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From: Samuel Le <Sam...@sr...> - 2011-10-27 14:05:47
|
Yes, I made this mistake.
Now it's fixed.
Thanks a lot for the quick help Anders, much appreciated.
Samuel
-----Original Message-----
From: Anders Peterson [mailto:an...@op...]
Sent: 27 October 2011 14:56
To: oja...@li...
Subject: Re: [ojAlgo-user] Problem with the constraints on the assets with Markowitz model
Your model is very artificial/symmetric...
The problem is that you've mixed up the lower and upper limits on the variables (asset weight constraints).
/Anders
On 27 okt 2011, at 15:10, Samuel Le wrote:
> Indeed you are right!
> My correlation matrix was wrong.
> Now I just slightly change the way I set the volatilities of the assets:
>
> Double[] vols = new Double[n];
> for(int i = 0; i < n; i++) {
> vols[i] = new Double(i+1)/ new Double(n);
> }
>
> (the volatility of asset i is now (i+1)/n, so there are no zeros anymore).
>
> Now the optimization stated is still FAILED. Also when I re-run the same code I get different weights. I will change my code to always check the optimisation state and ignore the weights provided when it's FAILED.
> Also this time I have no idea what causes the optimization to fail.
>
> Samuel
>
> -----Original Message-----
>> From: Anders Peterson [mailto:an...@op...]
> Sent: 27 October 2011 13:59
> To: oja...@li...
> Subject: Re: [ojAlgo-user] Problem with the constraints on the assets with Markowitz model
>
> It seems I was lucky that one time. Running the code again I get solutions similar to yours.
>
> The problem is your covariance matrix. It has columns and rows with all zeros. That's not allowed!
>
> Also you can/should check the optimization state:
>
> markowitzModel.getOptimisationState();
>
> I get state "FAILED".
>
> /Anders
>
>
> On 27 okt 2011, at 14:24, Anders Peterson wrote:
>
>> Just ran your code. I got this solution:
>>
>> {{0.05},
>> {0.05},
>> {0.05},
>> {0.05},
>> {0.05},
>> {0.05},
>> {0.05},
>> {0.05},
>> {0.3},
>> {0.3}}
>>
>> I am of course using v31, but I don't know what would be the difference. Upgrade to v31 and see if the problem disappears for you as well.
>>
>> /Anders
>>
>>
>> On 27 okt 2011, at 13:21, Samuel Le wrote:
>>
>>> Dear all,
>>>
>>> I am new to ojalgo and am trying to use it for portfolio optimisation.
>>> I think I found a bug: when trying to find some optimal weights with constraints, I can obtain inconsistent weights.
>>> I include below an example. I am using the ojalgo version 30.6.
>>> I would be grateful if someone could tell me what I am doing wrong.
>>>
>>> Many thanks,
>>> Samuel
>>>
>>> Here is my code:
>>>
>>> import java.math.BigDecimal;
>>>
>>> import org.ojalgo.finance.portfolio.MarketEquilibrium;
>>> import org.ojalgo.finance.portfolio.MarkowitzModel;
>>> import org.ojalgo.matrix.BasicMatrix;
>>> import org.ojalgo.matrix.PrimitiveMatrix;
>>> import org.ojalgo.matrix.store.PhysicalStore;
>>> import org.ojalgo.matrix.store.PrimitiveDenseStore;
>>>
>>> public class OjalgoTest {
>>>
>>> public static void main(String[] args) {
>>> int n = 10;
>>> PhysicalStore<Double> resStore = PrimitiveDenseStore.FACTORY.makeZero(n, n);
>>> Double[] vols = new Double[n];
>>> for(int i = 0; i < n; i++) {
>>> vols[i] = new Double(i)/ new Double(n);
>>> }
>>> Double corr = 0.1;
>>> for(int i = 0; i < n; i++) {
>>> for(int j = 0; j < n; j ++) {
>>> if(i == j) {
>>> resStore.set(i, j, vols[i]*vols[i]);
>>> }
>>> else {
>>> resStore.set(i,j,corr*vols[i]*vols[j]);
>>> }
>>> }
>>> }
>>> double[] expectedRets = new double[]{0.2,0.19,0.18,0.17,0.16,0.15,0.14,0.13,0.12,0.11};
>>> PhysicalStore<Double> physicalStorDbl = PrimitiveDenseStore.FACTORY.makeZero(n, 1);
>>> for(int i = 0; i < n ; i++) {
>>> physicalStorDbl.set(i, 0, expectedRets[i]);
>>> }
>>> PrimitiveMatrix expectedReturnsMatrix = new PrimitiveMatrix(physicalStorDbl);
>>> PrimitiveMatrix covMat = new PrimitiveMatrix(resStore);
>>> MarketEquilibrium me = new MarketEquilibrium(covMat);
>>> MarkowitzModel markowitzModel = new MarkowitzModel(me, expectedReturnsMatrix);
>>> for(int i = 0; i < n; i++) {
>>> markowitzModel.setUpperLimit(i, new BigDecimal("0.05"));
>>> markowitzModel.setLowerLimit(i, new BigDecimal("0.3"));
>>> }
>>> markowitzModel.setRiskAversion(new BigDecimal("0.0001"));
>>> BasicMatrix tmpWgts = markowitzModel.getAssetWeights();
>>> System.out.println(tmpWgts);
>>>
>>> }
>>> }
>>>
>>> And this is what I am getting:
>>>
>>> {{0.05},
>>> {0.05},
>>> {0.05},
>>> {0.05},
>>> {0.05},
>>> {0.05},
>>> {0.05},
>>> {0.05},
>>> {76.9098},
>>> {-76.3098}}
>>>
>>>
>>> __________ Information from ESET NOD32 Antivirus, version of virus signature database 6275 (20110707) __________
>>>
>>> The message was checked by ESET NOD32 Antivirus.
>>>
>>> http://www.eset.com
>>> ------------------------------------------------------------------------------
>>> The demand for IT networking professionals continues to grow, and the
>>> demand for specialized networking skills is growing even more rapidly.
>>> Take a complimentary Learning@Cisco Self-Assessment and learn
>>> about Cisco certifications, training, and career opportunities.
>>> http://p.sf.net/sfu/cisco-dev2dev_______________________________________________
>>> ojAlgo-user mailing list
>>> ojA...@li...
>>> https://lists.sourceforge.net/lists/listinfo/ojalgo-user
>>
>
>
> ------------------------------------------------------------------------------
> The demand for IT networking professionals continues to grow, and the
> demand for specialized networking skills is growing even more rapidly.
> Take a complimentary Learning@Cisco Self-Assessment and learn
> about Cisco certifications, training, and career opportunities.
> http://p.sf.net/sfu/cisco-dev2dev
> _______________________________________________
> ojAlgo-user mailing list
> ojA...@li...
> https://lists.sourceforge.net/lists/listinfo/ojalgo-user
>
>
> __________ Information from ESET NOD32 Antivirus, version of virus signature database 6275 (20110707) __________
>
> The message was checked by ESET NOD32 Antivirus.
>
> http://www.eset.com
>
>
>
> __________ Information from ESET NOD32 Antivirus, version of virus signature database 6275 (20110707) __________
>
> The message was checked by ESET NOD32 Antivirus.
>
> http://www.eset.com
>
>
> ------------------------------------------------------------------------------
> The demand for IT networking professionals continues to grow, and the
> demand for specialized networking skills is growing even more rapidly.
> Take a complimentary Learning@Cisco Self-Assessment and learn
> about Cisco certifications, training, and career opportunities.
> http://p.sf.net/sfu/cisco-dev2dev
> _______________________________________________
> ojAlgo-user mailing list
> ojA...@li...
> https://lists.sourceforge.net/lists/listinfo/ojalgo-user
>
>
------------------------------------------------------------------------------
The demand for IT networking professionals continues to grow, and the
demand for specialized networking skills is growing even more rapidly.
Take a complimentary Learning@Cisco Self-Assessment and learn
about Cisco certifications, training, and career opportunities.
http://p.sf.net/sfu/cisco-dev2dev
_______________________________________________
ojAlgo-user mailing list
ojA...@li...
https://lists.sourceforge.net/lists/listinfo/ojalgo-user
__________ Information from ESET NOD32 Antivirus, version of virus signature database 6275 (20110707) __________
The message was checked by ESET NOD32 Antivirus.
http://www.eset.com
__________ Information from ESET NOD32 Antivirus, version of virus signature database 6275 (20110707) __________
The message was checked by ESET NOD32 Antivirus.
http://www.eset.com
|
|
From: Anders P. <an...@op...> - 2011-10-27 13:56:21
|
Your model is very artificial/symmetric…
The problem is that you've mixed up the lower and upper limits on the variables (asset weight constraints).
/Anders
On 27 okt 2011, at 15:10, Samuel Le wrote:
> Indeed you are right!
> My correlation matrix was wrong.
> Now I just slightly change the way I set the volatilities of the assets:
>
> Double[] vols = new Double[n];
> for(int i = 0; i < n; i++) {
> vols[i] = new Double(i+1)/ new Double(n);
> }
>
> (the volatility of asset i is now (i+1)/n, so there are no zeros anymore).
>
> Now the optimization stated is still FAILED. Also when I re-run the same code I get different weights. I will change my code to always check the optimisation state and ignore the weights provided when it's FAILED.
> Also this time I have no idea what causes the optimization to fail.
>
> Samuel
>
> -----Original Message-----
>> From: Anders Peterson [mailto:an...@op...]
> Sent: 27 October 2011 13:59
> To: oja...@li...
> Subject: Re: [ojAlgo-user] Problem with the constraints on the assets with Markowitz model
>
> It seems I was lucky that one time. Running the code again I get solutions similar to yours.
>
> The problem is your covariance matrix. It has columns and rows with all zeros. That's not allowed!
>
> Also you can/should check the optimization state:
>
> markowitzModel.getOptimisationState();
>
> I get state "FAILED".
>
> /Anders
>
>
> On 27 okt 2011, at 14:24, Anders Peterson wrote:
>
>> Just ran your code. I got this solution:
>>
>> {{0.05},
>> {0.05},
>> {0.05},
>> {0.05},
>> {0.05},
>> {0.05},
>> {0.05},
>> {0.05},
>> {0.3},
>> {0.3}}
>>
>> I am of course using v31, but I don't know what would be the difference. Upgrade to v31 and see if the problem disappears for you as well.
>>
>> /Anders
>>
>>
>> On 27 okt 2011, at 13:21, Samuel Le wrote:
>>
>>> Dear all,
>>>
>>> I am new to ojalgo and am trying to use it for portfolio optimisation.
