mceuropeangjrgarchengine.hpp

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/* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
 
/*
 Copyright (C) 2008 Yee Man Chan
 
 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 mceuropeangjrgarchengine.hpp
    \brief Monte Carlo GJR-GARCH-model engine for European options
*/
 
#ifndef quantlib_mc_european_gjrgarch_engine_hpp
#define quantlib_mc_european_gjrgarch_engine_hpp
 
#include <ql/pricingengines/vanilla/mcvanillaengine.hpp>
#include <ql/processes/gjrgarchprocess.hpp>
#include <utility>
 
namespace QuantLib {
 
    //! Monte Carlo GJR-GARCH-model engine for European options
    /*! \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 MCEuropeanGJRGARCHEngine
        : public MCVanillaEngine<MultiVariate,RNG,S> {
      public:
        typedef typename MCVanillaEngine<MultiVariate,RNG,S>::path_pricer_type
            path_pricer_type;
        MCEuropeanGJRGARCHEngine(const ext::shared_ptr<GJRGARCHProcess>&,
                               Size timeSteps,
                               Size timeStepsPerYear,
                               bool antitheticVariate,
                               Size requiredSamples,
                               Real requiredTolerance,
                               Size maxSamples,
                               BigNatural seed);
      protected:
        ext::shared_ptr<path_pricer_type> pathPricer() const override;
    };
 
    //! Monte Carlo GJR-GARCH European engine factory
    template <class RNG = PseudoRandom, class S = Statistics>
    class MakeMCEuropeanGJRGARCHEngine {
      public:
        MakeMCEuropeanGJRGARCHEngine(ext::shared_ptr<GJRGARCHProcess>);
        // named parameters
        MakeMCEuropeanGJRGARCHEngine& withSteps(Size steps);
        MakeMCEuropeanGJRGARCHEngine& withStepsPerYear(Size steps);
        MakeMCEuropeanGJRGARCHEngine& withSamples(Size samples);
        MakeMCEuropeanGJRGARCHEngine& withAbsoluteTolerance(Real tolerance);
        MakeMCEuropeanGJRGARCHEngine& withMaxSamples(Size samples);
        MakeMCEuropeanGJRGARCHEngine& withSeed(BigNatural seed);
        MakeMCEuropeanGJRGARCHEngine& withAntitheticVariate(bool b = true);
        // conversion to pricing engine
        operator ext::shared_ptr<PricingEngine>() const;
      private:
        ext::shared_ptr<GJRGARCHProcess> process_;
        bool antithetic_ = false;
        Size steps_, stepsPerYear_, samples_, maxSamples_;
        Real tolerance_;
        BigNatural seed_ = 0;
    };
 
 
    class EuropeanGJRGARCHPathPricer : public PathPricer<MultiPath> {
      public:
        EuropeanGJRGARCHPathPricer(Option::Type type,
                                 Real strike,
                                 DiscountFactor discount);
        Real operator()(const MultiPath& Multipath) const override;
 
      private:
        PlainVanillaPayoff payoff_;
        DiscountFactor discount_;
    };
 
 
    // template definitions
 
    template <class RNG, class S>
    MCEuropeanGJRGARCHEngine<RNG, S>::MCEuropeanGJRGARCHEngine(
                const ext::shared_ptr<GJRGARCHProcess>& process,
                Size timeSteps, Size timeStepsPerYear, bool antitheticVariate,
                Size requiredSamples, Real requiredTolerance,
                Size maxSamples, BigNatural seed)
    : MCVanillaEngine<MultiVariate,RNG,S>(process, timeSteps, timeStepsPerYear,
                                          false, antitheticVariate, false,
                                          requiredSamples, requiredTolerance,
                                          maxSamples, seed) {}
 
 
    template <class RNG, class S>
    ext::shared_ptr<
        typename MCEuropeanGJRGARCHEngine<RNG,S>::path_pricer_type>
    MCEuropeanGJRGARCHEngine<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<GJRGARCHProcess> process =
            ext::dynamic_pointer_cast<GJRGARCHProcess>(this->process_);
        QL_REQUIRE(process, "GJRGARCH process required");
 
