/usr/include/ql/pricingengines/basket/mcamericanbasketengine.hpp is in libquantlib0-dev 1.7.1-1.
This file is owned by root:root, with mode 0o644.
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/*
Copyright (C) 2004 Neil Firth
Copyright (C) 2006 Klaus Spanderen
Copyright (C) 2007, 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
<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.
*/
/*! \file mcamericanbasketengine.hpp
\brief Least-square Monte Carlo engines
*/
#ifndef quantlib_american_basket_montecarlo_engine_hpp
#define quantlib_american_basket_montecarlo_engine_hpp
#include <ql/qldefines.hpp>
#include <ql/instruments/basketoption.hpp>
#include <ql/processes/blackscholesprocess.hpp>
#include <ql/processes/stochasticprocessarray.hpp>
#include <ql/methods/montecarlo/lsmbasissystem.hpp>
#include <ql/pricingengines/mclongstaffschwartzengine.hpp>
#include <ql/exercise.hpp>
#include <boost/function.hpp>
namespace QuantLib {
//! least-square Monte Carlo engine
/*! \warning This method is intrinsically weak for out-of-the-money
options.
\ingroup basketengines
*/
template <class RNG = PseudoRandom>
class MCAmericanBasketEngine
: public MCLongstaffSchwartzEngine<BasketOption::engine,
MultiVariate,RNG> {
public:
MCAmericanBasketEngine(const boost::shared_ptr<StochasticProcessArray>&,
Size timeSteps,
Size timeStepsPerYear,
bool brownianBridge,
bool antitheticVariate,
Size requiredSamples,
Real requiredTolerance,
Size maxSamples,
BigNatural seed,
Size nCalibrationSamples = Null<Size>());
protected:
boost::shared_ptr<LongstaffSchwartzPathPricer<MultiPath> >
lsmPathPricer() const;
};
//! Monte Carlo American basket-option engine factory
template <class RNG = PseudoRandom>
class MakeMCAmericanBasketEngine {
public:
MakeMCAmericanBasketEngine(
const boost::shared_ptr<StochasticProcessArray>&);
// named parameters
MakeMCAmericanBasketEngine& withSteps(Size steps);
MakeMCAmericanBasketEngine& withStepsPerYear(Size steps);
MakeMCAmericanBasketEngine& withBrownianBridge(bool b = true);
MakeMCAmericanBasketEngine& withAntitheticVariate(bool b = true);
MakeMCAmericanBasketEngine& withSamples(Size samples);
MakeMCAmericanBasketEngine& withAbsoluteTolerance(Real tolerance);
MakeMCAmericanBasketEngine& withMaxSamples(Size samples);
MakeMCAmericanBasketEngine& withSeed(BigNatural seed);
MakeMCAmericanBasketEngine& withCalibrationSamples(Size samples);
// conversion to pricing engine
operator boost::shared_ptr<PricingEngine>() const;
private:
boost::shared_ptr<StochasticProcessArray> process_;
bool brownianBridge_, antithetic_;
Size steps_, stepsPerYear_, samples_, maxSamples_, calibrationSamples_;
Real tolerance_;
BigNatural seed_;
};
class AmericanBasketPathPricer
: public EarlyExercisePathPricer<MultiPath> {
public:
AmericanBasketPathPricer(Size assetNumber,
const boost::shared_ptr<Payoff>& payoff,
Size polynomOrder = 2,
LsmBasisSystem::PolynomType
polynomType = LsmBasisSystem::Monomial);
Array state(const MultiPath& path, Size t) const;
Real operator()(const MultiPath& path, Size t) const;
std::vector<boost::function1<Real, Array> > basisSystem() const;
protected:
Real payoff(const Array& state) const;
const Size assetNumber_;
const boost::shared_ptr<Payoff> payoff_;
Real scalingValue_;
std::vector<boost::function1<Real, Array> > v_;
};
template <class RNG> inline
MCAmericanBasketEngine<RNG>::MCAmericanBasketEngine(
const boost::shared_ptr<StochasticProcessArray>& processes,
Size timeSteps,
Size timeStepsPerYear,
bool brownianBridge,
bool antitheticVariate,
Size requiredSamples,
Real requiredTolerance,
Size maxSamples,
BigNatural seed,
Size nCalibrationSamples)
: MCLongstaffSchwartzEngine<BasketOption::engine,
MultiVariate,RNG>(processes,
timeSteps,
timeStepsPerYear,
brownianBridge,
antitheticVariate,
false,
requiredSamples,
requiredTolerance,
maxSamples,
seed,
nCalibrationSamples) {}