>>> I think I found a bug: when trying to find some optimal weights with constraints, I can obtain inconsistent weights.
>>> I include below an example. I am using the ojalgo version 30.6.
>>> I would be grateful if someone could tell me what I am doing wrong.
>>>
>>> Many thanks,
>>> Samuel
>>>
>>> Here is my code:
>>>
>>> import java.math.BigDecimal;
>>>
>>> import org.ojalgo.finance.portfolio.MarketEquilibrium;
>>> import org.ojalgo.finance.portfolio.MarkowitzModel;
>>> import org.ojalgo.matrix.BasicMatrix;
>>> import org.ojalgo.matrix.PrimitiveMatrix;
>>> import org.ojalgo.matrix.store.PhysicalStore;
>>> import org.ojalgo.matrix.store.PrimitiveDenseStore;
>>>
>>> public class OjalgoTest {
>>>
>>> public static void main(String[] args) {
>>> int n = 10;
>>> PhysicalStore<Double> resStore = PrimitiveDenseStore.FACTORY.makeZero(n, n);
>>> Double[] vols = new Double[n];
>>> for(int i = 0; i < n; i++) {
>>> vols[i] = new Double(i)/ new Double(n);
>>> }
>>> Double corr = 0.1;
>>> for(int i = 0; i < n; i++) {
>>> for(int j = 0; j < n; j ++) {
>>> if(i == j) {
>>> resStore.set(i, j, vols[i]*vols[i]);
>>> }
>>> else {
>>> resStore.set(i,j,corr*vols[i]*vols[j]);
>>> }
>>> }
>>> }
>>> double[] expectedRets = new double[]{0.2,0.19,0.18,0.17,0.16,0.15,0.14,0.13,0.12,0.11};
>>> PhysicalStore<Double> physicalStorDbl = PrimitiveDenseStore.FACTORY.makeZero(n, 1);
>>> for(int i = 0; i < n ; i++) {
>>> physicalStorDbl.set(i, 0, expectedRets[i]);
>>> }
>>> PrimitiveMatrix expectedReturnsMatrix = new PrimitiveMatrix(physicalStorDbl);
>>> PrimitiveMatrix covMat = new PrimitiveMatrix(resStore);
>>> MarketEquilibrium me = new MarketEquilibrium(covMat);
>>> MarkowitzModel markowitzModel = new MarkowitzModel(me, expectedReturnsMatrix);
>>> for(int i = 0; i < n; i++) {
>>> markowitzModel.setUpperLimit(i, new BigDecimal("0.05"));
>>> markowitzModel.setLowerLimit(i, new BigDecimal("0.3"));
>>> }
>>> markowitzModel.setRiskAversion(new BigDecimal("0.0001"));
>>> BasicMatrix tmpWgts = markowitzModel.getAssetWeights();
>>> System.out.println(tmpWgts);
>>>
>>> }
>>> }
>>>
>>> And this is what I am getting:
>>>
>>> {{0.05},
>>> {0.05},
>>> {0.05},
>>> {0.05},
>>> {0.05},
>>> {0.05},
>>> {0.05},
>>> {0.05},
>>> {76.9098},
>>> {-76.3098}}
>>>
>>>
>>> __________ Information from ESET NOD32 Antivirus, version of virus signature database 6275 (20110707) __________
>>>
>>> The message was checked by ESET NOD32 Antivirus.
>>>
>>> http://www.eset.com
>>> ------------------------------------------------------------------------------
>>> The demand for IT networking professionals continues to grow, and the
>>> demand for specialized networking skills is growing even more rapidly.
>>> Take a complimentary Learning@Cisco Self-Assessment and learn
>>> about Cisco certifications, training, and career opportunities.
>>> http://p.sf.net/sfu/cisco-dev2dev_______________________________________________
>>> ojAlgo-user mailing list
>>> ojA...@li...
>>> https://lists.sourceforge.net/lists/listinfo/ojalgo-user
>>
>
>
> ------------------------------------------------------------------------------
> The demand for IT networking professionals continues to grow, and the
> demand for specialized networking skills is growing even more rapidly.
> Take a complimentary Learning@Cisco Self-Assessment and learn
> about Cisco certifications, training, and career opportunities.
> http://p.sf.net/sfu/cisco-dev2dev
> _______________________________________________
> ojAlgo-user mailing list
> ojA...@li...
> https://lists.sourceforge.net/lists/listinfo/ojalgo-user
>
>
> __________ Information from ESET NOD32 Antivirus, version of virus signature database 6275 (20110707) __________
>
> The message was checked by ESET NOD32 Antivirus.
>
> http://www.eset.com
>
>
>
> __________ Information from ESET NOD32 Antivirus, version of virus signature database 6275 (20110707) __________
>
> The message was checked by ESET NOD32 Antivirus.
>
> http://www.eset.com
>
>
> ------------------------------------------------------------------------------
> The demand for IT networking professionals continues to grow, and the
> demand for specialized networking skills is growing even more rapidly.
> Take a complimentary Learning@Cisco Self-Assessment and learn
> about Cisco certifications, training, and career opportunities.
> http://p.sf.net/sfu/cisco-dev2dev
> _______________________________________________
> ojAlgo-user mailing list
> ojA...@li...
> https://lists.sourceforge.net/lists/listinfo/ojalgo-user
>
>
|
|
From: Samuel Le <Sam...@sr...> - 2011-10-27 13:10:26
|
Indeed you are right!
My correlation matrix was wrong.
Now I just slightly change the way I set the volatilities of the assets:
Double[] vols = new Double[n];
for(int i = 0; i < n; i++) {
vols[i] = new Double(i+1)/ new Double(n);
}
(the volatility of asset i is now (i+1)/n, so there are no zeros anymore).
Now the optimization stated is still FAILED. Also when I re-run the same code I get different weights. I will change my code to always check the optimisation state and ignore the weights provided when it's FAILED.
Also this time I have no idea what causes the optimization to fail.
Samuel
-----Original Message-----
From: Anders Peterson [mailto:an...@op...]
Sent: 27 October 2011 13:59
To: oja...@li...
Subject: Re: [ojAlgo-user] Problem with the constraints on the assets with Markowitz model
It seems I was lucky that one time. Running the code again I get solutions similar to yours.
The problem is your covariance matrix. It has columns and rows with all zeros. That's not allowed!
Also you can/should check the optimization state:
markowitzModel.getOptimisationState();
I get state "FAILED".
/Anders
On 27 okt 2011, at 14:24, Anders Peterson wrote:
> Just ran your code. I got this solution:
>
> {{0.05},
> {0.05},
> {0.05},
> {0.05},
> {0.05},
> {0.05},
> {0.05},
> {0.05},
> {0.3},
> {0.3}}
>
> I am of course using v31, but I don't know what would be the difference. Upgrade to v31 and see if the problem disappears for you as well.
>
> /Anders
>
>
> On 27 okt 2011, at 13:21, Samuel Le wrote:
>
>> Dear all,
>>
>> I am new to ojalgo and am trying to use it for portfolio optimisation.
>> I think I found a bug: when trying to find some optimal weights with constraints, I can obtain inconsistent weights.
>> I include below an example. I am using the ojalgo version 30.6.
>> I would be grateful if someone could tell me what I am doing wrong.
>>
>> Many thanks,
>> Samuel
>>
>> Here is my code:
>>
>> import java.math.BigDecimal;
>>
>> import org.ojalgo.finance.portfolio.MarketEquilibrium;
>> import org.ojalgo.finance.portfolio.MarkowitzModel;
>> import org.ojalgo.matrix.BasicMatrix;
>> import org.ojalgo.matrix.PrimitiveMatrix;
>> import org.ojalgo.matrix.store.PhysicalStore;
>> import org.ojalgo.matrix.store.PrimitiveDenseStore;
>>
>> public class OjalgoTest {
>>
>> public static void main(String[] args) {
>> int n = 10;
>> PhysicalStore<Double> resStore = PrimitiveDenseStore.FACTORY.makeZero(n, n);
>> Double[] vols = new Double[n];
>> for(int i = 0; i < n; i++) {
>> vols[i] = new Double(i)/ new Double(n);
>> }
>> Double corr = 0.1;
>> for(int i = 0; i < n; i++) {
>> for(int j = 0; j < n; j ++) {
>> if(i == j) {
>> resStore.set(i, j, vols[i]*vols[i]);
>> }
>> else {
>> resStore.set(i,j,corr*vols[i]*vols[j]);
>> }
>> }
>> }
>> double[] expectedRets = new double[]{0.2,0.19,0.18,0.17,0.16,0.15,0.14,0.13,0.12,0.11};
>> PhysicalStore<Double> physicalStorDbl = PrimitiveDenseStore.FACTORY.makeZero(n, 1);
>> for(int i = 0; i < n ; i++) {
>> physicalStorDbl.set(i, 0, expectedRets[i]);
>> }
>> PrimitiveMatrix expectedReturnsMatrix = new PrimitiveMatrix(physicalStorDbl);
>> PrimitiveMatrix covMat = new PrimitiveMatrix(resStore);
>> MarketEquilibrium me = new MarketEquilibrium(covMat);
>> MarkowitzModel markowitzModel = new MarkowitzModel(me, expectedReturnsMatrix);
>> for(int i = 0; i < n; i++) {
>> markowitzModel.setUpperLimit(i, new BigDecimal("0.05"));
>> markowitzModel.setLowerLimit(i, new BigDecimal("0.3"));
>> }
>> markowitzModel.setRiskAversion(new BigDecimal("0.0001"));
>> BasicMatrix tmpWgts = markowitzModel.getAssetWeights();
>> System.out.println(tmpWgts);
>>
>> }
>> }
>>
>> And this is what I am getting:
>>
>> {{0.05},
>> {0.05},
>> {0.05},
>> {0.05},
>> {0.05},
>> {0.05},
>> {0.05},
>> {0.05},
>> {76.9098},
>> {-76.3098}}
>>
>>
>> __________ Information from ESET NOD32 Antivirus, version of virus signature database 6275 (20110707) __________
>>
>> The message was checked by ESET NOD32 Antivirus.
>>
>> http://www.eset.com
>> ------------------------------------------------------------------------------
>> The demand for IT networking professionals continues to grow, and the
>> demand for specialized networking skills is growing even more rapidly.
>> Take a complimentary Learning@Cisco Self-Assessment and learn
>> about Cisco certifications, training, and career opportunities.
>> http://p.sf.net/sfu/cisco-dev2dev_______________________________________________
>> ojAlgo-user mailing list
>> ojA...@li...
