true);
>         markowitzModel.setTargetReturn(new BigDecimal(0.2 + (0.002 * 
j)));
>         for (int i = 0; i < 2; i++) {
>             markowitzModel.setLowerLimit(i, new BigDecimal(0.00000));
>             markowitzModel.setUpperLimit(i, new BigDecimal(1.00000));
>         }
>         System.out.println(0.2 + (0.002 * j) + "," + 
markowitzModel.getReturnVariance() + " , "  + 
markowitzModel.getMeanReturn()  + "," + markowitzModel.getWeights());
> 
> 
> }
> 
> 
>       when TargetReturn equal to 0.206,Variance equal to 0.04 , weights 
equal to [1.0, 0.0]
>       when TargetReturn  equal to  0.208, Variance equal to 0.25,weights 
equal to [0.0, 1.0]
>       Below  Relationship of TargetReturn And Target Variance?Y-Axis 
TargetReturn,X-AXis standard deviation? 
> 
> 
> 
> ???
> 
> 
------------------------------------------------------------------------------
> Check out the vibrant tech community on one of the world's most
> engaging tech sites, Slashdot.org! 
http://sdm.link/slashdot_______________________________________________
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------------------------------

Message: 3
Date: Tue, 9 May 2017 23:32:47 +0200
From: Anders Peterson <an...@op...>
Subject: Re: [ojAlgo-user] Report A Bug Of ojalgo finace library
To: oja...@li...
Message-ID: <A20...@op...>
Content-Type: text/plain; charset=utf-8

Haven?t fully understood yet why that small/simple model is so 
problematic. The covariance matrix is not positive definite, Strictly 
speaking it needs to be, but most of the time semidefinite is ok. 

Setting a target return or variance is not the best way to use ojAlgo?s 
MarkowitzModel class. Work directly with the risk aversion factor instead. 


If what you want to do is to calculate the efficient frontier then it?s 
better to use the EfficientFrontier class rather than the MarkowitzModel 
class.

/Anders


> On 8 May 2017, at 14:20, lvz...@gt... wrote:
> 
> 
> Hi,
>       I have a problem when calculate best invest group by using 
markowitzModel in ojalgo with code below(for test);
> 
> 
> 
> 
>           for(int j = 0; j < 100; j ++)
>          { Builder<PrimitiveMatrix> tmpBuilder = 
PrimitiveMatrix.FACTORY.getBuilder(2, 2);
>     tmpBuilder.add(0, 0, 0.040000);
>     tmpBuilder.add(0, 1, 0.1000);
>     tmpBuilder.add(1, 0, 0.1000);
>     tmpBuilder.add(1, 1, 0.250000);
>         BasicMatrix covariances = tmpBuilder.build();
>         tmpBuilder = PrimitiveMatrix.FACTORY.getBuilder(2);
>         tmpBuilder.add(0, 0.20000);
>         tmpBuilder.add(1, 0.40000);
>         BasicMatrix expectedExcessReturns = tmpBuilder.build(); 
> 
>        MarketEquilibrium equilibrium = new 
MarketEquilibrium(covariances);
>         MarkowitzModel markowitzModel = new MarkowitzModel(equilibrium, 
expectedExcessReturns);
>         markowitzModel.setShortingAllowed(false);
>        // markowitzModel.optimiser().validate(true);
>         markowitzModel.setTargetReturn(new BigDecimal(0.2 + (0.002 * 
j)));
>         for (int i = 0; i < 2; i++) {
>             markowitzModel.setLowerLimit(i, new BigDecimal(0.00000));
>             markowitzModel.setUpperLimit(i, new BigDecimal(1.00000));
>         }
>         System.out.println(0.2 + (0.002 * j) + "," + 
markowitzModel.getReturnVariance() + " , "  + 
markowitzModel.getMeanReturn()  + "," + markowitzModel.getWeights());
> 
> 
> }
> 
> 
>       when TargetReturn equal to 0.206,Variance equal to 0.04 , weights 
equal to [1.0, 0.0]
>       when TargetReturn  equal to  0.208, Variance equal to 0.25,weights 
equal to [0.0, 1.0]
>       Below  Relationship of TargetReturn And Target Variance?Y-Axis 
TargetReturn,X-AXis standard deviation? 
> 
> 
> 
> ???
> 
> 
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> Check out the vibrant tech community on one of the world's most
> engaging tech sites, Slashdot.org! 
http://sdm.link/slashdot_______________________________________________
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> https://lists.sourceforge.net/lists/listinfo/ojalgo-user




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