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Domain specific (finance) additions to oj! Algorithms
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/*
* Copyright 1997-2022 Optimatika
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
package org.ojalgo.finance.portfolio;
import java.util.Collections;
import java.util.Map;
import org.ojalgo.function.constant.BigMath;
import org.ojalgo.matrix.Primitive64Matrix;
import org.ojalgo.optimisation.ExpressionsBasedModel;
import org.ojalgo.optimisation.Optimisation.Result;
/**
* Represents a portfolio on the efficient fronter. You get different efficient portfolios by altering the
* risk aversion.
*
* @author apete
*/
public final class EfficientFrontier extends OptimisedPortfolio {
private static final Map CONSTRAINTS = Collections.emptyMap();
private final ExpressionsBasedModel myOptimisationModel;
public EfficientFrontier(final FinancePortfolio.Context portfolioContext) {
super(portfolioContext);
myOptimisationModel = this.makeModel(CONSTRAINTS);
}
public EfficientFrontier(final MarketEquilibrium marketEquilibrium, final Primitive64Matrix expectedExcessReturns) {
super(marketEquilibrium, expectedExcessReturns);
myOptimisationModel = this.makeModel(CONSTRAINTS);
}
public EfficientFrontier(final Primitive64Matrix covarianceMatrix, final Primitive64Matrix expectedExcessReturns) {
super(covarianceMatrix, expectedExcessReturns);
myOptimisationModel = this.makeModel(CONSTRAINTS);
}
@Override
protected Primitive64Matrix calculateAssetWeights() {
myOptimisationModel.getExpression(VARIANCE).weight(this.getRiskAversion().doubleValue() / 2.0);
final Result tmpResult = myOptimisationModel.minimise();
return this.handle(tmpResult);
}
@Override
protected void reset() {
super.reset();
final boolean tmpAllowed = this.isShortingAllowed();
myOptimisationModel.getVariables().forEach(v -> v.lower(tmpAllowed ? null : BigMath.ZERO));
}
}
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