>> https://lists.sourceforge.net/lists/listinfo/ojalgo-user
>
------------------------------------------------------------------------------
The demand for IT networking professionals continues to grow, and the
demand for specialized networking skills is growing even more rapidly.
Take a complimentary Learning@Cisco Self-Assessment and learn
about Cisco certifications, training, and career opportunities.
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_______________________________________________
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__________ Information from ESET NOD32 Antivirus, version of virus signature database 6275 (20110707) __________
The message was checked by ESET NOD32 Antivirus.
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The message was checked by ESET NOD32 Antivirus.
http://www.eset.com
|
|
From: Anders P. <an...@op...> - 2011-10-27 13:00:12
|
It seems I was lucky that one time. Running the code again I get solutions similar to yours.
The problem is your covariance matrix. It has columns and rows with all zeros. That's not allowed!
Also you can/should check the optimization state:
markowitzModel.getOptimisationState();
I get state "FAILED".
/Anders
On 27 okt 2011, at 14:24, Anders Peterson wrote:
> Just ran your code. I got this solution:
>
> {{0.05},
> {0.05},
> {0.05},
> {0.05},
> {0.05},
> {0.05},
> {0.05},
> {0.05},
> {0.3},
> {0.3}}
>
> I am of course using v31, but I don't know what would be the difference. Upgrade to v31 and see if the problem disappears for you as well.
>
> /Anders
>
>
> On 27 okt 2011, at 13:21, Samuel Le wrote:
>
>> Dear all,
>>
>> I am new to ojalgo and am trying to use it for portfolio optimisation.
>> I think I found a bug: when trying to find some optimal weights with constraints, I can obtain inconsistent weights.
>> I include below an example. I am using the ojalgo version 30.6.
>> I would be grateful if someone could tell me what I am doing wrong.
>>
>> Many thanks,
>> Samuel
>>
>> Here is my code:
>>
>> import java.math.BigDecimal;
>>
>> import org.ojalgo.finance.portfolio.MarketEquilibrium;
>> import org.ojalgo.finance.portfolio.MarkowitzModel;
>> import org.ojalgo.matrix.BasicMatrix;
>> import org.ojalgo.matrix.PrimitiveMatrix;
>> import org.ojalgo.matrix.store.PhysicalStore;
>> import org.ojalgo.matrix.store.PrimitiveDenseStore;
>>
>> public class OjalgoTest {
>>
>> public static void main(String[] args) {
>> int n = 10;
>> PhysicalStore<Double> resStore = PrimitiveDenseStore.FACTORY.makeZero(n, n);
>> Double[] vols = new Double[n];
>> for(int i = 0; i < n; i++) {
>> vols[i] = new Double(i)/ new Double(n);
>> }
>> Double corr = 0.1;
>> for(int i = 0; i < n; i++) {
>> for(int j = 0; j < n; j ++) {
>> if(i == j) {
>> resStore.set(i, j, vols[i]*vols[i]);
>> }
>> else {
>> resStore.set(i,j,corr*vols[i]*vols[j]);
>> }
>> }
>> }
>> double[] expectedRets = new double[]{0.2,0.19,0.18,0.17,0.16,0.15,0.14,0.13,0.12,0.11};
>> PhysicalStore<Double> physicalStorDbl = PrimitiveDenseStore.FACTORY.makeZero(n, 1);
>> for(int i = 0; i < n ; i++) {
>> physicalStorDbl.set(i, 0, expectedRets[i]);
>> }
>> PrimitiveMatrix expectedReturnsMatrix = new PrimitiveMatrix(physicalStorDbl);
>> PrimitiveMatrix covMat = new PrimitiveMatrix(resStore);
>> MarketEquilibrium me = new MarketEquilibrium(covMat);
>> MarkowitzModel markowitzModel = new MarkowitzModel(me, expectedReturnsMatrix);
>> for(int i = 0; i < n; i++) {
>> markowitzModel.setUpperLimit(i, new BigDecimal("0.05"));
>> markowitzModel.setLowerLimit(i, new BigDecimal("0.3"));
>> }
>> markowitzModel.setRiskAversion(new BigDecimal("0.0001"));
>> BasicMatrix tmpWgts = markowitzModel.getAssetWeights();
>> System.out.println(tmpWgts);
>>
>> }
>> }
>>
>> And this is what I am getting:
>>
>> {{0.05},
>> {0.05},
>> {0.05},
>> {0.05},
>> {0.05},
>> {0.05},
>> {0.05},
>> {0.05},
>> {76.9098},
>> {-76.3098}}
>>
>>
>> __________ Information from ESET NOD32 Antivirus, version of virus signature database 6275 (20110707) __________
>>
>> The message was checked by ESET NOD32 Antivirus.
>>
>> http://www.eset.com
>> ------------------------------------------------------------------------------
>> The demand for IT networking professionals continues to grow, and the
>> demand for specialized networking skills is growing even more rapidly.
>> Take a complimentary Learning@Cisco Self-Assessment and learn
>> about Cisco certifications, training, and career opportunities.
>> http://p.sf.net/sfu/cisco-dev2dev_______________________________________________
>> ojAlgo-user mailing list
>> ojA...@li...
>> https://lists.sourceforge.net/lists/listinfo/ojalgo-user
>
|
|
From: Samuel Le <Sam...@sr...> - 2011-10-27 12:59:08
|
Hi Anders,
Thank you for your quick reply.
I just upgraded my jars and re ran my code. This time I get a plausible result but for some reason different of yours:
{{0.05},
{0.05},
{0.05},
{0.05},
{0.05},
{0.05},
{0.05},
{0.05},
{0.05},
{0.55}}
I will keep investigating, I must have something else wrong.
Cheers,
Samuel
-----Original Message-----
From: Anders Peterson [mailto:an...@op...]
Sent: 27 October 2011 13:24
To: oja...@li...
Subject: Re: [ojAlgo-user] Problem with the constraints on the assets with Markowitz model
Just ran your code. I got this solution:
{{0.05},
{0.05},
{0.05},
{0.05},
{0.05},
{0.05},
{0.05},
{0.05},
{0.3},
{0.3}}
I am of course using v31, but I don't know what would be the difference. Upgrade to v31 and see if the problem disappears for you as well.
/Anders
On 27 okt 2011, at 13:21, Samuel Le wrote:
> Dear all,
>
> I am new to ojalgo and am trying to use it for portfolio optimisation.
> I think I found a bug: when trying to find some optimal weights with constraints, I can obtain inconsistent weights.
> I include below an example. I am using the ojalgo version 30.6.
> I would be grateful if someone could tell me what I am doing wrong.
>
> Many thanks,
> Samuel
>
> Here is my code:
>
> import java.math.BigDecimal;
>
> import org.ojalgo.finance.portfolio.MarketEquilibrium;
> import org.ojalgo.finance.portfolio.MarkowitzModel;
> import org.ojalgo.matrix.BasicMatrix;
> import org.ojalgo.matrix.PrimitiveMatrix;
> import org.ojalgo.matrix.store.PhysicalStore;
> import org.ojalgo.matrix.store.PrimitiveDenseStore;
>
> public class OjalgoTest {
>
> public static void main(String[] args) {
> int n = 10;
> PhysicalStore<Double> resStore = PrimitiveDenseStore.FACTORY.makeZero(n, n);
> Double[] vols = new Double[n];
> for(int i = 0; i < n; i++) {
> vols[i] = new Double(i)/ new Double(n);
> }
> Double corr = 0.1;
> for(int i = 0; i < n; i++) {
> for(int j = 0; j < n; j ++) {
> if(i == j) {
> resStore.set(i, j, vols[i]*vols[i]);
> }
> else {
> resStore.set(i,j,corr*vols[i]*vols[j]);
> }
> }
> }
> double[] expectedRets = new double[]{0.2,0.19,0.18,0.17,0.16,0.15,0.14,0.13,0.12,0.11};
> PhysicalStore<Double> physicalStorDbl = PrimitiveDenseStore.FACTORY.makeZero(n, 1);
> for(int i = 0; i < n ; i++) {
> physicalStorDbl.set(i, 0, expectedRets[i]);
> }
> PrimitiveMatrix expectedReturnsMatrix = new PrimitiveMatrix(physicalStorDbl);
> PrimitiveMatrix covMat = new PrimitiveMatrix(resStore);
> MarketEquilibrium me = new MarketEquilibrium(covMat);
> MarkowitzModel markowitzModel = new MarkowitzModel(me, expectedReturnsMatrix);
> for(int i = 0; i < n; i++) {
> markowitzModel.setUpperLimit(i, new BigDecimal("0.05"));
> markowitzModel.setLowerLimit(i, new BigDecimal("0.3"));
> }
> markowitzModel.setRiskAversion(new BigDecimal("0.0001"));
> BasicMatrix tmpWgts = markowitzModel.getAssetWeights();
> System.out.println(tmpWgts);
>
> }
> }
>
> And this is what I am getting:
>
> {{0.05},
> {0.05},
> {0.05},
> {0.05},
> {0.05},
> {0.05},
> {0.05},
> {0.05},
> {76.9098},
> {-76.3098}}
>
>
> __________ Information from ESET NOD32 Antivirus, version of virus signature database 6275 (20110707) __________
>
> The message was checked by ESET NOD32 Antivirus.
>
> http://www.eset.com
> ------------------------------------------------------------------------------
> The demand for IT networking professionals continues to grow, and the
> demand for specialized networking skills is growing even more rapidly.
> Take a complimentary Learning@Cisco Self-Assessment and learn
> about Cisco certifications, training, and career opportunities.
> http://p.sf.net/sfu/cisco-dev2dev_______________________________________________
> ojAlgo-user mailing list
> ojA...@li...
> https://lists.sourceforge.net/lists/listinfo/ojalgo-user
------------------------------------------------------------------------------
The demand for IT networking professionals continues to grow, and the
demand for specialized networking skills is growing even more rapidly.
Take a complimentary Learning@Cisco Self-Assessment and learn
about Cisco certifications, training, and career opportunities.
http://p.sf.net/sfu/cisco-dev2dev
_______________________________________________
ojAlgo-user mailing list
ojA...@li...
https://lists.sourceforge.net/lists/listinfo/ojalgo-user
__________ Information from ESET NOD32 Antivirus, version of virus signature database 6275 (20110707) __________
The message was checked by ESET NOD32 Antivirus.
http://www.eset.com
__________ Information from ESET NOD32 Antivirus, version of virus signature database 6275 (20110707) __________
The message was checked by ESET NOD32 Antivirus.
http://www.eset.com
|
|
From: Anders P. <an...@op...> - 2011-10-27 12:24:23
|
Just ran your code. I got this solution:
{{0.05},
{0.05},
{0.05},
{0.05},
{0.05},
{0.05},
{0.05},
{0.05},
{0.3},
{0.3}}
I am of course using v31, but I don't know what would be the difference. Upgrade to v31 and see if the problem disappears for you as well.
