/usr/include/ql/pricingengines/vanilla/mcvanillaengine.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) 2003 Ferdinando Ametrano
Copyright (C) 2003, 2004, 2005, 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 mcvanillaengine.hpp
\brief Monte Carlo vanilla option engine
*/
#ifndef quantlib_mcvanilla_engine_hpp
#define quantlib_mcvanilla_engine_hpp
#include <ql/pricingengines/mcsimulation.hpp>
#include <ql/instruments/vanillaoption.hpp>
namespace QuantLib {
//! Pricing engine for vanilla options using Monte Carlo simulation
/*! \ingroup vanillaengines */
template <template <class> class MC, class RNG,
class S = Statistics, class Inst = VanillaOption>
class MCVanillaEngine : public Inst::engine,
public McSimulation<MC,RNG,S> {
public:
void calculate() const {
McSimulation<MC,RNG,S>::calculate(requiredTolerance_,
requiredSamples_,
maxSamples_);
this->results_.value = this->mcModel_->sampleAccumulator().mean();
if (RNG::allowsErrorEstimate)
this->results_.errorEstimate =
this->mcModel_->sampleAccumulator().errorEstimate();
}
protected:
typedef typename McSimulation<MC,RNG,S>::path_generator_type
path_generator_type;
typedef typename McSimulation<MC,RNG,S>::path_pricer_type
path_pricer_type;
typedef typename McSimulation<MC,RNG,S>::stats_type
stats_type;
typedef typename McSimulation<MC,RNG,S>::result_type
result_type;
// constructor
MCVanillaEngine(const boost::shared_ptr<StochasticProcess>&,
Size timeSteps,
Size timeStepsPerYear,
bool brownianBridge,
bool antitheticVariate,
bool controlVariate,
Size requiredSamples,
Real requiredTolerance,
Size maxSamples,
BigNatural seed);
// McSimulation implementation
TimeGrid timeGrid() const;
boost::shared_ptr<path_generator_type> pathGenerator() const {
Size dimensions = process_->factors();
TimeGrid grid = this->timeGrid();
typename RNG::rsg_type generator =
RNG::make_sequence_generator(dimensions*(grid.size()-1),seed_);
return boost::shared_ptr<path_generator_type>(
new path_generator_type(process_, grid,
generator, brownianBridge_));
}
result_type controlVariateValue() const;
// data members
boost::shared_ptr<StochasticProcess> process_;
Size timeSteps_, timeStepsPerYear_;
Size requiredSamples_, maxSamples_;
Real requiredTolerance_;
bool brownianBridge_;
BigNatural seed_;
};
// template definitions
template <template <class> class MC, class RNG, class S, class Inst>
inline MCVanillaEngine<MC,RNG,S,Inst>::MCVanillaEngine(
const boost::shared_ptr<StochasticProcess>& process,
Size timeSteps,
Size timeStepsPerYear,
bool brownianBridge,
bool antitheticVariate,
bool controlVariate,
Size requiredSamples,
Real requiredTolerance,
Size maxSamples,
BigNatural seed)
: McSimulation<MC,RNG,S>(antitheticVariate, controlVariate),
process_(process), timeSteps_(timeSteps),
timeStepsPerYear_(timeStepsPerYear),
requiredSamples_(requiredSamples), maxSamples_(maxSamples),
requiredTolerance_(requiredTolerance),
brownianBridge_(brownianBridge), seed_(seed) {
QL_REQUIRE(timeSteps != Null<Size>() ||
timeStepsPerYear != Null<Size>(),
"no time steps provided");
QL_REQUIRE(timeSteps == Null<Size>() ||
timeStepsPerYear == Null<Size>(),
"both time steps and time steps per year were provided");
QL_REQUIRE(timeSteps != 0,
"timeSteps must be positive, " << timeSteps <<
" not allowed");
QL_REQUIRE(timeStepsPerYear != 0,
"timeStepsPerYear must be positive, " << timeStepsPerYear <<
" not allowed");
this->registerWith(process_);
}
template <template <class> class MC, class RNG, class S, class Inst>
inline typename MCVanillaEngine<MC,RNG,S,Inst>::result_type
MCVanillaEngine<MC,RNG,S,Inst>::controlVariateValue() const {
boost::shared_ptr<PricingEngine> controlPE =
this->controlPricingEngine();
QL_REQUIRE(controlPE,
"engine does not provide "
"control variation pricing engine");
typename Inst::arguments* controlArguments =
dynamic_cast<typename Inst::arguments*>(
controlPE->getArguments());
QL_REQUIRE(controlArguments, "engine is using inconsistent arguments");
*controlArguments = this->arguments_;
controlPE->calculate();
const typename Inst::results* controlResults =
dynamic_cast<const typename Inst::results*>(
controlPE->getResults());
QL_REQUIRE(controlResults,
"engine returns an inconsistent result type");
return result_type(controlResults->value);
}
template <template <class> class MC, class RNG, class S, class Inst>
inline TimeGrid MCVanillaEngine<MC,RNG,S,Inst>::timeGrid() const {
Date lastExerciseDate = this->arguments_.exercise->lastDate();
Time t = process_->time(lastExerciseDate);
if (this->timeSteps_ != Null<Size>()) {
return TimeGrid(t, this->timeSteps_);
} else if (this->timeStepsPerYear_ != Null<Size>()) {
Size steps = static_cast<Size>(this->timeStepsPerYear_*t);
return TimeGrid(t, std::max<Size>(steps, 1));
} else {
QL_FAIL("time steps not specified");
}
}
}
#endif
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