19830875741

Committed 01 Dec 2025 05:03PM UTC coverage: 74.35% (+0.4%) from 73.914%

Build # 19830875741

Build Type

Pull #2344

github

Committed by

web-flow

Commit Message

Merge 313f6c36a into b3612efbd

Pull Request Pull Request #2344: add multicurve bootstrap

Run Details

111 of 125 new or added lines in 6 files covered. (88.8%)

413 existing lines in 27 files now uncovered.

57218 of 76958 relevant lines covered (74.35%)

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81.25

/ql/termstructures/globalbootstrap.cpp

/* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */

/*
 Copyright (C) 2019 SoftSolutions! S.r.l.
 Copyright (C) 2025 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/math/optimization/levenbergmarquardt.hpp>
#include <ql/termstructures/globalbootstrap.hpp>

namespace QuantLib {

MultiCurveBootstrap::MultiCurveBootstrap(Real accuracy) {
    optimizer_ = ext::make_shared<LevenbergMarquardt>(accuracy, accuracy, accuracy);
    endCriteria_ = ext::make_shared<EndCriteria>(1000, 10, accuracy, accuracy, accuracy);
}

MultiCurveBootstrap::MultiCurveBootstrap(ext::shared_ptr<OptimizationMethod> optimizer,
                                         ext::shared_ptr<EndCriteria> endCriteria)
: optimizer_(std::move(optimizer)), endCriteria_(std::move(endCriteria)) {
    constexpr Real accuracy = 1E-10;
    if (optimizer_ == nullptr)
        optimizer_ = ext::make_shared<LevenbergMarquardt>(accuracy, accuracy, accuracy);
    if (endCriteria_ == nullptr)
        endCriteria_ = ext::make_shared<EndCriteria>(1000, 10, accuracy, accuracy, accuracy);
}

void MultiCurveBootstrap::add(const MultiCurveBootstrapContributor* c) {
    contributors_.push_back(c);
    c->setParentBootstrapper(shared_from_this());
}

void MultiCurveBootstrap::addObserver(Observer* o) {
    observers_.push_back(o);
}

void MultiCurveBootstrap::runMultiCurveBootstrap() {

    std::vector<Size> guessSizes;
    std::vector<Real> globalGuess;

    for (auto const& c : contributors_) {
        Array guess = c->setupCostFunction();
        globalGuess.insert(globalGuess.end(), guess.begin(), guess.end());
        guessSizes.push_back(guess.size());
    }

    auto fn = [this, &guessSizes](const Array& x) {
        // call the contributors' cost functions' set part

        std::size_t offset = 0;
        for (std::size_t c = 0; c < contributors_.size(); ++c) {
            Array tmp(guessSizes[c]);
            std::copy(std::next(x.begin(), offset), std::next(x.begin(), offset + guessSizes[c]),
                      tmp.begin());
            offset += guessSizes[c];
            contributors_[c]->setCostFunctionArgument(tmp);
        }

        // update observers
        for(auto o: observers_)
            o->update();

        // collect the contributors' result

        std::vector<Array> results;
        for (std::size_t c = 0; c < contributors_.size(); ++c) {
            results.push_back(contributors_[c]->evaluateCostFunction());
        }

        // concatenate the contributors' values and return the concatenation as the result

        std::size_t resultSize =
            std::accumulate(results.begin(), results.end(), 0,
                            [](std::size_t len, const Array& a) { return len + a.size(); });

        Array result(resultSize);

        offset = 0;
        for (auto const& r : results) {
            std::copy(r.begin(), r.end(), std::next(result.begin(), offset));
            offset += r.size();
        }

        return result;
    };

    SimpleCostFunction<decltype(fn)> costFunction(fn);
    NoConstraint noConstraint;
    Problem problem(costFunction, noConstraint, Array(globalGuess.begin(), globalGuess.end()));
    EndCriteria::Type endType = optimizer_->minimize(problem, *endCriteria_);

    QL_REQUIRE(
        EndCriteria::succeeded(endType),
        "global bootstrap failed to minimize to required accuracy (during multi curve bootstrap): "
            << endType);