/Anders
On 27 okt 2011, at 13:21, Samuel Le wrote:
> Dear all,
>
> I am new to ojalgo and am trying to use it for portfolio optimisation.
> I think I found a bug: when trying to find some optimal weights with constraints, I can obtain inconsistent weights.
> I include below an example. I am using the ojalgo version 30.6.
> I would be grateful if someone could tell me what I am doing wrong.
>
> Many thanks,
> Samuel
>
> Here is my code:
>
> import java.math.BigDecimal;
>
> import org.ojalgo.finance.portfolio.MarketEquilibrium;
> import org.ojalgo.finance.portfolio.MarkowitzModel;
> import org.ojalgo.matrix.BasicMatrix;
> import org.ojalgo.matrix.PrimitiveMatrix;
> import org.ojalgo.matrix.store.PhysicalStore;
> import org.ojalgo.matrix.store.PrimitiveDenseStore;
>
> public class OjalgoTest {
>
> public static void main(String[] args) {
> int n = 10;
> PhysicalStore<Double> resStore = PrimitiveDenseStore.FACTORY.makeZero(n, n);
> Double[] vols = new Double[n];
> for(int i = 0; i < n; i++) {
> vols[i] = new Double(i)/ new Double(n);
> }
> Double corr = 0.1;
> for(int i = 0; i < n; i++) {
> for(int j = 0; j < n; j ++) {
> if(i == j) {
> resStore.set(i, j, vols[i]*vols[i]);
> }
> else {
> resStore.set(i,j,corr*vols[i]*vols[j]);
> }
> }
> }
> double[] expectedRets = new double[]{0.2,0.19,0.18,0.17,0.16,0.15,0.14,0.13,0.12,0.11};
> PhysicalStore<Double> physicalStorDbl = PrimitiveDenseStore.FACTORY.makeZero(n, 1);
> for(int i = 0; i < n ; i++) {
> physicalStorDbl.set(i, 0, expectedRets[i]);
> }
> PrimitiveMatrix expectedReturnsMatrix = new PrimitiveMatrix(physicalStorDbl);
> PrimitiveMatrix covMat = new PrimitiveMatrix(resStore);
> MarketEquilibrium me = new MarketEquilibrium(covMat);
> MarkowitzModel markowitzModel = new MarkowitzModel(me, expectedReturnsMatrix);
> for(int i = 0; i < n; i++) {
> markowitzModel.setUpperLimit(i, new BigDecimal("0.05"));
> markowitzModel.setLowerLimit(i, new BigDecimal("0.3"));
> }
> markowitzModel.setRiskAversion(new BigDecimal("0.0001"));
> BasicMatrix tmpWgts = markowitzModel.getAssetWeights();
> System.out.println(tmpWgts);
>
> }
> }
>
> And this is what I am getting:
>
> {{0.05},
> {0.05},
> {0.05},
> {0.05},
> {0.05},
> {0.05},
> {0.05},
> {0.05},
> {76.9098},
> {-76.3098}}
>
>
> __________ Information from ESET NOD32 Antivirus, version of virus signature database 6275 (20110707) __________
>
> The message was checked by ESET NOD32 Antivirus.
>
> http://www.eset.com
> ------------------------------------------------------------------------------
> The demand for IT networking professionals continues to grow, and the
> demand for specialized networking skills is growing even more rapidly.
> Take a complimentary Learning@Cisco Self-Assessment and learn
> about Cisco certifications, training, and career opportunities.
> http://p.sf.net/sfu/cisco-dev2dev_______________________________________________
> ojAlgo-user mailing list
> ojA...@li...
> https://lists.sourceforge.net/lists/listinfo/ojalgo-user
|
|
From: Samuel Le <Sam...@sr...> - 2011-10-27 11:34:32
|
Dear all,
I am new to ojalgo and am trying to use it for portfolio optimisation.
I think I found a bug: when trying to find some optimal weights with constraints, I can obtain inconsistent weights.
I include below an example. I am using the ojalgo version 30.6.
I would be grateful if someone could tell me what I am doing wrong.
Many thanks,
Samuel
Here is my code:
import java.math.BigDecimal;
import org.ojalgo.finance.portfolio.MarketEquilibrium;
import org.ojalgo.finance.portfolio.MarkowitzModel;
import org.ojalgo.matrix.BasicMatrix;
import org.ojalgo.matrix.PrimitiveMatrix;
import org.ojalgo.matrix.store.PhysicalStore;
import org.ojalgo.matrix.store.PrimitiveDenseStore;
public class OjalgoTest {
public static void main(String[] args) {
int n = 10;
PhysicalStore<Double> resStore = PrimitiveDenseStore.FACTORY.makeZero(n, n);
Double[] vols = new Double[n];
for(int i = 0; i < n; i++) {
vols[i] = new Double(i)/ new Double(n);
}
Double corr = 0.1;
for(int i = 0; i < n; i++) {
for(int j = 0; j < n; j ++) {
if(i == j) {
resStore.set(i, j, vols[i]*vols[i]);
}
else {
resStore.set(i,j,corr*vols[i]*vols[j]);
}
}
}
double[] expectedRets = new double[]{0.2,0.19,0.18,0.17,0.16,0.15,0.14,0.13,0.12,0.11};
PhysicalStore<Double> physicalStorDbl = PrimitiveDenseStore.FACTORY.makeZero(n, 1);
for(int i = 0; i < n ; i++) {
physicalStorDbl.set(i, 0, expectedRets[i]);
}
PrimitiveMatrix expectedReturnsMatrix = new PrimitiveMatrix(physicalStorDbl);
PrimitiveMatrix covMat = new PrimitiveMatrix(resStore);
MarketEquilibrium me = new MarketEquilibrium(covMat);
MarkowitzModel markowitzModel = new MarkowitzModel(me, expectedReturnsMatrix);
for(int i = 0; i < n; i++) {
markowitzModel.setUpperLimit(i, new BigDecimal("0.05"));
markowitzModel.setLowerLimit(i, new BigDecimal("0.3"));
}
markowitzModel.setRiskAversion(new BigDecimal("0.0001"));
BasicMatrix tmpWgts = markowitzModel.getAssetWeights();
System.out.println(tmpWgts);
}
}
And this is what I am getting:
{{0.05},
{0.05},
{0.05},
{0.05},
{0.05},
{0.05},
{0.05},
{0.05},
{76.9098},
{-76.3098}}
|
|
From: Anders P. <an...@op...> - 2011-10-26 17:59:23
|
http://ojalgo.org/change_log.html http://sourceforge.net/projects/ojalgo/files/ojAlgo/ /Anders |
|
From: Anders P. <an...@op...> - 2011-10-13 08:20:12
|
http://en.wikipedia.org/wiki/Quadratic_programming#Solution_methods It's a plain Lagrange solver. If there are inequality constraints it uses an active set strategy, and if there are any integer constraints on the variables everything is wrapped in a branch-and-bound algorithm. There are plenty of books and on-line resources covering this. Just google for it. /Anders On 13 okt 2011, at 06:00, Tin Nguyen Chi wrote: > Hi, > > I'd like to ask about the method ojalgo use to solve the quadratic programming. It would be great if a reference (paper or book) so I can look for more details > > Thanks a lot > ------------------------------------------------------------------------------ > All the data continuously generated in your IT infrastructure contains a > definitive record of customers, application performance, security > threats, fraudulent activity and more. Splunk takes this data and makes > sense of it. Business sense. IT sense. Common sense. > http://p.sf.net/sfu/splunk-d2d-oct_______________________________________________ > ojAlgo-user mailing list > ojA...@li... > https://lists.sourceforge.net/lists/listinfo/ojalgo-user |
|
From: Tin N. C. <tin...@gm...> - 2011-10-13 04:00:44
|
Hi, I'd like to ask about the method ojalgo use to solve the quadratic programming. It would be great if a reference (paper or book) so I can look for more details Thanks a lot |
|
From: Anders P. <an...@op...> - 2011-10-10 21:43:34
|
I uploaded a new snapshot https://sourceforge.net/projects/ojalgo/files/ojAlgo/snapshot/ Could you test if that works better for you? /Anders On 10 okt 2011, at 14:45, Anders Peterson wrote: > Haven't looked at this in great detail, but if you change: > > objective[1].setInteger(true); > to > objective[1].setInteger(false); > > and > > model.minimise(); > to > model.setMinimisation(true); > final OptimisationSolver tmpSolver = model.getDefaultSolver(); > final Result tmpResult = tmpSolver.solve(); > > Then you'll see that ojAlgo reports the relaxed problem to be unbounded. If that's true it's a (big) problem for the integer solver. The relaxed problems need to be able to be solved by the linear or quadratic solvers. > > I'm not confident that ojAlgo reports INFEASIBLE and/or UNBOUNDED problems right all the time, but you should definitely not get a NullPointerException! > > X=0, Y=0 & Z=0 is a valid solution to your problem, right? In that case there is a bug with the LinearSolver. > > /Anders > > > On 10 okt 2011, at 12:18, Julien.Cojan wrote: > >> Hello, >> >> I am using OjAlgo to solve mixed linear programming problems. >> However I often get a NullPointerException when running on my examples. >> I tried version 30.0 and 30.6, I get the same error. >> >> This is the smallest example I could find where I get this exception : >> >> >> import static org.ojalgo.constant.BigMath.ONE; >> import static org.ojalgo.constant.BigMath.ZERO; >> >> import java.math.BigDecimal; >> >> import org.ojalgo.optimisation.Expression; >> import org.ojalgo.optimisation.Variable; >> import org.ojalgo.optimisation.linear.LinearExpressionsModel; >> >> >> public class TestOjAlgo { >> >> public static void testBug1(){ >> Variable[] objective = new Variable[] { >> new Variable("X").weight(ONE), >> new Variable("Y").weight(ZERO), >> new Variable("Z").weight(ZERO)}; >> >> objective[1].setInteger(true); >> >> LinearExpressionsModel model = new LinearExpressionsModel(objective); >> >> // c1: X =0 >> Expression c1 = model.addEmptyLinearExpression("c1"); >> c1.level(ZERO); >> c1.setLinearFactor(0, ONE); >> >> // c2: -X +5Y =0 >> Expression c2 = model.addEmptyLinearExpression("c2"); >> c2.level(ZERO); >> >> c2.setLinearFactor(0, new BigDecimal(-1)); >> c2.setLinearFactor(1, ONE); >> >> // c3: X -Z =0 >> Expression c3 = model.addEmptyLinearExpression("c3"); >> c3.level(ZERO); >> // bugs with this constraint >> c3.setLinearFactor(0, ONE); >> c3.setLinearFactor(2, new BigDecimal(-1)); >> // but not with this one ??? >> // c3.setLinearFactor(0, new BigDecimal(-1)); >> // c3.setLinearFactor(2, ONE); >> >> model.minimise(); >> } >> >> public static void main(String[] args){ >> testBug1(); >> } >> >> } >> >> >> >> >> >> I get the following message >> Exception in thread "main" java.lang.NullPointerException >> at org.ojalgo.optimisation.OptimisationSolver$Result.<init>(OptimisationSolver.java:99) >> at org.ojalgo.optimisation.integer.IntegerSolver.solve(IntegerSolver.java:318) >> at org.ojalgo.optimisation.ExpressionsBasedModel.solve(ExpressionsBasedModel.java:741) >> at org.ojalgo.optimisation.ExpressionsBasedModel.minimise(ExpressionsBasedModel.java:458) >> at TestOjAlgo.testBug1(TestOjAlgo.java:57) >> at TestOjAlgo.main(TestOjAlgo.java:61) >> >> >> Is it a bug or am I not using ojAlgo properly ? >> >> >> -- >> The Open University is incorporated by Royal Charter (RC 000391), an exempt charity in England & Wales and a charity registered in Scotland (SC 038302). >> >> >> ------------------------------------------------------------------------------ >> All the data continuously generated in your IT infrastructure contains a >> definitive record of customers, application performance, security >> threats, fraudulent activity and more. Splunk takes this data and makes >> sense of it. Business sense. IT sense. Common sense. >> http://p.sf.net/sfu/splunk-d2dcopy1 >> _______________________________________________ >> ojAlgo-user mailing list >> ojA...@li... >> https://lists.sourceforge.net/lists/listinfo/ojalgo-user >> >> > > > ------------------------------------------------------------------------------ > All the data continuously generated in your IT infrastructure contains a > definitive record of customers, application performance, security > threats, fraudulent activity and more. Splunk takes this data and makes > sense of it. Business sense. IT sense. Common sense. > http://p.sf.net/sfu/splunk-d2dcopy1 > _______________________________________________ > ojAlgo-user mailing list > ojA...@li... > https://lists.sourceforge.net/lists/listinfo/ojalgo-user > > |
|
From: Anders P. <an...@op...> - 2011-10-10 13:01:16
|
Haven't looked at this in great detail, but if you change:
objective[1].setInteger(true);
to
objective[1].setInteger(false);
and
model.minimise();
to
model.setMinimisation(true);
final OptimisationSolver tmpSolver = model.getDefaultSolver();
final Result tmpResult = tmpSolver.solve();
Then you'll see that ojAlgo reports the relaxed problem to be unbounded. If that's true it's a (big) problem for the integer solver. The relaxed problems need to be able to be solved by the linear or quadratic solvers.
