RollGeskeWhaley

Create RollGeskeWhaley pricer object for American exercise Vanilla instrument using BlackScholes model

Description

Create and price a Vanilla instrument object with a BlackScholes model and a RollGeskeWhaley pricing method using this workflow:

1. Use fininstrument to create a Vanilla instrument object.

2. Use finmodel to specify a BlackScholes model for the Vanilla instrument object.

3. Use finpricer to specify a RollGeskeWhaley pricer object for the Vanilla instrument object (American exercise).

For more information on this workflow, see Get Started with Workflows Using Object-Based Framework for Pricing Financial Instruments.

For more information on the available instruments, models, and pricing methods for a Vanilla instrument, see Choose Instruments, Models, and Pricers.

Creation

Syntax

RollGeskeWhaleyPricerObj = finpricer(PricerType,'Model',model,'DiscountCurve',ratecurve_obj,'SpotPrice',spotrate_value,'DividendType',dividendtype,'DividendValue',dividendvalue)

RollGeskeWhaleyPricerObj = finpricer(___,Name,Value)

Description

RollGeskeWhaleyPricerObj = finpricer(PricerType,'Model',model,'DiscountCurve',ratecurve_obj,'SpotPrice',spotrate_value,'DividendType',dividendtype,'DividendValue',dividendvalue) creates a RollGeskeWhaley pricer object by specifying PricerType and sets the properties for the required name-value pair arguments Model, DiscountCurve, and SpotPrice.

RollGeskeWhaleyPricerObj = finpricer(___,Name,Value) to set optional properties using additional name-value pairs in addition to the required arguments in the previous syntax. For example, RollGeskeWhaleyPricerObj = finpricer("Analytic",'Model',BSModel,'DiscountCurve',ratecurve_obj,'SpotPrice',1000,'DividendValue',timetable(datetime(2021,6,15),2.5),'DividendType',"cash",'PricingMethod',"RollGeskeWhaley") creates a RollGeskeWhaley pricer object. You can specify multiple name-value pair arguments.

Input Arguments

PricerType — Pricer type

string with value "Analytic" | character vector with value 'Analytic'

Pricer type, specified as a string with the value of "Analytic" or a character vector with the value of 'Analytic'.

Data Types: char | string

Name-Value Arguments

Specify required and optional pairs of arguments as Name1=Value1,...,NameN=ValueN, where Name is the argument name and Value is the corresponding value. Name-value arguments must appear after other arguments, but the order of the pairs does not matter.

Before R2021a, use commas to separate each name and value, and enclose Name in quotes.

Example: RollGeskeWhaleyPricerObj = finpricer("Analytic",'Model',BSModel,'DiscountCurve',ratecurve_obj,'SpotPrice',1000,'DividendValue',timetable(datetime(2021,6,15),2.5),'DividendType',"cash",'PricingMethod',"RollGeskeWhaley")

Required RollGeskeWhaley Name-Value Pair Arguments

Model — Model

BlackScholes model object

Model, specified as the comma-separated pair consisting of 'Model' and the name of a previously created BlackScholes model object using finmodel.

Data Types: object

DiscountCurve — ratecurve object for discounting cash flows

ratecurve object

ratecurve object for discounting cash flows, specified as the comma-separated pair consisting of 'DiscountCurve' and the name of a previously created ratecurve object.

Note

Specify a flat ratecurve object for DiscountCurve. If you use a nonflat ratecurve object, the software uses the rate in the ratecurve object at Maturity and assumes that the value is constant for the life of the equity option.

Data Types: object

SpotPrice — Current price of underlying asset

nonnegative numeric

Current price of the underlying asset, specified as the comma-separated pair consisting of 'SpotPrice' and a scalar nonnegative numeric.

Data Types: double

DividendValue — Cash dividend for underlying stock

timetable

Cash dividend for the underlying stock, specified as the comma-separated pair consisting of 'DividendValue' and a timetable.

Data Types: timetable

Optional RollGeskeWhaley Name-Value Pair Arguments

DividendType — Stock dividend type

"cash" (default) | string with value "cash" | character vector with value 'cash'

Stock dividend type, specified as the comma-separated pair consisting of 'DividendType' and a string or character vector.

