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mc_discr_arith_av_strike.hpp
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/* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
/*
Copyright (C) 2008 Master IMAFA - Polytech'Nice Sophia - Université de Nice Sophia Antipolis
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
<[email protected]>. 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 mc_discr_arith_av_strike.hpp
\brief Monte Carlo engine for discrete arithmetic average-strike Asian
*/
#ifndef mc_discrete_arithmetic_average_strike_asian_engine_hpp
#define mc_discrete_arithmetic_average_strike_asian_engine_hpp
#include <ql/exercise.hpp>
#include <ql/pricingengines/asian/mcdiscreteasianenginebase.hpp>
#include <ql/pricingengines/asian/mc_discr_arith_av_strike.hpp>
#include <ql/processes/blackscholesprocess.hpp>
#include <utility>
namespace QuantLib {
//! Monte Carlo pricing engine for discrete arithmetic average-strike Asian
/*! \ingroup asianengines */
template <class RNG = PseudoRandom, class S = Statistics>
class MCDiscreteArithmeticASEngine_2
: public MCDiscreteAveragingAsianEngineBase<SingleVariate,RNG,S> {
public:
typedef
typename MCDiscreteAveragingAsianEngineBase<SingleVariate,RNG,S>::path_generator_type
path_generator_type;
typedef typename MCDiscreteAveragingAsianEngineBase<SingleVariate,RNG,S>::path_pricer_type
path_pricer_type;
typedef typename MCDiscreteAveragingAsianEngineBase<SingleVariate,RNG,S>::stats_type
stats_type;
// constructor
MCDiscreteArithmeticASEngine_2(
const ext::shared_ptr<GeneralizedBlackScholesProcess>& process,
bool brownianBridge,
bool antitheticVariate,
Size requiredSamples,
Real requiredTolerance,
Size maxSamples,
BigNatural seed,
bool withConstantParameters);
protected:
ext::shared_ptr<path_pricer_type> pathPricer() const override;
};
// inline definitions
template <class RNG, class S>
inline
MCDiscreteArithmeticASEngine_2<RNG,S>::MCDiscreteArithmeticASEngine_2(
const ext::shared_ptr<GeneralizedBlackScholesProcess>& process,
bool brownianBridge,
bool antitheticVariate,
Size requiredSamples,
Real requiredTolerance,
Size maxSamples,
BigNatural seed,
bool withConstantParameters)
: MCDiscreteAveragingAsianEngineBase<SingleVariate,RNG,S>(process,
brownianBridge,
antitheticVariate,
false,
requiredSamples,
requiredTolerance,
maxSamples,
seed) {withConstantParameters = withConstantParameters;}
template <class RNG, class S>
inline
ext::shared_ptr<
typename MCDiscreteArithmeticASEngine_2<RNG,S>::path_pricer_type>
MCDiscreteArithmeticASEngine_2<RNG,S>::pathPricer() const {
ext::shared_ptr<PlainVanillaPayoff> payoff =
ext::dynamic_pointer_cast<PlainVanillaPayoff>(
this->arguments_.payoff);
QL_REQUIRE(payoff, "non-plain payoff given");
ext::shared_ptr<EuropeanExercise> exercise =
ext::dynamic_pointer_cast<EuropeanExercise>(
this->arguments_.exercise);
QL_REQUIRE(exercise, "wrong exercise given");
ext::shared_ptr<GeneralizedBlackScholesProcess> process =
ext::dynamic_pointer_cast<GeneralizedBlackScholesProcess>(
this->process_);
QL_REQUIRE(process, "Black-Scholes process required");
return ext::shared_ptr<typename
MCDiscreteArithmeticASEngine_2<RNG,S>::path_pricer_type>(