I'm not confident that ojAlgo reports INFEASIBLE and/or UNBOUNDED problems right all the time, but you should definitely not get a NullPointerException!
X=0, Y=0 & Z=0 is a valid solution to your problem, right? In that case there is a bug with the LinearSolver.
/Anders
On 10 okt 2011, at 12:18, Julien.Cojan wrote:
> Hello,
>
> I am using OjAlgo to solve mixed linear programming problems.
> However I often get a NullPointerException when running on my examples.
> I tried version 30.0 and 30.6, I get the same error.
>
> This is the smallest example I could find where I get this exception :
>
>
> import static org.ojalgo.constant.BigMath.ONE;
> import static org.ojalgo.constant.BigMath.ZERO;
>
> import java.math.BigDecimal;
>
> import org.ojalgo.optimisation.Expression;
> import org.ojalgo.optimisation.Variable;
> import org.ojalgo.optimisation.linear.LinearExpressionsModel;
>
>
> public class TestOjAlgo {
>
> public static void testBug1(){
> Variable[] objective = new Variable[] {
> new Variable("X").weight(ONE),
> new Variable("Y").weight(ZERO),
> new Variable("Z").weight(ZERO)};
>
> objective[1].setInteger(true);
>
> LinearExpressionsModel model = new LinearExpressionsModel(objective);
>
> // c1: X =0
> Expression c1 = model.addEmptyLinearExpression("c1");
> c1.level(ZERO);
> c1.setLinearFactor(0, ONE);
>
> // c2: -X +5Y =0
> Expression c2 = model.addEmptyLinearExpression("c2");
> c2.level(ZERO);
>
> c2.setLinearFactor(0, new BigDecimal(-1));
> c2.setLinearFactor(1, ONE);
>
> // c3: X -Z =0
> Expression c3 = model.addEmptyLinearExpression("c3");
> c3.level(ZERO);
> // bugs with this constraint
> c3.setLinearFactor(0, ONE);
> c3.setLinearFactor(2, new BigDecimal(-1));
> // but not with this one ???
> // c3.setLinearFactor(0, new BigDecimal(-1));
> // c3.setLinearFactor(2, ONE);
>
> model.minimise();
> }
>
> public static void main(String[] args){
> testBug1();
> }
>
> }
>
>
>
>
>
> I get the following message
> Exception in thread "main" java.lang.NullPointerException
> at org.ojalgo.optimisation.OptimisationSolver$Result.<init>(OptimisationSolver.java:99)
> at org.ojalgo.optimisation.integer.IntegerSolver.solve(IntegerSolver.java:318)
> at org.ojalgo.optimisation.ExpressionsBasedModel.solve(ExpressionsBasedModel.java:741)
> at org.ojalgo.optimisation.ExpressionsBasedModel.minimise(ExpressionsBasedModel.java:458)
> at TestOjAlgo.testBug1(TestOjAlgo.java:57)
> at TestOjAlgo.main(TestOjAlgo.java:61)
>
>
> Is it a bug or am I not using ojAlgo properly ?
>
>
> --
> The Open University is incorporated by Royal Charter (RC 000391), an exempt charity in England & Wales and a charity registered in Scotland (SC 038302).
>
>
> ------------------------------------------------------------------------------
> All the data continuously generated in your IT infrastructure contains a
> definitive record of customers, application performance, security
> threats, fraudulent activity and more. Splunk takes this data and makes
> sense of it. Business sense. IT sense. Common sense.
> http://p.sf.net/sfu/splunk-d2dcopy1
> _______________________________________________
> ojAlgo-user mailing list
> ojA...@li...
> https://lists.sourceforge.net/lists/listinfo/ojalgo-user
>
>
|
|
From: Julien.Cojan <Jul...@op...> - 2011-10-10 10:18:39
|
Hello,
I am using OjAlgo to solve mixed linear programming problems.
However I often get a NullPointerException when running on my examples.
I tried version 30.0 and 30.6, I get the same error.
This is the smallest example I could find where I get this exception :
import static org.ojalgo.constant.BigMath.ONE;
import static org.ojalgo.constant.BigMath.ZERO;
import java.math.BigDecimal;
import org.ojalgo.optimisation.Expression;
import org.ojalgo.optimisation.Variable;
import org.ojalgo.optimisation.linear.LinearExpressionsModel;
public class TestOjAlgo {
public static void testBug1(){
Variable[] objective = new Variable[] {
new Variable("X").weight(ONE),
new Variable("Y").weight(ZERO),
new Variable("Z").weight(ZERO)};
objective[1].setInteger(true);
LinearExpressionsModel model = new LinearExpressionsModel(objective);
// c1: X =0
Expression c1 = model.addEmptyLinearExpression("c1");
c1.level(ZERO);
c1.setLinearFactor(0, ONE);
// c2: -X +5Y =0
Expression c2 = model.addEmptyLinearExpression("c2");
c2.level(ZERO);
c2.setLinearFactor(0, new BigDecimal(-1));
c2.setLinearFactor(1, ONE);
// c3: X -Z =0
Expression c3 = model.addEmptyLinearExpression("c3");
c3.level(ZERO);
// bugs with this constraint
c3.setLinearFactor(0, ONE);
c3.setLinearFactor(2, new BigDecimal(-1));
// but not with this one ???
// c3.setLinearFactor(0, new BigDecimal(-1));
// c3.setLinearFactor(2, ONE);
model.minimise();
}
public static void main(String[] args){
testBug1();
}
}
I get the following message
Exception in thread "main" java.lang.NullPointerException
at org.ojalgo.optimisation.OptimisationSolver$Result.<init>(OptimisationSolver.java:99)
at org.ojalgo.optimisation.integer.IntegerSolver.solve(IntegerSolver.java:318)
at org.ojalgo.optimisation.ExpressionsBasedModel.solve(ExpressionsBasedModel.java:741)
at org.ojalgo.optimisation.ExpressionsBasedModel.minimise(ExpressionsBasedModel.java:458)
at TestOjAlgo.testBug1(TestOjAlgo.java:57)
at TestOjAlgo.main(TestOjAlgo.java:61)
Is it a bug or am I not using ojAlgo properly ?