template <class RNG>
inline boost::shared_ptr<LongstaffSchwartzPathPricer<MultiPath> >
MCAmericanBasketEngine<RNG>::lsmPathPricer() const {
boost::shared_ptr<StochasticProcessArray> processArray =
boost::dynamic_pointer_cast<StochasticProcessArray>(
this->process_);
QL_REQUIRE(processArray && processArray->size()>0,
"Stochastic process array required");
boost::shared_ptr<GeneralizedBlackScholesProcess> process =
boost::dynamic_pointer_cast<GeneralizedBlackScholesProcess>(
processArray->process(0));
QL_REQUIRE(process, "generalized Black-Scholes process required");
boost::shared_ptr<EarlyExercise> exercise =
boost::dynamic_pointer_cast<EarlyExercise>(
this->arguments_.exercise);
QL_REQUIRE(exercise, "wrong exercise given");
QL_REQUIRE(!exercise->payoffAtExpiry(),
"payoff at expiry not handled");
boost::shared_ptr<AmericanBasketPathPricer> earlyExercisePathPricer(
new AmericanBasketPathPricer(processArray->size(),
this->arguments_.payoff));
return boost::shared_ptr<LongstaffSchwartzPathPricer<MultiPath> > (
new LongstaffSchwartzPathPricer<MultiPath>(
this->timeGrid(),
earlyExercisePathPricer,
*(process->riskFreeRate())));
}
template <class RNG>
inline MakeMCAmericanBasketEngine<RNG>::MakeMCAmericanBasketEngine(
const boost::shared_ptr<StochasticProcessArray>& process)
: process_(process), brownianBridge_(false), antithetic_(false),
steps_(Null<Size>()), stepsPerYear_(Null<Size>()),
samples_(Null<Size>()), maxSamples_(Null<Size>()),
calibrationSamples_(Null<Size>()),
tolerance_(Null<Real>()), seed_(0) {}
template <class RNG>
inline MakeMCAmericanBasketEngine<RNG>&
MakeMCAmericanBasketEngine<RNG>::withSteps(Size steps) {
steps_ = steps;
return *this;
}
template <class RNG>
inline MakeMCAmericanBasketEngine<RNG>&
MakeMCAmericanBasketEngine<RNG>::withStepsPerYear(Size steps) {
stepsPerYear_ = steps;
return *this;
}
template <class RNG>
inline MakeMCAmericanBasketEngine<RNG>&
MakeMCAmericanBasketEngine<RNG>::withBrownianBridge(bool brownianBridge) {
brownianBridge_ = brownianBridge;
return *this;
}
template <class RNG>
inline MakeMCAmericanBasketEngine<RNG>&
MakeMCAmericanBasketEngine<RNG>::withAntitheticVariate(bool b) {
antithetic_ = b;
return *this;
}
template <class RNG>
inline MakeMCAmericanBasketEngine<RNG>&
MakeMCAmericanBasketEngine<RNG>::withSamples(Size samples) {
QL_REQUIRE(tolerance_ == Null<Real>(),
"tolerance already set");
samples_ = samples;
return *this;
}
template <class RNG>
inline MakeMCAmericanBasketEngine<RNG>&
MakeMCAmericanBasketEngine<RNG>::withAbsoluteTolerance(Real tolerance) {
QL_REQUIRE(samples_ == Null<Size>(),
"number of samples already set");
QL_REQUIRE(RNG::allowsErrorEstimate,
"chosen random generator policy "
"does not allow an error estimate");
tolerance_ = tolerance;
return *this;
}
template <class RNG>
inline MakeMCAmericanBasketEngine<RNG>&
MakeMCAmericanBasketEngine<RNG>::withMaxSamples(Size samples) {
maxSamples_ = samples;
return *this;
}
template <class RNG>
inline MakeMCAmericanBasketEngine<RNG>&
MakeMCAmericanBasketEngine<RNG>::withSeed(BigNatural seed) {
seed_ = seed;
return *this;
}
template <class RNG>
inline MakeMCAmericanBasketEngine<RNG>&
MakeMCAmericanBasketEngine<RNG>::withCalibrationSamples(Size samples) {
calibrationSamples_ = samples;
return *this;
}
template <class RNG>
inline
MakeMCAmericanBasketEngine<RNG>::operator
boost::shared_ptr<PricingEngine>() const {
QL_REQUIRE(steps_ != Null<Size>() || stepsPerYear_ != Null<Size>(),
"number of steps not given");
QL_REQUIRE(steps_ == Null<Size>() || stepsPerYear_ == Null<Size>(),
"number of steps overspecified");
return boost::shared_ptr<PricingEngine>(new
MCAmericanBasketEngine<RNG>(process_,
steps_,
stepsPerYear_,
brownianBridge_,
antithetic_,
samples_,
tolerance_,
maxSamples_,
seed_,
calibrationSamples_));
}
}
#endif
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