/usr/include/ql/pricingengines/vanilla/mcdigitalengine.hpp is in libquantlib0-dev 1.7.1-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 | /* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
/*
Copyright (C) 2002, 2003 Ferdinando Ametrano
Copyright (C) 2002, 2003 Sadruddin Rejeb
Copyright (C) 2003 Neil Firth
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 mcdigitalengine.hpp
\brief digital option Monte Carlo engine
*/
#ifndef quantlib_digital_mc_engine_hpp
#define quantlib_digital_mc_engine_hpp
#include <ql/exercise.hpp>
#include <ql/termstructures/yieldtermstructure.hpp>
#include <ql/termstructures/volatility/equityfx/blackvoltermstructure.hpp>
#include <ql/methods/montecarlo/mctraits.hpp>
#include <ql/pricingengines/vanilla/mcvanillaengine.hpp>
#include <ql/processes/blackscholesprocess.hpp>
namespace QuantLib {
//! Pricing engine for digital options using Monte Carlo simulation
/*! Uses the Brownian Bridge correction for the barrier found in
<i>
Going to Extremes: Correcting Simulation Bias in Exotic
Option Valuation - D.R. Beaglehole, P.H. Dybvig and G. Zhou
Financial Analysts Journal; Jan/Feb 1997; 53, 1. pg. 62-68
</i>
and
<i>
Simulating path-dependent options: A new approach -
M. El Babsiri and G. Noel
Journal of Derivatives; Winter 1998; 6, 2; pg. 65-83
</i>
\ingroup vanillaengines
\test the correctness of the returned value in case of
cash-or-nothing at-hit digital payoff is tested by
reproducing known good results.
*/
template<class RNG = PseudoRandom, class S = Statistics>
class MCDigitalEngine : public MCVanillaEngine<SingleVariate,RNG,S> {
public:
typedef
typename MCVanillaEngine<SingleVariate,RNG,S>::path_generator_type
path_generator_type;
typedef
typename MCVanillaEngine<SingleVariate,RNG,S>::path_pricer_type
path_pricer_type;
typedef typename MCVanillaEngine<SingleVariate,RNG,S>::stats_type
stats_type;
// constructor
MCDigitalEngine(
const boost::shared_ptr<GeneralizedBlackScholesProcess>&,
Size timeSteps,
Size timeStepsPerYear,
bool brownianBridge,
bool antitheticVariate,
Size requiredSamples,
Real requiredTolerance,
Size maxSamples,
BigNatural seed);
protected:
// McSimulation implementation
boost::shared_ptr<path_pricer_type> pathPricer() const;
};
//! Monte Carlo digital engine factory
template <class RNG = PseudoRandom, class S = Statistics>
class MakeMCDigitalEngine {
public:
MakeMCDigitalEngine(
const boost::shared_ptr<GeneralizedBlackScholesProcess>&);
// named parameters
MakeMCDigitalEngine& withSteps(Size steps);
MakeMCDigitalEngine& withStepsPerYear(Size steps);
MakeMCDigitalEngine& withBrownianBridge(bool b = true);
MakeMCDigitalEngine& withSamples(Size samples);
MakeMCDigitalEngine& withAbsoluteTolerance(Real tolerance);
MakeMCDigitalEngine& withMaxSamples(Size samples);
MakeMCDigitalEngine& withSeed(BigNatural seed);
MakeMCDigitalEngine& withAntitheticVariate(bool b = true);
// conversion to pricing engine
operator boost::shared_ptr<PricingEngine>() const;
private:
boost::shared_ptr<GeneralizedBlackScholesProcess> process_;
bool antithetic_;
Size steps_, stepsPerYear_, samples_, maxSamples_;
Real tolerance_;
bool brownianBridge_;
BigNatural seed_;
};
class DigitalPathPricer : public PathPricer<Path> {
public:
DigitalPathPricer(
const boost::shared_ptr<CashOrNothingPayoff>& payoff,
const boost::shared_ptr<AmericanExercise>& exercise,
const Handle<YieldTermStructure>& discountTS,
const boost::shared_ptr<StochasticProcess1D>& diffProcess,
const PseudoRandom::ursg_type& sequenceGen);
Real operator()(const Path& path) const;
private:
boost::shared_ptr<CashOrNothingPayoff> payoff_;