--
The Open University is incorporated by Royal Charter (RC 000391), an exempt charity in England & Wales and a charity registered in Scotland (SC 038302).
|
|
From: Anders P. <an...@op...> - 2011-07-04 21:01:54
|
I ran these tests again with v30 and updated the results page. http://ojalgo.org/performance_ejml.html /Anders On 4 apr 2011, at 22.58, Anders Peterson wrote: > I ran the "Java Matrix Benchmark" > > http://ojalgo.org/performance_ejml.html > > ojAlgo performs ok considering I didn't write the benchmark ;-) > > /Anders |
|
From: Anders P. <an...@op...> - 2011-06-30 15:06:15
|
Just use the MarkowitzModel class http://ojalgo.org/generated/org/ojalgo/finance/portfolio/MarkowitzModel.html and/or browse through the list archive. I believe this question (similar questions at least) has been asked before. /Anders On 30 jun 2011, at 02.31, Charley Swift wrote: > I'm working on a portfolio optimization problem, using QP to find the optimal weight (allocation) of each asset in the portfolio. My objective is to minimize variance: find the optimal portfolio weights for the Minimum Variance Portfolio (MVP). Here's an example in R of what I'm trying to do in Java: > > http://quantivity.wordpress.com/2011/04/17/minimum-variance-portfolios/ > > My inputs are an n x n covariance matrix (where n is the number of assets in the portfolio), which I've calculated from the known asset returns. > > The two constraints are: sum of the portfolio weights must add up to 1.0 (allocate all available capital), and all weights must be >= 0 (no shorting allowed). > > Could someone please provide (or point me to) some Java code how to do this in ojAlgo (using its quadratic solver)? > > Thank you, > Charley > > > ------------------------------------------------------------------------------ > All of the data generated in your IT infrastructure is seriously valuable. > Why? It contains a definitive record of application performance, security > threats, fraudulent activity, and more. Splunk takes this data and makes > sense of it. IT sense. And common sense. > http://p.sf.net/sfu/splunk-d2d-c2 > _______________________________________________ > ojAlgo-user mailing list > ojA...@li... > https://lists.sourceforge.net/lists/listinfo/ojalgo-user > > |
|
From: Charley S. <cha...@ya...> - 2011-06-30 00:31:29
|
I'm working on a portfolio optimization problem, using QP to find the optimal weight (allocation) of each asset in the portfolio. My objective is to minimize variance: find the optimal portfolio weights for the Minimum Variance Portfolio (MVP). Here's an example in R of what I'm trying to do in Java: http://quantivity.wordpress.com/2011/04/17/minimum-variance-portfolios/ My inputs are an n x n covariance matrix (where n is the number of assets in the portfolio), which I've calculated from the known asset returns. The two constraints are: sum of the portfolio weights must add up to 1.0 (allocate all available capital), and all weights must be >= 0 (no shorting allowed). Could someone please provide (or point me to) some Java code how to do this in ojAlgo (using its quadratic solver)? Thank you, Charley |
|
From: Anders P. <an...@op...> - 2011-06-26 21:35:13
|
I have now released v30.1 that should fix that problem. /Anders
On 26 jun 2011, at 10.23, Anders Peterson wrote:
> That looks like a bug. I'll have to think about which is the correct fix.
>
> Until I release a fixed version, creating an empty linear expression should work:
>
> Expression tmpLinExpr = addEmptyLinearExpression("LinearExpression");
> tmpLinExpr.setLinearFactor(0, ...);
> tmpLinExpr.setLinearFactor(1, ...);
> tmpLinExpr.setLinearFactor(2, ...);
> tmpLinExpr.setLinearFactor(3, ...);
>
>
> /Anders
>
>
>
> On 24 jun 2011, at 13.56, Luke Lindsay wrote:
>
>> What is the correct way to create a row vector for
>> ExpressionsBasedModel.addLinearExpression? The code below throws an
>> excecption:
>>
>> LinearExpressionsModel model = new LinearExpressionsModel(vars);
>> Access1D a1d = Array1D.makePrimitive(2);
>> model.addLinearExpression("LinearExpression", a1d);
>>
>> Must be a row vector!
>> java.lang.IllegalArgumentException: Must be a row vector!
>> at org.ojalgo.function.multiary.LinearFunction.<init>(LinearFunction.java:91)
>> at org.ojalgo.function.multiary.LinearFunction.makeBig(LinearFunction.java:39)
>> at org.ojalgo.optimisation.Expression.makeLinear(Expression.java:70)
>> at org.ojalgo.optimisation.ExpressionsBasedModel.addLinearExpression(ExpressionsBasedModel.java:160)
>>
>> ------------------------------------------------------------------------------
>> All the data continuously generated in your IT infrastructure contains a
>> definitive record of customers, application performance, security
>> threats, fraudulent activity and more. Splunk takes this data and makes
>> sense of it. Business sense. IT sense. Common sense..
>> http://p.sf.net/sfu/splunk-d2d-c1
>> _______________________________________________
>> ojAlgo-user mailing list
>> ojA...@li...
>> https://lists.sourceforge.net/lists/listinfo/ojalgo-user
>>
>>
>
>
> ------------------------------------------------------------------------------
> All of the data generated in your IT infrastructure is seriously valuable.
> Why? It contains a definitive record of application performance, security
> threats, fraudulent activity, and more. Splunk takes this data and makes
> sense of it. IT sense. And common sense.
> http://p.sf.net/sfu/splunk-d2d-c2
> _______________________________________________
> ojAlgo-user mailing list
> ojA...@li...
> https://lists.sourceforge.net/lists/listinfo/ojalgo-user
>
>
|
|
From: Anders P. <an...@op...> - 2011-06-26 08:23:41
|
That looks like a bug. I'll have to think about which is the correct fix.
Until I release a fixed version, creating an empty linear expression should work:
Expression tmpLinExpr = addEmptyLinearExpression("LinearExpression");
tmpLinExpr.setLinearFactor(0, ...);
tmpLinExpr.setLinearFactor(1, ...);
tmpLinExpr.setLinearFactor(2, ...);
tmpLinExpr.setLinearFactor(3, ...);
/Anders
On 24 jun 2011, at 13.56, Luke Lindsay wrote:
> What is the correct way to create a row vector for
> ExpressionsBasedModel.addLinearExpression? The code below throws an
> excecption:
>
> LinearExpressionsModel model = new LinearExpressionsModel(vars);
> Access1D a1d = Array1D.makePrimitive(2);
> model.addLinearExpression("LinearExpression", a1d);
>
> Must be a row vector!
> java.lang.IllegalArgumentException: Must be a row vector!
> at org.ojalgo.function.multiary.LinearFunction.<init>(LinearFunction.java:91)
> at org.ojalgo.function.multiary.LinearFunction.makeBig(LinearFunction.java:39)
> at org.ojalgo.optimisation.Expression.makeLinear(Expression.java:70)
> at org.ojalgo.optimisation.ExpressionsBasedModel.addLinearExpression(ExpressionsBasedModel.java:160)
>
> ------------------------------------------------------------------------------
> All the data continuously generated in your IT infrastructure contains a
> definitive record of customers, application performance, security
> threats, fraudulent activity and more. Splunk takes this data and makes
> sense of it. Business sense. IT sense. Common sense..
> http://p.sf.net/sfu/splunk-d2d-c1
> _______________________________________________
> ojAlgo-user mailing list
> ojA...@li...
> https://lists.sourceforge.net/lists/listinfo/ojalgo-user
>
>
|
|
From: Luke L. <luk...@gm...> - 2011-06-24 11:56:54
|
What is the correct way to create a row vector for
ExpressionsBasedModel.addLinearExpression? The code below throws an
excecption:
LinearExpressionsModel model = new LinearExpressionsModel(vars);
Access1D a1d = Array1D.makePrimitive(2);
model.addLinearExpression("LinearExpression", a1d);
Must be a row vector!
java.lang.IllegalArgumentException: Must be a row vector!
at org.ojalgo.function.multiary.LinearFunction.<init>(LinearFunction.java:91)
at org.ojalgo.function.multiary.LinearFunction.makeBig(LinearFunction.java:39)
at org.ojalgo.optimisation.Expression.makeLinear(Expression.java:70)
at org.ojalgo.optimisation.ExpressionsBasedModel.addLinearExpression(ExpressionsBasedModel.java:160)
|
|
From: Simon G. <si...@ya...> - 2011-06-15 20:59:25
|
Thank you for your help, it works now. SG ________________________________ From: Anders Peterson <an...@op...> To: oja...@li... Sent: Wed, June 15, 2011 4:10:03 AM Subject: Re: [ojAlgo-user] QuadraticSolver issue Here's my code. testP20110614 is your *problem* http://ojalgo.cvs.sourceforge.net/viewvc/ojalgo/TestProj/src/org/ojalgo/finance/portfolio/ReportedProblems.java?view=markup /Anders On 14 jun 2011, at 23.33, Simon Greaves wrote: > Yes, I have to finish the lower bounds, that part I'm not worried about. > But I don't understand, I must be doing something different from how you did >it, because I get: > > X class org.ojalgo.matrix.PrimitiveMatrix > {{1.000000000000013}, > {3.2333333333333143}, > {-3.233333333333325}} > > This is how I get X: > > Result rslt = qdrtc_slvr.solve(); > BasicMatrix rslt_mtrx = rslt.getSolution(); > PhysicalStore<Double> result = rslt_mtrx.toPrimitiveStore(); > System.out.println("\nX " + rslt_mtrx.toString()); > > I this correct? > Thanks again for all your help by the way! > > SG > > From: Anders Peterson <an...@op...> > To: oja...@li... > Sent: Tue, June 14, 2011 4:34:59 PM > Subject: Re: [ojAlgo-user] QuadraticSolver issue > > Here's what I get: > > [AE] = class org.ojalgo.matrix.PrimitiveMatrix > {{1.0, 1.0, 1.0}} > > [BE] = class org.ojalgo.matrix.PrimitiveMatrix > {{1.0}} > > [Q] = class org.ojalgo.matrix.PrimitiveMatrix > {{4.0, 1.0, 2.0}, > {1.0, 9.0, 1.0}, > {2.0, 1.0, 16.0}} > > [C] = class org.ojalgo.matrix.PrimitiveMatrix > {{10.0}, > {15.0}, > {18.0}} > > [AI] = class org.ojalgo.matrix.PrimitiveMatrix > {{1.0, 0.0, 0.0}, > {0.0, 1.0, 0.0}, > {0.0, 0.0, 1.0}} > > [BI] = class org.ojalgo.matrix.PrimitiveMatrix > {{1.0}, > {1.0}, > {1.0}} > > [X] = class org.ojalgo.matrix.PrimitiveMatrix > {{-0.17441860465116266}, > {0.6279069767441859}, > {0.5465116279069767}} > > [LE] = class org.ojalgo.matrix.PrimitiveMatrix > {{8.976744186046512}} > > [LI] = class org.ojalgo.matrix.PrimitiveMatrix > {{0.0}, > {0.0}, > {0.0}} > > [SE] = class org.ojalgo.matrix.PrimitiveMatrix > {{0.0}} > > [SI] = class org.ojalgo.matrix.PrimitiveMatrix > {{1.1744186046511627}, > {0.37209302325581406}, > {0.4534883720930233}} > > I do not get any weights larger than 1.0, but I do get one weight smaller than >0.0. There's no constraint to restrict that! Add constraints for that and you >should get the solutions you expect. > > Here's how I would find the efficient frontier: > > final BasicMatrix tmpCovars = ...; > final BasicMatrix tmpReturs = ...; > > final MarketEquilibrium tmpME = new MarketEquilibrium(tmpCovars); > > final MarkowitzModel tmpMarkowitz = new MarkowitzModel(tmpME, >tmpReturs); > > for (int i = 1; i < 10; i++) { // Some different risk aversion factors > |
