/usr/include/ql/pricingengines/vanilla/mcamericanengine.hpp is in libquantlib0-dev 1.7.1-1.
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/*
Copyright (C) 2006 Klaus Spanderen
Copyright (C) 2007 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 mcamericanengine.hpp
\brief American Monte Carlo engine
*/
#ifndef quantlib_mc_american_engine_hpp
#define quantlib_mc_american_engine_hpp
#include <ql/qldefines.hpp>
#include <ql/payoff.hpp>
#include <ql/exercise.hpp>
#include <ql/methods/montecarlo/lsmbasissystem.hpp>
#include <ql/processes/blackscholesprocess.hpp>
#include <ql/pricingengines/mclongstaffschwartzengine.hpp>
#include <ql/pricingengines/vanilla/mceuropeanengine.hpp>
#include <ql/pricingengines/vanilla/analyticeuropeanengine.hpp>
namespace QuantLib {
//! American Monte Carlo engine
/*! References:
\ingroup vanillaengines
\test the correctness of the returned value is tested by
reproducing results available in web/literature
*/
template <class RNG = PseudoRandom, class S = Statistics>
class MCAmericanEngine
: public MCLongstaffSchwartzEngine<VanillaOption::engine,
SingleVariate,RNG,S>{
public:
MCAmericanEngine(
const boost::shared_ptr<GeneralizedBlackScholesProcess>& process,
Size timeSteps,
Size timeStepsPerYear,
bool antitheticVariate,
bool controlVariate,
Size requiredSamples,
Real requiredTolerance,
Size maxSamples,
BigNatural seed,
Size polynomOrder,
LsmBasisSystem::PolynomType polynomType,
Size nCalibrationSamples = Null<Size>());
void calculate() const;
protected:
boost::shared_ptr<LongstaffSchwartzPathPricer<Path> >
lsmPathPricer() const;
Real controlVariateValue() const;
boost::shared_ptr<PricingEngine> controlPricingEngine() const;
boost::shared_ptr<PathPricer<Path> > controlPathPricer() const;
private:
const Size polynomOrder_;
const LsmBasisSystem::PolynomType polynomType_;
};
class AmericanPathPricer : public EarlyExercisePathPricer<Path> {
public:
AmericanPathPricer(const boost::shared_ptr<Payoff>& payoff,
Size polynomOrder,
LsmBasisSystem::PolynomType polynomType);
Real state(const Path& path, Size t) const;
Real operator()(const Path& path, Size t) const;
std::vector<boost::function1<Real, Real> > basisSystem() const;
protected:
Real payoff(Real state) const;
Real scalingValue_;
const boost::shared_ptr<Payoff> payoff_;
std::vector<boost::function1<Real, Real> > v_;
};
//! Monte Carlo American engine factory
template <class RNG = PseudoRandom, class S = Statistics>
class MakeMCAmericanEngine {
public:
MakeMCAmericanEngine(
const boost::shared_ptr<GeneralizedBlackScholesProcess>&);
// named parameters
MakeMCAmericanEngine& withSteps(Size steps);
MakeMCAmericanEngine& withStepsPerYear(Size steps);
MakeMCAmericanEngine& withSamples(Size samples);
MakeMCAmericanEngine& withAbsoluteTolerance(Real tolerance);
MakeMCAmericanEngine& withMaxSamples(Size samples);
MakeMCAmericanEngine& withSeed(BigNatural seed);
MakeMCAmericanEngine& withAntitheticVariate(bool b = true);
MakeMCAmericanEngine& withControlVariate(bool b = true);
MakeMCAmericanEngine& withPolynomOrder(Size polynomOrer);
MakeMCAmericanEngine& withBasisSystem(LsmBasisSystem::PolynomType);
MakeMCAmericanEngine& withCalibrationSamples(Size calibrationSamples);
// conversion to pricing engine