    // set all contributors to valid

    for (auto const& c : contributors_)
        c->setToValid();
}

} // namespace QuantLib

1	/* -- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -- */
2
3	/*
4	Copyright (C) 2019 SoftSolutions! S.r.l.
5	Copyright (C) 2025 Peter Caspers
6
7	This file is part of QuantLib, a free-software/open-source library
8	for financial quantitative analysts and developers - http://quantlib.org/
9
10	QuantLib is free software: you can redistribute it and/or modify it
11	under the terms of the QuantLib license. You should have received a
12	copy of the license along with this program; if not, please email
13	<quantlib-dev@lists.sf.net>. The license is also available online at
14	<http://quantlib.org/license.shtml>.
15
16	This program is distributed in the hope that it will be useful, but WITHOUT
17	ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
18	FOR A PARTICULAR PURPOSE. See the license for more details.
19	*/
20
21	#include <ql/math/optimization/levenbergmarquardt.hpp>
22	#include <ql/termstructures/globalbootstrap.hpp>
23
24	namespace QuantLib {
25
26	MultiCurveBootstrap::MultiCurveBootstrap(Real accuracy) {	2✔
27	optimizer_ = ext::make_shared<LevenbergMarquardt>(accuracy, accuracy, accuracy);	2✔
28	endCriteria_ = ext::make_shared<EndCriteria>(1000, 10, accuracy, accuracy, accuracy);	2✔
29	}	2✔
30
NEW 31	MultiCurveBootstrap::MultiCurveBootstrap(ext::shared_ptr<OptimizationMethod> optimizer,	×
NEW 32	ext::shared_ptr<EndCriteria> endCriteria)	×
NEW 33	: optimizer_(std::move(optimizer)), endCriteria_(std::move(endCriteria)) {	×
NEW 34	constexpr Real accuracy = 1E-10;	×
NEW 35	if (optimizer_ == nullptr)	×
NEW 36	optimizer_ = ext::make_shared<LevenbergMarquardt>(accuracy, accuracy, accuracy);	×
NEW 37	if (endCriteria_ == nullptr)	×
NEW 38	endCriteria_ = ext::make_shared<EndCriteria>(1000, 10, accuracy, accuracy, accuracy);	×
NEW 39	}	×
40
41	void MultiCurveBootstrap::add(const MultiCurveBootstrapContributor* c) {	3✔
42	contributors_.push_back(c);	3✔
43	c->setParentBootstrapper(shared_from_this());	3✔
44	}	3✔
45
46	void MultiCurveBootstrap::addObserver(Observer* o) {	1✔
47	observers_.push_back(o);	1✔
48	}	1✔
49
50	void MultiCurveBootstrap::runMultiCurveBootstrap() {	2✔
51
52	std::vector<Size> guessSizes;
53	std::vector<Real> globalGuess;
54
55	for (auto const& c : contributors_) {	5✔
56	Array guess = c->setupCostFunction();	3✔
57	globalGuess.insert(globalGuess.end(), guess.begin(), guess.end());	3✔
58	guessSizes.push_back(guess.size());	3✔
59	}
60
61	auto fn = [this, &guessSizes](const Array& x) {	1,251✔
62	// call the contributors' cost functions' set part
63
64	std::size_t offset = 0;
65	for (std::size_t c = 0; c < contributors_.size(); ++c) {	475✔
66	Array tmp(guessSizes[c]);	301✔
67	std::copy(std::next(x.begin(), offset), std::next(x.begin(), offset + guessSizes[c]),	301✔
68	tmp.begin());
69	offset += guessSizes[c];	301✔
70	contributors_[c]->setCostFunctionArgument(tmp);	301✔
71	}
72
73	// update observers
74	for(auto o: observers_)	221✔
75	o->update();	47✔
76
77	// collect the contributors' result
78
79	std::vector<Array> results;
80	for (std::size_t c = 0; c < contributors_.size(); ++c) {	475✔
81	results.push_back(contributors_[c]->evaluateCostFunction());	602✔
82	}
83
84	// concatenate the contributors' values and return the concatenation as the result
85
86	std::size_t resultSize =
87	std::accumulate(results.begin(), results.end(), 0,
88	[](std::size_t len, const Array& a) { return len + a.size(); });	301✔
89
90	Array result(resultSize);	174✔
91
92	offset = 0;
93	for (auto const& r : results) {	475✔
94	std::copy(r.begin(), r.end(), std::next(result.begin(), offset));	301✔
95	offset += r.size();	301✔
96	}
97
98	return result;	174✔
99	};	174✔
100
101	SimpleCostFunction<decltype(fn)> costFunction(fn);
102	NoConstraint noConstraint;
103	Problem problem(costFunction, noConstraint, Array(globalGuess.begin(), globalGuess.end()));	2✔
104	EndCriteria::Type endType = optimizer_->minimize(problem, *endCriteria_);	2✔
105
106	QL_REQUIRE(	2✔
107	EndCriteria::succeeded(endType),
108	"global bootstrap failed to minimize to required accuracy (during multi curve bootstrap): "
109	<< endType);
110
111	// set all contributors to valid
112
113	for (auto const& c : contributors_)	5✔
114	c->setToValid();	3✔
115	}	2✔
116
117	} // namespace QuantLib

lballabio / QuantLib / 19830875741

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