|
From: Anders P. <an...@op...> - 2011-06-15 08:40:11
|
Here's my code. testP20110614 is your *problem* http://ojalgo.cvs.sourceforge.net/viewvc/ojalgo/TestProj/src/org/ojalgo/finance/portfolio/ReportedProblems.java?view=markup /Anders On 14 jun 2011, at 23.33, Simon Greaves wrote: > Yes, I have to finish the lower bounds, that part I'm not worried about. > But I don't understand, I must be doing something different from how you did it, because I get: > > X class org.ojalgo.matrix.PrimitiveMatrix > {{1.000000000000013}, > {3.2333333333333143}, > {-3.233333333333325}} > > This is how I get X: > > Result rslt = qdrtc_slvr.solve(); > BasicMatrix rslt_mtrx = rslt.getSolution(); > PhysicalStore<Double> result = rslt_mtrx.toPrimitiveStore(); > System.out.println("\nX " + rslt_mtrx.toString()); > > I this correct? > Thanks again for all your help by the way! > > SG > > From: Anders Peterson <an...@op...> > To: oja...@li... > Sent: Tue, June 14, 2011 4:34:59 PM > Subject: Re: [ojAlgo-user] QuadraticSolver issue > > Here's what I get: > > [AE] = class org.ojalgo.matrix.PrimitiveMatrix > {{1.0, 1.0, 1.0}} > > [BE] = class org.ojalgo.matrix.PrimitiveMatrix > {{1.0}} > > [Q] = class org.ojalgo.matrix.PrimitiveMatrix > {{4.0, 1.0, 2.0}, > {1.0, 9.0, 1.0}, > {2.0, 1.0, 16.0}} > > [C] = class org.ojalgo.matrix.PrimitiveMatrix > {{10.0}, > {15.0}, > {18.0}} > > [AI] = class org.ojalgo.matrix.PrimitiveMatrix > {{1.0, 0.0, 0.0}, > {0.0, 1.0, 0.0}, > {0.0, 0.0, 1.0}} > > [BI] = class org.ojalgo.matrix.PrimitiveMatrix > {{1.0}, > {1.0}, > {1.0}} > > [X] = class org.ojalgo.matrix.PrimitiveMatrix > {{-0.17441860465116266}, > {0.6279069767441859}, > {0.5465116279069767}} > > [LE] = class org.ojalgo.matrix.PrimitiveMatrix > {{8.976744186046512}} > > [LI] = class org.ojalgo.matrix.PrimitiveMatrix > {{0.0}, > {0.0}, > {0.0}} > > [SE] = class org.ojalgo.matrix.PrimitiveMatrix > {{0.0}} > > [SI] = class org.ojalgo.matrix.PrimitiveMatrix > {{1.1744186046511627}, > {0.37209302325581406}, > {0.4534883720930233}} > > I do not get any weights larger than 1.0, but I do get one weight smaller than 0.0. There's no constraint to restrict that! Add constraints for that and you should get the solutions you expect. > > Here's how I would find the efficient frontier: > > final BasicMatrix tmpCovars = ...; > final BasicMatrix tmpReturs = ...; > > final MarketEquilibrium tmpME = new MarketEquilibrium(tmpCovars); > > final MarkowitzModel tmpMarkowitz = new MarkowitzModel(tmpME, tmpReturs); > > for (int i = 1; i < 10; i++) { // Some different risk aversion factors > > tmpMarkowitz.setRiskAversion(new BigDecimal(i)); > > final List<BigDecimal> tmpWeights = tmpMarkowitz.getWeights(); > } > > ------------------------------------------------------------------------------ > EditLive Enterprise is the world's most technically advanced content > authoring tool. Experience the power of Track Changes, Inline Image > Editing and ensure content is compliant with Accessibility Checking. > http://p.sf.net/sfu/ephox-dev2dev_______________________________________________ > ojAlgo-user mailing list > ojA...@li... > https://lists.sourceforge.net/lists/listinfo/ojalgo-user |
|
From: Anders P. <an...@op...> - 2011-06-15 08:35:21
|
2011-06-15: Released v30 http://ojalgo.org/change_log.html http://sourceforge.net/projects/ojalgo/files/ojAlgo/v30/ |
|
From: Simon G. <si...@ya...> - 2011-06-14 21:33:20
|
Yes, I have to finish the lower bounds, that part I'm not worried about.
But I don't understand, I must be doing something different from how you did it,
because I get:
X class org.ojalgo.matrix.PrimitiveMatrix
{{1.000000000000013},
{3.2333333333333143},
{-3.233333333333325}}
This is how I get X:
Result rslt = qdrtc_slvr.solve();
BasicMatrix rslt_mtrx = rslt.getSolution();
PhysicalStore<Double> result = rslt_mtrx.toPrimitiveStore();
System.out.println("\nX " + rslt_mtrx.toString());
I this correct?
Thanks again for all your help by the way!
SG
________________________________
From: Anders Peterson <an...@op...>
To: oja...@li...
Sent: Tue, June 14, 2011 4:34:59 PM
Subject: Re: [ojAlgo-user] QuadraticSolver issue
Here's what I get:
[AE] = class org.ojalgo.matrix.PrimitiveMatrix
{{1.0, 1.0, 1.0}}
[BE] = class org.ojalgo.matrix.PrimitiveMatrix
{{1.0}}
[Q] = class org.ojalgo.matrix.PrimitiveMatrix
{{4.0, 1.0, 2.0},
{1.0, 9.0, 1.0},
{2.0, 1.0, 16.0}}
[C] = class org.ojalgo.matrix.PrimitiveMatrix
{{10.0},
{15.0},
{18.0}}
[AI] = class org.ojalgo.matrix.PrimitiveMatrix
{{1.0, 0.0, 0.0},
{0.0, 1.0, 0.0},
{0.0, 0.0, 1.0}}
[BI] = class org.ojalgo.matrix.PrimitiveMatrix
{{1.0},
{1.0},
{1.0}}
[X] = class org.ojalgo.matrix.PrimitiveMatrix
{{-0.17441860465116266},
{0.6279069767441859},
{0.5465116279069767}}
[LE] = class org.ojalgo.matrix.PrimitiveMatrix
{{8.976744186046512}}
[LI] = class org.ojalgo.matrix.PrimitiveMatrix
{{0.0},
{0.0},
{0.0}}
[SE] = class org.ojalgo.matrix.PrimitiveMatrix
{{0.0}}
[SI] = class org.ojalgo.matrix.PrimitiveMatrix
{{1.1744186046511627},
{0.37209302325581406},
{0.4534883720930233}}
I do not get any weights larger than 1.0, but I do get one weight smaller than
0.0. There's no constraint to restrict that! Add constraints for that and you
should get the solutions you expect.
Here's how I would find the efficient frontier:
final BasicMatrix tmpCovars = ...;
final BasicMatrix tmpReturs = ...;
final MarketEquilibrium tmpME = new MarketEquilibrium(tmpCovars);
final MarkowitzModel tmpMarkowitz = new MarkowitzModel(tmpME,
tmpReturs);
for (int i = 1; i < 10; i++) { // Some different risk aversion factors
tmpMarkowitz.setRiskAversion(new BigDecimal(i));
final List<BigDecimal> tmpWeights = tmpMarkowitz.getWeights();
} |
|
From: Anders P. <an...@op...> - 2011-06-14 21:05:09
|
Here's what I get:
[AE] = class org.ojalgo.matrix.PrimitiveMatrix
{{1.0, 1.0, 1.0}}
[BE] = class org.ojalgo.matrix.PrimitiveMatrix
{{1.0}}
[Q] = class org.ojalgo.matrix.PrimitiveMatrix
{{4.0, 1.0, 2.0},
{1.0, 9.0, 1.0},
{2.0, 1.0, 16.0}}
[C] = class org.ojalgo.matrix.PrimitiveMatrix
{{10.0},
{15.0},
{18.0}}
[AI] = class org.ojalgo.matrix.PrimitiveMatrix
{{1.0, 0.0, 0.0},
{0.0, 1.0, 0.0},
{0.0, 0.0, 1.0}}
[BI] = class org.ojalgo.matrix.PrimitiveMatrix
{{1.0},
{1.0},
{1.0}}
[X] = class org.ojalgo.matrix.PrimitiveMatrix
{{-0.17441860465116266},
{0.6279069767441859},
{0.5465116279069767}}
[LE] = class org.ojalgo.matrix.PrimitiveMatrix
{{8.976744186046512}}
[LI] = class org.ojalgo.matrix.PrimitiveMatrix
{{0.0},
{0.0},
{0.0}}
[SE] = class org.ojalgo.matrix.PrimitiveMatrix
{{0.0}}
[SI] = class org.ojalgo.matrix.PrimitiveMatrix
{{1.1744186046511627},
{0.37209302325581406},
{0.4534883720930233}}
I do not get any weights larger than 1.0, but I do get one weight smaller than 0.0. There's no constraint to restrict that! Add constraints for that and you should get the solutions you expect.
Here's how I would find the efficient frontier:
final BasicMatrix tmpCovars = ...;
final BasicMatrix tmpReturs = ...;
final MarketEquilibrium tmpME = new MarketEquilibrium(tmpCovars);
final MarkowitzModel tmpMarkowitz = new MarkowitzModel(tmpME, tmpReturs);
for (int i = 1; i < 10; i++) { // Some different risk aversion factors
tmpMarkowitz.setRiskAversion(new BigDecimal(i));
final List<BigDecimal> tmpWeights = tmpMarkowitz.getWeights();
}
On 14 jun 2011, at 17.59, Simon Greaves wrote:
> Well I made this test case, but it requires a utilities library to load the files that contain the matrices.
> You can see what I'm doing but it can't run.
> I'm trying to to Efficient Frontier analysis. I tried using the ojAlgo.finance.porfolio.MarkowitzModel class, but I had a lot of trouble understanding the doc file. So I decided to to it myself using the QuadraticSolver, which I had less trouble with...
>
> I'm solving (as in the doc file):
> min 1/2 [X]T[Q][X] - [C]T[X]
> when [AE][X] == [BE]
> and [AI][X] <= [BI]
>
> where (in the test case)
> Q (Covariance Matrix):
> 0.04 0.01 0.02
> 0.01 0.09 0.01
> 0.02 0.01 0.16
>
> C (Expected Return Vector):
> 0.10
> 0.15
> 0.18
>
> The sum of X should be 1 since it's portfolio analysis, and I should use 100% of the investment on all activities.
> And every Xi should be between 0 and 1.
> So I made AE a vector of 1's and BE=1, so that takes care of sum(X)=1. And
> AI is an identity matrix, and BI a 1 vector. So all Xi's should be <=1.
