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/* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
/*
Copyright (C) 2001, 2002, 2003 Sadruddin Rejeb
Copyright (C) 2013 Peter Caspers
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
<quantlib-dev@lists.sf.net>. The license is also available online at
<http://quantlib.org/license.shtml>.
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.
*/
#include <ql/models/model.hpp>
#include <ql/math/optimization/problem.hpp>
#include <ql/math/optimization/projection.hpp>
#include <ql/math/optimization/projectedconstraint.hpp>
namespace QuantLib {
namespace {
void no_deletion(CalibratedModel*) {}
}
CalibratedModel::CalibratedModel(Size nArguments)
: arguments_(nArguments),
constraint_(new PrivateConstraint(arguments_)),
shortRateEndCriteria_(EndCriteria::None) {}
class CalibratedModel::CalibrationFunction : public CostFunction {
public:
CalibrationFunction(
CalibratedModel* model,
const std::vector<boost::shared_ptr<CalibrationHelper> >&
instruments,
const std::vector<Real>& weights,
const Projection& projection)
: model_(model, no_deletion), instruments_(instruments),
weights_(weights), projection_(projection) { }
virtual ~CalibrationFunction() {}
virtual Real value(const Array& params) const {
model_->setParams(projection_.include(params));
Real value = 0.0;
for (Size i=0; i<instruments_.size(); i++) {
Real diff = instruments_[i]->calibrationError();
value += diff*diff*weights_[i];
}
return std::sqrt(value);
}
virtual Disposable<Array> values(const Array& params) const {
model_->setParams(projection_.include(params));
Array values(instruments_.size());
for (Size i=0; i<instruments_.size(); i++) {
values[i] = instruments_[i]->calibrationError()
*std::sqrt(weights_[i]);
}
return values;
}
virtual Real finiteDifferenceEpsilon() const { return 1e-6; }
private:
boost::shared_ptr<CalibratedModel> model_;
const std::vector<boost::shared_ptr<CalibrationHelper> >& instruments_;
std::vector<Real> weights_;
const Projection projection_;
};
void CalibratedModel::calibrate(
const std::vector<boost::shared_ptr<CalibrationHelper> >& instruments,
OptimizationMethod& method,
const EndCriteria& endCriteria,
const Constraint& additionalConstraint,
const std::vector<Real>& weights,
const std::vector<bool>& fixParameters) {
QL_REQUIRE(weights.empty() ||
weights.size() == instruments.size(),
"mismatch between number of instruments and weights");
Constraint c;
if (additionalConstraint.empty())
c = *constraint_;
else
c = CompositeConstraint(*constraint_,additionalConstraint);
std::vector<Real> w = weights.empty() ?
std::vector<Real>(instruments.size(), 1.0):
weights;
Array prms = params();
std::vector<bool> all(prms.size(), false);
Projection proj(prms,fixParameters.size()>0 ? fixParameters : all);
CalibrationFunction f(this,instruments,w,proj);
ProjectedConstraint pc(c,proj);
Problem prob(f, pc, proj.project(prms));
shortRateEndCriteria_ = method.minimize(prob, endCriteria);
Array result(prob.currentValue());
setParams(proj.include(result));
Array shortRateProblemValues_ = prob.values(result);
notifyObservers();
}
EndCriteria::Type CalibratedModel::endCriteria() {
return shortRateEndCriteria_;
}
Real CalibratedModel::value(const Array& params,
const std::vector<boost::shared_ptr<CalibrationHelper> >& instruments) {
std::vector<Real> w = std::vector<Real>(instruments.size(), 1.0);
Projection p(params);
CalibrationFunction f(this, instruments, w, p);
return f.value(params);
}
Disposable<Array> CalibratedModel::params() const {
Size size = 0, i;
for (i=0; i<arguments_.size(); i++)
size += arguments_[i].size();
Array params(size);
Size k = 0;
for (i=0; i<arguments_.size(); i++) {
for (Size j=0; j<arguments_[i].size(); j++, k++) {
params[k] = arguments_[i].params()[j];
}
}
return params;
}
void CalibratedModel::setParams(const Array& params) {
Array::const_iterator p = params.begin();
for (Size i=0; i<arguments_.size(); ++i) {
for (Size j=0; j<arguments_[i].size(); ++j, ++p) {
QL_REQUIRE(p!=params.end(),"parameter array too small");
arguments_[i].setParam(j, *p);
}
}
QL_REQUIRE(p==params.end(),"parameter array too big!");
generateArguments();
notifyObservers();
}
ShortRateModel::ShortRateModel(Size nArguments)
: CalibratedModel(nArguments) {}
}
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