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/* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
/*
Copyright (C) 2008 StatPro Italia srl
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
<https://www.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 "toplevelfixture.hpp"
#include "utilities.hpp"
#include <ql/experimental/exoticoptions/everestoption.hpp>
#include <ql/experimental/exoticoptions/mceverestengine.hpp>
#include <ql/math/randomnumbers/rngtraits.hpp>
#include <ql/time/daycounters/actual360.hpp>
#include <ql/quotes/simplequote.hpp>
using namespace QuantLib;
using namespace boost::unit_test_framework;
BOOST_FIXTURE_TEST_SUITE(QuantLibTests, TopLevelFixture)
BOOST_AUTO_TEST_SUITE(EverestOptionTests)
BOOST_AUTO_TEST_CASE(testCached) {
BOOST_TEST_MESSAGE("Testing Everest option against cached values...");
Date today = Settings::instance().evaluationDate();
DayCounter dc = Actual360();
Date exerciseDate = today+360;
ext::shared_ptr<Exercise> exercise(new EuropeanExercise(exerciseDate));
Real notional = 1.0;
Rate guarantee = 0.0;
EverestOption option(notional, guarantee, exercise);
Handle<YieldTermStructure> riskFreeRate(flatRate(today, 0.05, dc));
std::vector<ext::shared_ptr<StochasticProcess1D> > processes(4);
Handle<Quote> dummyUnderlying(ext::shared_ptr<Quote>(
new SimpleQuote(1.0)));
processes[0] = ext::shared_ptr<StochasticProcess1D>(
new BlackScholesMertonProcess(
dummyUnderlying,
Handle<YieldTermStructure>(flatRate(today, 0.01, dc)),
riskFreeRate,
Handle<BlackVolTermStructure>(flatVol(today, 0.30, dc))));
processes[1] = ext::shared_ptr<StochasticProcess1D>(
new BlackScholesMertonProcess(
dummyUnderlying,
Handle<YieldTermStructure>(flatRate(today, 0.05, dc)),
riskFreeRate,
Handle<BlackVolTermStructure>(flatVol(today, 0.35, dc))));
processes[2] = ext::shared_ptr<StochasticProcess1D>(
new BlackScholesMertonProcess(
dummyUnderlying,
Handle<YieldTermStructure>(flatRate(today, 0.04, dc)),
riskFreeRate,
Handle<BlackVolTermStructure>(flatVol(today, 0.25, dc))));
processes[3] = ext::shared_ptr<StochasticProcess1D>(
new BlackScholesMertonProcess(
dummyUnderlying,
Handle<YieldTermStructure>(flatRate(today, 0.03, dc)),
riskFreeRate,
Handle<BlackVolTermStructure>(flatVol(today, 0.20, dc))));
Matrix correlation(4,4);
correlation[0][0] = 1.00;
correlation[0][1] = 0.50;
correlation[0][2] = 0.30;
correlation[0][3] = 0.10;
correlation[1][0] = 0.50;
correlation[1][1] = 1.00;
correlation[1][2] = 0.20;
correlation[1][3] = 0.40;
correlation[2][0] = 0.30;
correlation[2][1] = 0.20;
correlation[2][2] = 1.00;
correlation[2][3] = 0.60;
correlation[3][0] = 0.10;
correlation[3][1] = 0.40;
correlation[3][2] = 0.60;
correlation[3][3] = 1.00;
BigNatural seed = 86421;
Size fixedSamples = 1023;
Real minimumTol = 1.0e-2;
ext::shared_ptr<StochasticProcessArray> process(
new StochasticProcessArray(processes, correlation));
option.setPricingEngine(MakeMCEverestEngine<PseudoRandom>(process)
.withStepsPerYear(1)
.withSamples(fixedSamples)
.withSeed(seed));
Real value = option.NPV();
Real storedValue = 0.75784944;
Real tolerance = 1.0e-8;
if (std::fabs(value-storedValue) > tolerance)
BOOST_FAIL(std::setprecision(10)
<< " calculated value: " << value << "\n"
<< " expected: " << storedValue);
tolerance = option.errorEstimate();
tolerance = std::min<Real>(tolerance/2.0, minimumTol*value);
option.setPricingEngine(MakeMCEverestEngine<PseudoRandom>(process)
.withStepsPerYear(1)
.withAbsoluteTolerance(tolerance)
.withSeed(seed));
option.NPV();
Real accuracy = option.errorEstimate();
if (accuracy > tolerance)
BOOST_FAIL(std::setprecision(10)
<< " reached accuracy: " << accuracy << "\n"
<< " expected: " << tolerance);
}
BOOST_AUTO_TEST_SUITE_END()
BOOST_AUTO_TEST_SUITE_END()
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