Data Types: char | string

PricingMethod — Analytic pricing method

default pricer associated with BlackScholes model (default) | string with value "RollGeskeWhaley" | character vector with value 'RollGeskeWhaley'

Analytic pricing method, specified as the comma-separated pair consisting of 'PricingMethod' and a string or character vector.

Note

The default pricing method for a BlackScholes model is a BlackScholes pricer.

Data Types: double

Output Arguments

RollGeskeWhaleyPricerObj — Roll-Geske-Whaley pricer

RollGeskeWhaley object

Roll-Geske-Whaley pricer, returned as a RollGeskeWhaley object.

Properties

Model — Model

BlackScholes model object

Model, returned as a BlackScholes model object.

Data Types: object

DiscountCurve — ratecurve object for discounting cash flows

ratecurve object

ratecurve object for discounting cash flows, returned as a ratecurve object.

Data Types: object

SpotPrice — Current price of underlying asset

nonnegative numeric

Current price of the underlying asset, returned as a scalar nonnegative numeric.

Data Types: double

DividendValue — Cash dividend for underlying stock

timetable

Cash dividend for the underlying stock, returned as a timetable.

Data Types: timetable

DividendType — Stock dividend type

"cash" (default) | string with value "cash"

Stock dividend type, returned as a string.

Data Types: char | string

PricingMethod — Analytic pricing method

default pricer associated with BlackScholes model (default) | string with value "RollGeskeWhaley"

Analytic pricing method, returned as a string.

Data Types: string

Object Functions

price

Compute price for interest-rate, equity, or credit derivative instrument with Analytic pricer

Examples

Use a RollGeskeWhaley Pricer and BlackScholes Model to Price Vanilla Instrument

This example shows the workflow to price an American exercise Vanilla instrument when you use a BlackScholes model and a RollGeskeWhaley pricing method.

Create Vanilla Instrument Object

Use fininstrument to create a Vanilla instrument object.

VanillaOpt = fininstrument("Vanilla",'ExerciseDate',datetime(2022,9,15),'Strike',105,'ExerciseStyle',"american",'Name',"vanilla_american_instrument")

VanillaOpt = 
  Vanilla with properties:

       OptionType: "call"
    ExerciseStyle: "american"
     ExerciseDate: 15-Sep-2022
           Strike: 105
             Name: "vanilla_american_instrument"

Create BlackScholes Model Object

Use finmodel to create a BlackScholes model object.

BlackScholesModel = finmodel("BlackScholes",'Volatility',0.07)

BlackScholesModel = 
  BlackScholes with properties:

     Volatility: 0.0700
    Correlation: 1

Create ratecurve Object

Create a flat ratecurve object using ratecurve.

Settle = datetime(2018,9,15);
myRC = ratecurve("zero",Settle,datetime(2023,9,15),.05,'Basis',12);

Create RollGeskeWhaley Pricer Object

Use finpricer to create a RollGeskeWhaley pricer object and use the ratecurve object for the 'DiscountCurve' name-value pair argument.

outPricer = finpricer("analytic",'Model',BlackScholesModel,'DiscountCurve',myRC,'SpotPrice',100,"DividendValue",timetable(datetime(2021,6,15),0.25),'PricingMethod',"RollGeskeWhaley")

outPricer = 
  RollGeskeWhaley with properties:

    DiscountCurve: [1×1 ratecurve]
            Model: [1×1 finmodel.BlackScholes]
        SpotPrice: 100
    DividendValue: [1×1 timetable]
     DividendType: "cash"

Price Vanilla Instrument

Use price to compute the price and sensitivities for the Vanilla instrument.

[Price, outPR] = price(outPricer,VanillaOpt,["all"])

Price = 
14.9582

outPR = 
  priceresult with properties:

       Results: [1×7 table]
    PricerData: []

outPR.Results

ans=1×7 table
    Price      Delta      Gamma     Lambda     Vega      Theta      Rho 
    ______    _______    _______    ______    ______    _______    _____

    14.958    0.87494    0.01471    5.8493    41.184    -3.9873    290.2

More About

Roll-Geske-Whaley Pricing Method

The Roll-Geske-Whaley pricing method offers an analytical solution for pricing American options and provides a formula that incorporates the possibility of early exercise, allowing for a more accurate valuation of American options.

Version History

Introduced in R2020a