Longstaff-Schwarz Monte Carlo engine for early exercise options. More...

#include <ql/pricingengines/mclongstaffschwartzengine.hpp>

Inheritance diagram for MCLongstaffSchwartzEngine< GenericEngine, MC, RNG, S, RNG_Calibration >:

Collaboration diagram for MCLongstaffSchwartzEngine< GenericEngine, MC, RNG, S, RNG_Calibration >:

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

typedef McSimulation< MC, RNG_Calibration, S >::path_generator_type	path_generator_type_calibration

Public Types inherited from Observer
typedef set_type::iterator	iterator

Public Types inherited from McSimulation< MC, RNG, S >
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
	MCLongstaffSchwartzEngine (ext::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 >(), ext::optional< bool > brownianBridgeCalibration=ext::nullopt, ext::optional< bool > antitheticVariateCalibration=ext::nullopt, BigNatural seedCalibration=Null< Size >())

void	calculate () const override

Public Member Functions inherited from GenericEngine< ArgumentsType, ResultsType >
PricingEngine::arguments *	getArguments () const override

const PricingEngine::results *	getResults () const override

void	reset () override

void	update () override

Public Member Functions inherited from PricingEngine
	~PricingEngine () override=default

virtual arguments *	getArguments () const =0

virtual const results *	getResults () const =0

virtual void	reset ()=0

virtual void	calculate () const =0

Public Member Functions inherited from Observable
	Observable ()

	Observable (const Observable &)

Observable &	operator= (const Observable &)

	Observable (Observable &&)=delete

Observable &	operator= (Observable &&)=delete

virtual	~Observable ()=default

void	notifyObservers ()

Public Member Functions inherited from Observer
	Observer ()=default

	Observer (const Observer &)

Observer &	operator= (const Observer &)

virtual	~Observer ()

std::pair< iterator, bool >	registerWith (const ext::shared_ptr< Observable > &)

void	registerWithObservables (const ext::shared_ptr< Observer > &)

Size	unregisterWith (const ext::shared_ptr< Observable > &)

void	unregisterWithAll ()

virtual void	update ()=0

virtual void	deepUpdate ()

Public Member Functions inherited from McSimulation< MC, RNG, S >
virtual	~McSimulation ()=default

result_type	value (Real tolerance, Size maxSamples=QL_MAX_INTEGER, Size minSamples=1023) const
	add samples until the required absolute tolerance is reached More...

result_type	valueWithSamples (Size samples) const
	simulate a fixed number of samples More...

result_type	errorEstimate () const
	error estimated using the samples simulated so far More...

const stats_type &	sampleAccumulator () const
	access to the sample accumulator for richer statistics More...

void	calculate (Real requiredTolerance, Size requiredSamples, Size maxSamples) const
	basic calculate method provided to inherited pricing engines More...

Protected Member Functions
virtual ext::shared_ptr< LongstaffSchwartzPathPricer< path_type > >	lsmPathPricer () const =0

TimeGrid	timeGrid () const override

ext::shared_ptr< path_pricer_type >	pathPricer () const override

ext::shared_ptr< path_generator_type >	pathGenerator () const override

Protected Member Functions inherited from McSimulation< MC, RNG, S >
	McSimulation (bool antitheticVariate, bool controlVariate)

virtual ext::shared_ptr< path_pricer_type >	pathPricer () const =0

virtual ext::shared_ptr< path_generator_type >	pathGenerator () const =0

virtual TimeGrid	timeGrid () const =0

virtual ext::shared_ptr< path_pricer_type >	controlPathPricer () const

virtual ext::shared_ptr< path_generator_type >	controlPathGenerator () const

virtual ext::shared_ptr< PricingEngine >	controlPricingEngine () const

virtual result_type	controlVariateValue () const

Protected Attributes
ext::shared_ptr< StochasticProcess >	process_

const Size	timeSteps_

const Size	timeStepsPerYear_

const bool	brownianBridge_

const Size	requiredSamples_

const Real	requiredTolerance_

const Size	maxSamples_

const BigNatural	seed_

const Size	nCalibrationSamples_

const bool	brownianBridgeCalibration_

const bool	antitheticVariateCalibration_

const BigNatural	seedCalibration_

ext::shared_ptr< LongstaffSchwartzPathPricer< path_type > >	pathPricer_

ext::shared_ptr< MonteCarloModel< MC, RNG_Calibration, S > >	mcModelCalibration_

Protected Attributes inherited from GenericEngine< ArgumentsType, ResultsType >
ArgumentsType	arguments_

ResultsType	results_

Protected Attributes inherited from McSimulation< MC, RNG, S >
ext::shared_ptr< MonteCarloModel< MC, RNG, S > >	mcModel_

bool	antitheticVariate_

bool	controlVariate_

Additional Inherited Members
Static Protected Member Functions inherited from McSimulation< MC, RNG, S >
template<class Sequence >
static Real	maxError (const Sequence &sequence)

static Real	maxError (Real error)

Detailed Description

template<class GenericEngine, template< class > class MC, class RNG, class S = Statistics, class RNG_Calibration = RNG>
class QuantLib::MCLongstaffSchwartzEngine< GenericEngine, MC, RNG, S, RNG_Calibration >

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

Tests:: the correctness of the returned value is tested by reproducing results available in web/literature

Definition at line 49 of file mclongstaffschwartzengine.hpp.

Member Typedef Documentation

◆ path_type

typedef MC<RNG>::path_type path_type

Definition at line 52 of file mclongstaffschwartzengine.hpp.

◆ stats_type

typedef McSimulation<MC,RNG,S>::stats_type stats_type

Definition at line 54 of file mclongstaffschwartzengine.hpp.

◆ path_pricer_type

typedef McSimulation<MC,RNG,S>::path_pricer_type path_pricer_type

Definition at line 56 of file mclongstaffschwartzengine.hpp.

◆ path_generator_type

typedef McSimulation<MC,RNG,S>::path_generator_type path_generator_type

Definition at line 58 of file mclongstaffschwartzengine.hpp.

◆ path_generator_type_calibration

typedef McSimulation<MC,RNG_Calibration,S>::path_generator_type path_generator_type_calibration

Definition at line 61 of file mclongstaffschwartzengine.hpp.

Constructor & Destructor Documentation

◆ MCLongstaffSchwartzEngine()

MCLongstaffSchwartzEngine	(	ext::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>()`,
		ext::optional< bool >	brownianBridgeCalibration = `ext::nullopt`,
		ext::optional< bool >	antitheticVariateCalibration = `ext::nullopt`,
		BigNatural	seedCalibration = `Null<Size>()`
	)

If the parameters brownianBridge and antitheticVariate are not given they are chosen to be identical to the respective parameters for pricing; the seed for calibration is chosen to be zero if the pricing seed is zero and otherwise as the pricing seed plus some offset to avoid identical paths in calibration and pricing; note however that this has no effect for low discrepancy RNGs usually, it is therefore recommended to use pseudo random generators for the calibration phase always (and possibly quasi monte carlo in the subsequent pricing).

Definition at line 122 of file mclongstaffschwartzengine.hpp.

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