Longstaff-Schwarz Monte Carlo engine for early exercise options. More...
#include <ql/experimental/mcbasket/mclongstaffschwartzpathengine.hpp>
Public Types | |
typedef MC< RNG >::path_type | path_type |
typedef McSimulation< MC, RNG, S >::stats_type | stats_type |
typedef McSimulation< MC, RNG, S >::path_pricer_type | path_pricer_type |
typedef McSimulation< MC, RNG, S >::path_generator_type | path_generator_type |
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typedef MonteCarloModel< MC, RNG, S >::path_generator_type | path_generator_type |
typedef MonteCarloModel< MC, RNG, S >::path_pricer_type | path_pricer_type |
typedef MonteCarloModel< MC, RNG, S >::stats_type | stats_type |
typedef MonteCarloModel< MC, RNG, S >::result_type | result_type |
Public Member Functions | |
MCLongstaffSchwartzPathEngine (const boost::shared_ptr< StochasticProcess > &process, Size timeSteps, Size timeStepsPerYear, bool brownianBridge, bool antitheticVariate, bool controlVariate, Size requiredSamples, Real requiredTolerance, Size maxSamples, BigNatural seed, Size nCalibrationSamples=Null< Size >()) | |
void | calculate () const |
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PricingEngine::arguments * | getArguments () const |
const PricingEngine::results * | getResults () const |
void | reset () |
void | update () |
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Observable (const Observable &) | |
Observable & | operator= (const Observable &) |
void | notifyObservers () |
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Observer (const Observer &) | |
Observer & | operator= (const Observer &) |
std::pair< std::set< boost::shared_ptr< Observable > >::iterator, bool > | registerWith (const boost::shared_ptr< Observable > &) |
void | registerWithObservables (const boost::shared_ptr< Observer > &) |
Size | unregisterWith (const boost::shared_ptr< Observable > &) |
void | unregisterWithAll () |
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result_type | value (Real tolerance, Size maxSamples=QL_MAX_INTEGER, Size minSamples=1023) const |
add samples until the required absolute tolerance is reached | |
result_type | valueWithSamples (Size samples) const |
simulate a fixed number of samples | |
result_type | errorEstimate () const |
error estimated using the samples simulated so far | |
const stats_type & | sampleAccumulator (void) const |
access to the sample accumulator for richer statistics | |
void | calculate (Real requiredTolerance, Size requiredSamples, Size maxSamples) const |
basic calculate method provided to inherited pricing engines | |
Protected Member Functions | |
virtual boost::shared_ptr< LongstaffSchwartzMultiPathPricer > | lsmPathPricer () const =0 |
TimeGrid | timeGrid () const |
boost::shared_ptr< path_pricer_type > | pathPricer () const |
boost::shared_ptr< path_generator_type > | pathGenerator () const |
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McSimulation (bool antitheticVariate, bool controlVariate) | |
virtual boost::shared_ptr< path_pricer_type > | controlPathPricer () const |
virtual boost::shared_ptr< path_generator_type > | controlPathGenerator () const |
virtual boost::shared_ptr< PricingEngine > | controlPricingEngine () const |
virtual result_type | controlVariateValue () const |
Protected Attributes | |
boost::shared_ptr< StochasticProcess > | process_ |
const Size | timeSteps_ |
const Size | timeStepsPerYear_ |
const bool | brownianBridge_ |
const Size | requiredSamples_ |
const Real | requiredTolerance_ |
const Size | maxSamples_ |
const Size | seed_ |
const Size | nCalibrationSamples_ |
boost::shared_ptr< LongstaffSchwartzMultiPathPricer > | pathPricer_ |
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ArgumentsType | arguments_ |
ResultsType | results_ |
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boost::shared_ptr< MonteCarloModel< MC, RNG, S > > | mcModel_ |
bool | antitheticVariate_ |
bool | controlVariate_ |
Additional Inherited Members | |
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template<class Sequence > | |
static Real | maxError (const Sequence &sequence) |
static Real | maxError (Real error) |
Longstaff-Schwarz Monte Carlo engine for early exercise options.
References:
Francis Longstaff, Eduardo Schwartz, 2001. Valuing American Options by Simulation: A Simple Least-Squares Approach, The Review of Financial Studies, Volume 14, No. 1, 113-147