>
> But as a result I get, for example: [-2.4, 2.4, 1]
>
> So, I guess I'm not doing things right, and the inequality constraints aren't being respected...
> From: Anders Peterson <an...@op...>
> To: oja...@li...
> Sent: Mon, June 13, 2011 4:55:38 PM
> Subject: Re: [ojAlgo-user] QuadraticSolver issue
>
> What org.ojalgo.optimisation.State do you get?
>
> Why don't you construct a junit test case to show me exactly what you're doing.
>
> /Anders
> <TempClass.java><COVAR_MATRIX.txt><RETURN.txt><VARS.txt>------------------------------------------------------------------------------
> EditLive Enterprise is the world's most technically advanced content
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From: Simon G. <si...@ya...> - 2011-06-14 16:02:09
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package temporaryapp;
/*
* To change this template, choose Tools | Templates
* and open the template in the editor.
*/
/**
*
* @author simon
*/
import ms2Utils.FileUtils;
import org.ojalgo.optimisation.quadratic.*;
import org.ojalgo.matrix.BasicMatrix;
import org.ojalgo.optimisation.OptimisationSolver.Result;
import org.ojalgo.optimisation.*;
import org.ojalgo.matrix.store.*;
public class TempClass {
private double var, ret, fxd_ret;
private double[] C;
private double[][] Q;
private String[] var_names;
public static void TempClass() {
}
public static void main(String[] args) {
double[][] cov_mat = strng2Dbl(FileUtils.fileToArray("/home/simon/Documents/Frontera Eficiente de Markowitz/COVAR_MATRIX.txt", "\t"));
double[] r = strng2Dbl(FileUtils.fileToList("/home/simon/Documents/Frontera Eficiente de Markowitz/RETURN.txt"));
String[] vars = FileUtils.fileToList("/home/simon/Documents/Frontera Eficiente de Markowitz/VARS.txt");
TempClass FE = new TempClass();
FE.setQ(cov_mat);
FE.setC(r);
FE.setVar_names(vars);
// FE.minimizeVarMinusReturn();
FE.minimizeVarGivenReturn(0.3);
}
private void minimizeVarMinusReturn() {
/* CREACION DE VARIABLES COMPATIBLES CON LA LIBRERIA OjAlgo
*/
double[][] c_temp = new double[Q[0].length][1];
for (int i = 0; i < c_temp.length; i++) {
c_temp[i][0] = C[i];
}
double[] ae = new double[Q.length];
double[][] ai = new double[Q[0].length][Q.length];
double[][] be = new double[1][1];
be[0][0] = 1;
double[][] bi = new double[Q[0].length][1];
for (int i = 0; i < Q.length; i++) {
ae[i] = 1;
bi[i][0] = 1;
}
for (int i = 0; i < ai.length; i++) {
for (int j = 0; j < ai[0].length; j++) {
if (i == j) {
ai[i][j] = 1;
} else {
ai[i][j] = 0;
}
}
}
final PhysicalStore<Double> Q_aux = PrimitiveDenseStore.FACTORY.copy(Q);
final PhysicalStore<Double> C_aux = PrimitiveDenseStore.FACTORY.copy(c_temp);
final PhysicalStore<Double> aux_AE = PrimitiveDenseStore.FACTORY.makeColumn(ae);
final PhysicalStore<Double> aux_BE = PrimitiveDenseStore.FACTORY.copy(be);
final PhysicalStore<Double> aux_AI = PrimitiveDenseStore.FACTORY.copy(ai);
final PhysicalStore<Double> aux_BI = PrimitiveDenseStore.FACTORY.copy(bi);
MatrixStore Q_ms = Q_aux.copy();
MatrixStore C_ms = C_aux.copy();
MatrixStore AE_ms = aux_AE.copy().transpose();
MatrixStore BE_ms = aux_BE.copy();
MatrixStore AI_ms = aux_AI.copy().transpose();
MatrixStore BI_ms = aux_BI.copy();
Variable[] VARIABLE = new Variable[var_names.length];
for (int i = 0; i < var_names.length; i++) {
VARIABLE[i] = new Variable(var_names[i]);
System.out.println(VARIABLE[i].toString());
}
/* FIN CREACION DE VARIABLES COMPATIBLES CON LA LIBRERIA OjAlgo
*/
/* INICIALIZACION DE OBJETO QUADRATIC SOLVER
*/
QuadraticExpressionsModel qem = new QuadraticExpressionsModel(VARIABLE);
QuadraticSolver.Builder qdrtc_slvr_bldr = new QuadraticSolver.Builder(qem).objective(Q_ms, C_ms).equalities(AE_ms, BE_ms).inequalities(AI_ms, BI_ms);
QuadraticSolver qdrtc_slvr = qdrtc_slvr_bldr.build();
/* FIN INICIALIZACION DE OBJETO QUADRATIC SOLVER
*/
/* RESULTADOS
*/
Result rslt = qdrtc_slvr.solve();
BasicMatrix rslt_mtrx = rslt.getSolution();
PhysicalStore<Double> result = rslt_mtrx.toPrimitiveStore();
var = result.transpose().multiplyRight(Q_ms).multiplyRight(result).get(0, 0);
ret = C_aux.transpose().multiplyRight(result).get(0, 0);
System.out.println("\nRESULT");
for (int i = 0; i < rslt_mtrx.getRowDim(); i++) {
for (int j = 0; j < rslt_mtrx.getColDim(); j++) {
System.out.println(rslt_mtrx.doubleValue(i, j) + " ");
}
System.out.println();
}
System.out.println("\nVARIANCE " + var);
System.out.println("\nRETORNO " + ret);
/* FIN RESULTADOS
*/
}
private void minimizeVarGivenReturn(double given_return) {
setFxd_ret(given_return);
/* CREACION DE VARIABLES COMPATIBLES CON LA LIBRERIA OjAlgo
* Aqui haremos que los retornos entren en las restricciones. Esto significa
* que en vez de introducir los retornos en la matriz C, esta sera zeros
* y los retornos entraran en AE. De esta manera se obtienen retornos
* iguales a fxd_ret.
*/
double[][] c_temp = new double[Q[0].length][1];
for (int i = 0; i < c_temp.length; i++) {
c_temp[i][0] = 0;
}
double[][] ae = new double[2][Q.length];
double[][] ai = new double[Q[0].length][Q.length];
double[][] be = new double[2][1];
be[0][0] = 1;
be[1][0] = fxd_ret;
double[][] bi = new double[Q[0].length][1];
for (int i = 0; i < Q.length; i++) {
ae[0][i] = 1;
ae[1][i] = C[i];
bi[i][0] = 1;
}
for (int i = 0; i < ai.length; i++) {
for (int j = 0; j < ai[0].length; j++) {
if (i == j) {
ai[i][j] = 1;
} else {
ai[i][j] = 0;
}
}
}
final PhysicalStore<Double> Q_aux = PrimitiveDenseStore.FACTORY.copy(Q);
final PhysicalStore<Double> C_aux = PrimitiveDenseStore.FACTORY.copy(c_temp);
final PhysicalStore<Double> aux_AE = PrimitiveDenseStore.FACTORY.copy(ae);
final PhysicalStore<Double> aux_BE = PrimitiveDenseStore.FACTORY.copy(be);
final PhysicalStore<Double> aux_AI = PrimitiveDenseStore.FACTORY.copy(ai);
final PhysicalStore<Double> aux_BI = PrimitiveDenseStore.FACTORY.copy(bi);
MatrixStore Q_ms = Q_aux.copy();
MatrixStore C_ms = C_aux.copy();
MatrixStore AE_ms = aux_AE.copy();
MatrixStore BE_ms = aux_BE.copy();
MatrixStore AI_ms = aux_AI.copy().transpose();
MatrixStore BI_ms = aux_BI.copy();
Variable[] VARIABLE = new Variable[var_names.length];
for (int i = 0; i < var_names.length; i++) {
VARIABLE[i] = new Variable(var_names[i]);
System.out.println(VARIABLE[i].toString());
}
/* FIN CREACION DE VARIABLES COMPATIBLES CON LA LIBRERIA OjAlgo
*/
/* INICIALIZACION DE OBJETO QUADRATIC SOLVER
*/
QuadraticExpressionsModel qem = new QuadraticExpressionsModel(VARIABLE);
QuadraticSolver.Builder qdrtc_slvr_bldr = new QuadraticSolver.Builder(qem).objective(Q_ms, C_ms).equalities(AE_ms, BE_ms).inequalities(AI_ms, BI_ms);
QuadraticSolver qdrtc_slvr = qdrtc_slvr_bldr.build();
/* FIN INICIALIZACION DE OBJETO QUADRATIC SOLVER
*/
/* RESULTADOS
*/
Result rslt = qdrtc_slvr.solve();
BasicMatrix rslt_mtrx = rslt.getSolution();
PhysicalStore<Double> result = rslt_mtrx.toPrimitiveStore();
var = result.transpose().multiplyRight(Q_ms).multiplyRight(result).get(0, 0);
System.out.println("\nRESULT");
for (int i = 0; i < rslt_mtrx.getRowDim(); i++) {
for (int j = 0; j < rslt_mtrx.getColDim(); j++) {
System.out.println(rslt_mtrx.doubleValue(i, j) + " ");
}
System.out.println();
}
System.out.println("\nVARIANCE " + var);
/* FIN RESULTADOS
*/
}
private static double[][] strng2Dbl(String[][] strng_mat) {
double[][] mat = new double[strng_mat.length][strng_mat[0].length];
for (int i = 0; i < strng_mat.length; i++) {
for (int j = 0; j < strng_mat[0].length; j++) {
mat[i][j] = Double.parseDouble(strng_mat[i][j]);
}
}
return mat;
}
private static double[] strng2Dbl(String[] strng_vec) {
double[] vec = new double[strng_vec.length];
for (int i = 0; i < strng_vec.length; i++) {
vec[i] = Double.parseDouble(strng_vec[i]);
}
return vec;
}
/**
* @param R the R to set
*/
public void setC(double[] C) {
this.C = C;
}
/**
* @param W the W to set
*/
public void setQ(double[][] Q) {
this.Q = Q;
}
/**
* @return the var
*/
public double getVar() {
return var;
}
/**
* @return the ret
*/
public double getRet() {
return ret;
}
/**
* @param var_names the var_names to set
*/
public void setVar_names(String[] var_names) {
this.var_names = var_names;
}
/**
* @param fxd_ret the fxd_ret to set
*/
public void setFxd_ret(double fxd_ret) {
this.fxd_ret = fxd_ret;
}
}
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