operator boost::shared_ptr<PricingEngine>() const;
private:
boost::shared_ptr<GeneralizedBlackScholesProcess> process_;
bool antithetic_, controlVariate_;
Size steps_, stepsPerYear_;
Size samples_, maxSamples_, calibrationSamples_;
Real tolerance_;
BigNatural seed_;
Size polynomOrder_;
LsmBasisSystem::PolynomType polynomType_;
};
template <class RNG, class S> inline
MCAmericanEngine<RNG,S>::MCAmericanEngine(
const boost::shared_ptr<GeneralizedBlackScholesProcess>& process,
Size timeSteps, Size timeStepsPerYear,
bool antitheticVariate, bool controlVariate,
Size requiredSamples, Real requiredTolerance,
Size maxSamples,BigNatural seed,
Size polynomOrder, LsmBasisSystem::PolynomType polynomType,
Size nCalibrationSamples)
: MCLongstaffSchwartzEngine<VanillaOption::engine,
SingleVariate,RNG,S>(
process, timeSteps, timeStepsPerYear,
false, antitheticVariate,
controlVariate, requiredSamples,
requiredTolerance, maxSamples,
seed, nCalibrationSamples),
polynomOrder_(polynomOrder),
polynomType_(polynomType) {}
template <class RNG, class S>
inline void MCAmericanEngine<RNG,S>::calculate() const {
MCLongstaffSchwartzEngine<VanillaOption::engine,
SingleVariate,RNG,S>::calculate();
if (this->controlVariate_) {
// control variate might lead to small negative
// option values for deep OTM options
this->results_.value = std::max(0.0, this->results_.value);
}
}
template <class RNG, class S>
inline boost::shared_ptr<LongstaffSchwartzPathPricer<Path> >
MCAmericanEngine<RNG,S>::lsmPathPricer() const {
boost::shared_ptr<GeneralizedBlackScholesProcess> process =
boost::dynamic_pointer_cast<GeneralizedBlackScholesProcess>(
this->process_);
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<AmericanPathPricer> earlyExercisePathPricer(
new AmericanPathPricer(this->arguments_.payoff,
polynomOrder_, polynomType_));
return boost::shared_ptr<LongstaffSchwartzPathPricer<Path> > (
new LongstaffSchwartzPathPricer<Path>(
this->timeGrid(),
earlyExercisePathPricer,
*(process->riskFreeRate())));
}
template <class RNG, class S>
inline boost::shared_ptr<PathPricer<Path> >
MCAmericanEngine<RNG,S>::controlPathPricer() const {
boost::shared_ptr<StrikedTypePayoff> payoff =
boost::dynamic_pointer_cast<StrikedTypePayoff>(
this->arguments_.payoff);
QL_REQUIRE(payoff, "StrikedTypePayoff needed for control variate");
boost::shared_ptr<GeneralizedBlackScholesProcess> process =
boost::dynamic_pointer_cast<GeneralizedBlackScholesProcess>(
this->process_);
QL_REQUIRE(process, "generalized Black-Scholes process required");
return boost::shared_ptr<PathPricer<Path> >(
new EuropeanPathPricer(
payoff->optionType(),
payoff->strike(),
process->riskFreeRate()->discount(this->timeGrid().back()))
);
}
template <class RNG, class S>
inline boost::shared_ptr<PricingEngine>
MCAmericanEngine<RNG,S>::controlPricingEngine() const {
boost::shared_ptr<GeneralizedBlackScholesProcess> process =
boost::dynamic_pointer_cast<GeneralizedBlackScholesProcess>(
this->process_);
QL_REQUIRE(process, "generalized Black-Scholes process required");
return boost::shared_ptr<PricingEngine>(
new AnalyticEuropeanEngine(process));
}
template <class RNG, class S>
inline Real MCAmericanEngine<RNG,S>::controlVariateValue() const {
boost::shared_ptr<PricingEngine> controlPE =
