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/*
Copyright (C) 2001, 2002 Sadruddin Rejeb
This file is part of QuantLib, a free-software/open-source library
for financial quantitative analysts and developers - http://quantlib.org/
QuantLib is free software: you can redistribute it and/or modify it under the
terms of the QuantLib license. You should have received a copy of the
license along with this program; if not, please email ferdinando@ametrano.net
The license is also available online at http://quantlib.org/html/license.html
This program is distributed in the hope that it will be useful, but WITHOUT
ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
FOR A PARTICULAR PURPOSE. See the license for more details.
*/
/*! \file model.cpp
\brief Abstract interest rate model class
\fullpath
ql/InterestRateModelling/%model.cpp
*/
// $Id: model.cpp,v 1.18 2002/03/06 07:16:06 sadrejeb Exp $
#include "ql/InterestRateModelling/calibrationhelper.hpp"
#include "ql/Optimization/optimizer.hpp"
namespace QuantLib {
namespace InterestRateModelling {
using namespace Optimization;
class Model::CalibrationFunction : public CostFunction {
public:
CalibrationFunction(
Model* model,
CalibrationSet& instruments)
: model_(model, false),
instruments_(instruments), prices_(instruments.size()) {
for (Size i=0; i<prices_.size(); i++) {
instruments_[i]->setModel(model_);
prices_[i] = instruments_[i]->marketValue();
}
}
virtual ~CalibrationFunction() {}
virtual double value(
const Array& params) {
model_->setParams(params);
std::cout << "parameters set to " << params << std::endl;
double value = 0.0;
for (Size i=0; i<prices_.size(); i++) {
double diff = instruments_[i]->calibrationError();
value += diff*diff;
}
std::cout << "Cost function: " << QL_SQRT(value) << std::endl;
return QL_SQRT(value);
}
virtual double finiteDifferenceEpsilon() { return 1e-6; }
private:
Handle<Model> model_;
CalibrationSet& instruments_;
Array prices_;
};
void Model::calibrate(
CalibrationSet& instruments,
const Handle<OptimizationMethod>& method) {
CalibrationFunction f(this, instruments);
method->setInitialValue(params());
method->endCriteria().setPositiveOptimization();
OptimizationProblem prob(f, *constraint_, *method);
prob.minimize();
Array result(prob.minimumValue());
setParams(result);
std::cout << "Cost function: " << f.value(result) << std::endl;
std::cout << "Model calibrated to these parameters:" << std::endl;
for (Size i=0; i<result.size(); i++)
std::cout << i << " " << result[i]*100.0 << "%" << std::endl;
}
}
}
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