boost::shared_ptr<AmericanExercise> exercise_;
boost::shared_ptr<StochasticProcess1D> diffProcess_;
PseudoRandom::ursg_type sequenceGen_;
Handle<YieldTermStructure> discountTS_;
};
// template definitions
template<class RNG, class S>
MCDigitalEngine<RNG,S>::MCDigitalEngine(
const boost::shared_ptr<GeneralizedBlackScholesProcess>& process,
Size timeSteps,
Size timeStepsPerYear,
bool brownianBridge,
bool antitheticVariate,
Size requiredSamples,
Real requiredTolerance,
Size maxSamples,
BigNatural seed)
: MCVanillaEngine<SingleVariate,RNG,S>(process,
timeSteps,
timeStepsPerYear,
brownianBridge,
antitheticVariate,
false,
requiredSamples,
requiredTolerance,
maxSamples,
seed) {}
template <class RNG, class S>
inline
boost::shared_ptr<typename MCDigitalEngine<RNG,S>::path_pricer_type>
MCDigitalEngine<RNG,S>::pathPricer() const {
boost::shared_ptr<CashOrNothingPayoff> payoff =
boost::dynamic_pointer_cast<CashOrNothingPayoff>(
this->arguments_.payoff);
QL_REQUIRE(payoff, "wrong payoff given");
boost::shared_ptr<AmericanExercise> exercise =
boost::dynamic_pointer_cast<AmericanExercise>(
this->arguments_.exercise);
QL_REQUIRE(exercise, "wrong exercise given");
boost::shared_ptr<GeneralizedBlackScholesProcess> process =
boost::dynamic_pointer_cast<GeneralizedBlackScholesProcess>(
this->process_);
QL_REQUIRE(process, "Black-Scholes process required");
TimeGrid grid = this->timeGrid();
PseudoRandom::ursg_type sequenceGen(grid.size()-1,
PseudoRandom::urng_type(76));
return boost::shared_ptr<
typename MCDigitalEngine<RNG,S>::path_pricer_type>(
new DigitalPathPricer(payoff,
exercise,
process->riskFreeRate(),
process,
sequenceGen));
}
template <class RNG, class S>
inline MakeMCDigitalEngine<RNG,S>::MakeMCDigitalEngine(
const boost::shared_ptr<GeneralizedBlackScholesProcess>& process)
: process_(process), antithetic_(false),
steps_(Null<Size>()), stepsPerYear_(Null<Size>()),
samples_(Null<Size>()), maxSamples_(Null<Size>()),
tolerance_(Null<Real>()), brownianBridge_(false), seed_(0) {}
template <class RNG, class S>
inline MakeMCDigitalEngine<RNG,S>&
MakeMCDigitalEngine<RNG,S>::withSteps(Size steps) {
steps_ = steps;
return *this;
}
template <class RNG, class S>
inline MakeMCDigitalEngine<RNG,S>&
MakeMCDigitalEngine<RNG,S>::withStepsPerYear(Size steps) {
stepsPerYear_ = steps;
return *this;
}
template <class RNG, class S>
inline MakeMCDigitalEngine<RNG,S>&
MakeMCDigitalEngine<RNG,S>::withSamples(Size samples) {
QL_REQUIRE(tolerance_ == Null<Real>(),
"tolerance already set");
samples_ = samples;
return *this;
}
template <class RNG, class S>
inline MakeMCDigitalEngine<RNG,S>&
MakeMCDigitalEngine<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 MakeMCDigitalEngine<RNG,S>&
MakeMCDigitalEngine<RNG,S>::withMaxSamples(Size samples) {
maxSamples_ = samples;
return *this;
}
template <class RNG, class S>
inline MakeMCDigitalEngine<RNG,S>&
MakeMCDigitalEngine<RNG,S>::withSeed(BigNatural seed) {
seed_ = seed;
return *this;
}
template <class RNG, class S>
inline MakeMCDigitalEngine<RNG,S>&
MakeMCDigitalEngine<RNG,S>::withBrownianBridge(bool brownianBridge) {
brownianBridge_ = brownianBridge;
return *this;
}
template <class RNG, class S>
inline MakeMCDigitalEngine<RNG,S>&
MakeMCDigitalEngine<RNG,S>::withAntitheticVariate(bool b) {
antithetic_ = b;
return *this;
}
template <class RNG, class S>
inline
MakeMCDigitalEngine<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
MCDigitalEngine<RNG,S>(process_,
steps_,
stepsPerYear_,
brownianBridge_,
antithetic_,
samples_, tolerance_,
maxSamples_,
seed_));
}
}
#endif
|