new ArithmeticASOPathPricer(
payoff->optionType(),
process->riskFreeRate()->discount(exercise->lastDate()),
this->arguments_.runningAccumulator,
this->arguments_.pastFixings));
}
template <class RNG = PseudoRandom, class S = Statistics>
class MakeMCDiscreteArithmeticASEngine_2 {
public:
explicit MakeMCDiscreteArithmeticASEngine_2(
ext::shared_ptr<GeneralizedBlackScholesProcess> process);
// named parameters
MakeMCDiscreteArithmeticASEngine_2& withBrownianBridge(bool b = true);
MakeMCDiscreteArithmeticASEngine_2& withSamples(Size samples);
MakeMCDiscreteArithmeticASEngine_2& withAbsoluteTolerance(Real tolerance);
MakeMCDiscreteArithmeticASEngine_2& withMaxSamples(Size samples);
MakeMCDiscreteArithmeticASEngine_2& withSeed(BigNatural seed);
MakeMCDiscreteArithmeticASEngine_2& withAntitheticVariate(bool b = true);
MakeMCDiscreteArithmeticASEngine_2& withConstantParameters(bool b = true);
// conversion to pricing engine
operator ext::shared_ptr<PricingEngine>() const;
private:
ext::shared_ptr<GeneralizedBlackScholesProcess> process_;
bool antithetic_ = false;
Size samples_, maxSamples_;
Real tolerance_;
bool brownianBridge_ = true;
BigNatural seed_ = 0;
bool withConstantParameters_ = false;
};
template <class RNG, class S>
inline MakeMCDiscreteArithmeticASEngine_2<RNG, S>::MakeMCDiscreteArithmeticASEngine_2(
ext::shared_ptr<GeneralizedBlackScholesProcess> process)
: process_(std::move(process)), samples_(Null<Size>()), maxSamples_(Null<Size>()),
tolerance_(Null<Real>()) {}
template <class RNG, class S>
inline MakeMCDiscreteArithmeticASEngine_2<RNG,S>&
MakeMCDiscreteArithmeticASEngine_2<RNG,S>::withSamples(Size samples) {
QL_REQUIRE(tolerance_ == Null<Real>(),
"tolerance already set");
samples_ = samples;
return *this;
}
template <class RNG, class S>
inline MakeMCDiscreteArithmeticASEngine_2<RNG,S>&
MakeMCDiscreteArithmeticASEngine_2<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 MakeMCDiscreteArithmeticASEngine_2<RNG,S>&
MakeMCDiscreteArithmeticASEngine_2<RNG,S>::withMaxSamples(Size samples) {
maxSamples_ = samples;
return *this;
}
template <class RNG, class S>
inline MakeMCDiscreteArithmeticASEngine_2<RNG,S>&
MakeMCDiscreteArithmeticASEngine_2<RNG,S>::withSeed(BigNatural seed) {
seed_ = seed;
return *this;
}
template <class RNG, class S>
inline MakeMCDiscreteArithmeticASEngine_2<RNG,S>&
MakeMCDiscreteArithmeticASEngine_2<RNG,S>::withBrownianBridge(bool b) {
brownianBridge_ = b;
return *this;
}
template <class RNG, class S>
inline MakeMCDiscreteArithmeticASEngine_2<RNG,S>&
MakeMCDiscreteArithmeticASEngine_2<RNG,S>::withAntitheticVariate(bool b) {
antithetic_ = b;
return *this;
}
template <class RNG, class S>
inline MakeMCDiscreteArithmeticASEngine_2<RNG,S>&
MakeMCDiscreteArithmeticASEngine_2<RNG,S>::withConstantParameters(bool b) {
return *this;
}
template <class RNG, class S>
inline
MakeMCDiscreteArithmeticASEngine_2<RNG,S>::
operator ext::shared_ptr<PricingEngine>() const {
return ext::shared_ptr<PricingEngine>(
new MCDiscreteArithmeticASEngine_2<RNG,S>(process_,
brownianBridge_,
antithetic_,
samples_, tolerance_,
maxSamples_,
seed_,
withConstantParameters_));
}
}
#endif