this->controlPricingEngine();
QL_REQUIRE(controlPE,
"engine does not provide "
"control variation pricing engine");
VanillaOption::arguments* controlArguments =
dynamic_cast<VanillaOption::arguments*>(controlPE->getArguments());
*controlArguments = this->arguments_;
controlArguments->exercise = boost::shared_ptr<Exercise>(
new EuropeanExercise(this->arguments_.exercise->lastDate()));
controlPE->calculate();
const VanillaOption::results* controlResults =
dynamic_cast<const VanillaOption::results*>(
controlPE->getResults());
return controlResults->value;
}
template <class RNG, class S>
inline MakeMCAmericanEngine<RNG,S>::MakeMCAmericanEngine(
const boost::shared_ptr<GeneralizedBlackScholesProcess>& process)
: process_(process), antithetic_(false), controlVariate_(false),
steps_(Null<Size>()), stepsPerYear_(Null<Size>()),
samples_(Null<Size>()), maxSamples_(Null<Size>()),
calibrationSamples_(2048),
tolerance_(Null<Real>()), seed_(0),
polynomOrder_(2),
polynomType_ (LsmBasisSystem::Monomial) {}
template <class RNG, class S>
inline MakeMCAmericanEngine<RNG,S>&
MakeMCAmericanEngine<RNG,S>::withPolynomOrder(Size polynomOrder) {
polynomOrder_ = polynomOrder;
return *this;
}
template <class RNG, class S>
inline MakeMCAmericanEngine<RNG,S>&
MakeMCAmericanEngine<RNG,S>::withBasisSystem(
LsmBasisSystem::PolynomType polynomType) {
polynomType_ = polynomType;
return *this;
}
template <class RNG, class S>
inline MakeMCAmericanEngine<RNG,S>&
MakeMCAmericanEngine<RNG,S>::withSteps(Size steps) {
steps_ = steps;
return *this;
}
template <class RNG, class S>
inline MakeMCAmericanEngine<RNG,S>&
MakeMCAmericanEngine<RNG,S>::withStepsPerYear(Size steps) {
stepsPerYear_ = steps;
return *this;
}
template <class RNG, class S>
inline MakeMCAmericanEngine<RNG,S>&
MakeMCAmericanEngine<RNG,S>::withSamples(Size samples) {
QL_REQUIRE(tolerance_ == Null<Real>(),
"tolerance already set");
samples_ = samples;
return *this;
}
template <class RNG, class S>
inline MakeMCAmericanEngine<RNG,S>&
MakeMCAmericanEngine<RNG,S>::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, class S>
inline MakeMCAmericanEngine<RNG,S>&
MakeMCAmericanEngine<RNG,S>::withMaxSamples(Size samples) {
maxSamples_ = samples;
return *this;
}
template <class RNG, class S>
inline MakeMCAmericanEngine<RNG,S>&
MakeMCAmericanEngine<RNG,S>::withCalibrationSamples(Size samples) {
calibrationSamples_ = samples;
return *this;
}
template <class RNG, class S>
inline MakeMCAmericanEngine<RNG,S>&
MakeMCAmericanEngine<RNG,S>::withSeed(BigNatural seed) {
seed_ = seed;
return *this;
}
template <class RNG, class S>
inline MakeMCAmericanEngine<RNG,S>&
MakeMCAmericanEngine<RNG,S>::withAntitheticVariate(bool b) {
antithetic_ = b;
return *this;
}
template <class RNG, class S>
inline MakeMCAmericanEngine<RNG,S>&
MakeMCAmericanEngine<RNG,S>::withControlVariate(bool b) {
controlVariate_ = b;
return *this;
}
template <class RNG, class S>
inline
MakeMCAmericanEngine<RNG,S>::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
MCAmericanEngine<RNG, S>(process_,
steps_,
stepsPerYear_,
antithetic_,
controlVariate_,
samples_, tolerance_,
maxSamples_,
seed_,
polynomOrder_,
polynomType_,
calibrationSamples_));
}
}
#endif
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