Calculate price and sensitivities for European or American basket options using Monte Carlo simulations
PriceSens = basketsensbyls(RateSpec,BasketStockSpec,OptSpec,Strike,Settle,ExerciseDates)
PriceSens = basketsensbyls(RateSpec,BasketStockSpec,OptSpec,Strike,Settle,ExerciseDates,'ParameterName'
,ParameterValue
,
...)
PriceSens = basketsensbyls(RateSpec,BasketStockSpec,OptSpec,Strike,Settle,ExerciseDates)
prices
basket options using the LongstaffSchwartz model.
For American options, the LongstaffSchwartz least squares method is used to calculate the early exercise premium.
PriceSens = basketsensbyls(RateSpec,BasketStockSpec,OptSpec,Strike,Settle,ExerciseDates,
accepts optional inputs as one or more commaseparated
parameter/value pairs. 'ParameterName'
,ParameterValue
,
...)'ParameterName'
is
the name of the parameter inside single quotes. ParameterValue
is
the value corresponding to 'ParameterName'
.
Specify parametervalue pairs in any order. Names are caseinsensitive
and partial matches are allowable, if no ambiguities exist.

Annualized, continuously compounded rate term structure. For
more information on the interest rate specification, see 



Character vector or 

The option strike price:


Scalar of settlement or trade date. 

The exercise date for the option:


Parameter values are a scalar flag.
NoteFor American options, the LongstaffSchwartz least squares method is used to calculate the early exercise premium. For more information on the least squares method, see https://people.math.ethz.ch/%7Ehjfurrer/teaching/LongstaffSchwartzAmericanOptionsLeastSquareMonteCarlo.pdf.
Default: 0 

Parameter value is a scalar number of simulation periods. Default: 100 

Parameter value is a scalar number of independent sample paths (simulation trials). Default: 1000 

Parameter value is an
Default: 

Scalar of the indice of the underlying instrument to compute the sensitivity. Default: 

Expected prices or sensitivities values. 
Longstaff, F.A., and E.S. Schwartz. “Valuing American Options by Simulation: A Simple LeastSquares Approach.” The Review of Financial Studies. Vol. 14, No. 1, Spring 2001, pp. 113–147.