QuantLib
A free/open-source library for quantitative finance
Reference manual - version 1.8
Public Types | Public Member Functions | Protected Member Functions | Protected Attributes | List of all members
MCLongstaffSchwartzEngine< GenericEngine, MC, RNG, S, RNG_Calibration > Class Template Referenceabstract

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 >:

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 std::set< boost::shared_ptr< Observable > > set_type
 
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 (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 >(), boost::optional< bool > brownianBridgeCalibration=boost::none, boost::optional< bool > antitheticVariateCalibration=boost::none, BigNatural seedCalibration=Null< Size >())
 
void calculate () const
 
- Public Member Functions inherited from GenericEngine< ArgumentsType, ResultsType >
PricingEngine::arguments * getArguments () const
 
const PricingEngine::results * getResults () const
 
void reset ()
 
void update ()
 
- Public Member Functions inherited from Observable
 Observable (const Observable &)
 
Observableoperator= (const Observable &)
 
void notifyObservers ()
 
- Public Member Functions inherited from Observer
 Observer (const Observer &)
 
Observeroperator= (const Observer &)
 
std::pair< iterator, bool > registerWith (const boost::shared_ptr< Observable > &)
 
void registerWithObservables (const boost::shared_ptr< Observer > &)
 
Size unregisterWith (const boost::shared_ptr< Observable > &)
 
void unregisterWithAll ()
 
- Public Member Functions inherited from McSimulation< MC, RNG, S >
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_typesampleAccumulator (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< LongstaffSchwartzPathPricer< path_type > > lsmPathPricer () const =0
 
TimeGrid timeGrid () const
 
boost::shared_ptr< path_pricer_typepathPricer () const
 
boost::shared_ptr< path_generator_typepathGenerator () const
 
- Protected Member Functions inherited from McSimulation< MC, RNG, S >
 McSimulation (bool antitheticVariate, bool controlVariate)
 
virtual boost::shared_ptr< path_pricer_typecontrolPathPricer () const
 
virtual boost::shared_ptr< path_generator_typecontrolPathGenerator () const
 
virtual boost::shared_ptr< PricingEnginecontrolPricingEngine () const
 
virtual result_type controlVariateValue () const
 

Protected Attributes

boost::shared_ptr< StochasticProcessprocess_
 
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_
 
boost::shared_ptr< LongstaffSchwartzPathPricer< path_type > > pathPricer_
 
boost::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 >
boost::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

Constructor & Destructor Documentation

MCLongstaffSchwartzEngine ( 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>(),
boost::optional< bool >  brownianBridgeCalibration = boost::none,
boost::optional< bool >  antitheticVariateCalibration = boost::none,
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).