        return ext::shared_ptr<
            typename MCEuropeanGJRGARCHEngine<RNG,S>::path_pricer_type>(
                   new EuropeanGJRGARCHPathPricer(
                                        payoff->optionType(),
                                        payoff->strike(),
                                        process->riskFreeRate()->discount(
                                                   this->timeGrid().back())));
    }
 
 
    template <class RNG, class S>
    inline MakeMCEuropeanGJRGARCHEngine<RNG, S>::MakeMCEuropeanGJRGARCHEngine(
        ext::shared_ptr<GJRGARCHProcess> process)
    : process_(std::move(process)), steps_(Null<Size>()), stepsPerYear_(Null<Size>()),
      samples_(Null<Size>()), maxSamples_(Null<Size>()), tolerance_(Null<Real>()) {}
 
    template <class RNG, class S>
    inline MakeMCEuropeanGJRGARCHEngine<RNG,S>&
    MakeMCEuropeanGJRGARCHEngine<RNG,S>::withSteps(Size steps) {
        QL_REQUIRE(stepsPerYear_ == Null<Size>(),
                   "number of steps per year already set");
        steps_ = steps;
        return *this;
    }
 
    template <class RNG, class S>
    inline MakeMCEuropeanGJRGARCHEngine<RNG,S>&
    MakeMCEuropeanGJRGARCHEngine<RNG,S>::withStepsPerYear(Size steps) {
        QL_REQUIRE(steps_ == Null<Size>(),
                   "number of steps already set");
        stepsPerYear_ = steps;
        return *this;
    }
 
    template <class RNG, class S>
    inline MakeMCEuropeanGJRGARCHEngine<RNG,S>&
    MakeMCEuropeanGJRGARCHEngine<RNG,S>::withSamples(Size samples) {
        QL_REQUIRE(tolerance_ == Null<Real>(),
                   "tolerance already set");
        samples_ = samples;
        return *this;
    }
 
    template <class RNG, class S>
    inline MakeMCEuropeanGJRGARCHEngine<RNG,S>&
    MakeMCEuropeanGJRGARCHEngine<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 MakeMCEuropeanGJRGARCHEngine<RNG,S>&
    MakeMCEuropeanGJRGARCHEngine<RNG,S>::withMaxSamples(Size samples) {
        maxSamples_ = samples;
        return *this;
    }
 
    template <class RNG, class S>
    inline MakeMCEuropeanGJRGARCHEngine<RNG,S>&
    MakeMCEuropeanGJRGARCHEngine<RNG,S>::withSeed(BigNatural seed) {
        seed_ = seed;
        return *this;
    }
 
    template <class RNG, class S>
    inline MakeMCEuropeanGJRGARCHEngine<RNG,S>&
    MakeMCEuropeanGJRGARCHEngine<RNG,S>::withAntitheticVariate(bool b) {
        antithetic_ = b;
        return *this;
    }
 
    template <class RNG, class S>
    inline
    MakeMCEuropeanGJRGARCHEngine<RNG,S>::
    operator ext::shared_ptr<PricingEngine>() const {
        QL_REQUIRE(steps_ != Null<Size>() || stepsPerYear_ != Null<Size>(),
                   "number of steps not given");
        return ext::shared_ptr<PricingEngine>(
                 new MCEuropeanGJRGARCHEngine<RNG,S>(process_,
                                                   steps_,
                                                   stepsPerYear_,
                                                   antithetic_,
                                                   samples_, tolerance_,
                                                   maxSamples_,
                                                   seed_));
    }
 
 
 
    inline EuropeanGJRGARCHPathPricer::EuropeanGJRGARCHPathPricer(
                                                 Option::Type type,
                                                 Real strike,
                                                 DiscountFactor discount)
    : payoff_(type, strike), discount_(discount) {
        QL_REQUIRE(strike>=0.0,
                   "strike less than zero not allowed");
    }
 
    inline Real EuropeanGJRGARCHPathPricer::operator()(
                                           const MultiPath& multiPath) const {
        const Path& path = multiPath[0];
        const Size n = multiPath.pathSize();
        QL_REQUIRE(n>0, "the path cannot be empty");
 
        return payoff_(path.back()) * discount_;
    }
 
}
 
 
#endif