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Vanilla

Vanilla instrument object

Description

Create and price a Vanilla instrument object using this workflow:

  1. Use fininstrument to create a Vanilla instrument object.

  2. Use finmodel to specify a BlackScholes, Heston, Bates, Merton, or Dupire model for the Vanilla instrument.

  3. When using a BlackScholes model, use finpricer to specify a FiniteDifference, , , BlackScholes, BjerksundStensland, RollGeskeWhaley, VannaVolga, or AssetMonteCarlo pricing method for the Vanilla instrument.

    When using a Heston, Bates, or Merton model, use finpricer to specify a FiniteDifference, NumericalIntegration, FFT, or AssetMonteCarlo pricing method for the Vanilla instrument.

    When using a Dupire model, use finpricer to specify a FiniteDifference pricing method for the Vanilla instrument.

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 models and pricing methods for a Vanilla instrument, see Choose Instruments, Models, and Pricers.

Creation

Description

example

VanillaObj = fininstrument(InstrumentType,'Strike',strike_value,'ExerciseDate',exercise_date) creates a Vanilla object by specifying InstrumentType and sets the properties for the required name-value pair arguments Strike and ExerciseDate. For more information on a Vanilla instrument, see More About.

example

VanillaObj = fininstrument(___,Name,Value) sets optional properties using additional name-value pairs in addition to the required arguments in the previous syntax. For example, VanillaObj = fininstrument("Vanilla",'Strike',100,'ExerciseDate',datetime(2019,1,30),'OptionType',"put",'ExerciseStyle',"American",'Name',"vanilla_instrument") creates a Vanilla put option with an American exercise. You can specify multiple name-value pair arguments.

Input Arguments

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

Data Types: char | string

Vanilla Name-Value Pair Arguments

Specify required and optional comma-separated pairs of Name,Value arguments. Name is the argument name and Value is the corresponding value. Name must appear inside quotes. You can specify several name and value pair arguments in any order as Name1,Value1,...,NameN,ValueN.

Example: VanillaObj = fininstrument("Vanilla",'Strike',100,'ExerciseDate',datetime(2019,1,30),'OptionType',"put",'ExerciseStyle',"American",'Name',"vanilla_instrument")
Required Vanilla Name-Value Pair Arguments

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Option strike price value, specified as the comma-separated pair consisting of 'Strike' and a scalar nonnegative numeric value.

Note

When using a "Bermudan" ExerciseStyle with a FiniteDifference pricer, the Strike is a vector.

Data Types: double

Option exercise date, specified as the comma-separated pair consisting of 'ExerciseDate' and a scalar datetime, serial date number, date character vector, or date string.

Note

For a European option, there is only one ExerciseDate on the option expiry date.

When using a "Bermudan" ExerciseStyle with a FiniteDifference pricer, the ExerciseDate is a vector.

If you use a date character vector or date string, the format must be recognizable by datetime because the ExerciseDate property is stored as a datetime.

Data Types: double | char | string | datetime

Optional Vanilla Name-Value Pair Arguments

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Option type, specified as the comma-separated pair consisting of 'OptionType' and a scalar string or character vector.

Note

When you use a RollGeskeWhaley pricer with a Vanilla option, OptionType must be 'call'.

Data Types: char | string

Option exercise style, specified as the comma-separated pair consisting of 'ExerciseStyle' and a scalar string or character vector.

Note

For more information on ExerciseStyle, see Supported Exercise Styles.

Data Types: string | char

User-defined name for the instrument, specified as the comma-separated pair consisting of 'Name' and a scalar string or character vector.

Data Types: char | string

Properties

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Option strike price value, returned as a scalar nonnegative numeric value.

Data Types: double

Option exercise date, returned as a datetime.

Data Types: datetime

Option type, returned as a string with a value of "call" or "put".

Data Types: string

Option exercise style, returned as a string with a value of "European", "American", or "Bermudan".

Data Types: string

User-defined name for the instrument, returned as a string.

Data Types: string

Object Functions

setExercisePolicySet exercise policy for FixedBondOption, FloatBondOption, or Vanilla instrument

Examples

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

Create Vanilla Instrument Object

Use fininstrument to create a Vanilla instrument object.

VanillaOpt = fininstrument("Vanilla",'ExerciseDate',datetime(2018,5,1),'Strike',29,'OptionType',"put",'ExerciseStyle',"european",'Name',"vanilla_option")
VanillaOpt = 
  Vanilla with properties:

       OptionType: "put"
    ExerciseStyle: "european"
     ExerciseDate: 01-May-2018
           Strike: 29
             Name: "vanilla_option"

Create BlackScholes Model Object

Use finmodel to create a BlackScholes model object.

BlackScholesModel = finmodel("BlackScholes",'Volatility',0.25)
BlackScholesModel = 
  BlackScholes with properties:

     Volatility: 0.2500
    Correlation: 1

Create ratecurve Object

Create a flat ratecurve object using ratecurve.

Settle = datetime(2018,1,1);
Maturity = datetime(2019,1,1);
Rate = 0.05;
myRC = ratecurve('zero',Settle,Maturity,Rate,'Basis',1)
myRC = 
  ratecurve with properties:

                 Type: "zero"
          Compounding: -1
                Basis: 1
                Dates: 01-Jan-2019
                Rates: 0.0500
               Settle: 01-Jan-2018
         InterpMethod: "linear"
    ShortExtrapMethod: "next"
     LongExtrapMethod: "previous"

Create BlackScholes Pricer Object

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

outPricer = finpricer("analytic",'DiscountCurve',myRC,'Model',BlackScholesModel,'SpotPrice',30,'DividendValue',0.045)
outPricer = 
  BlackScholes with properties:

    DiscountCurve: [1x1 ratecurve]
            Model: [1x1 finmodel.BlackScholes]
        SpotPrice: 30
    DividendValue: 0.0450
     DividendType: "continuous"

Price Vanilla Instrument

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

[Price, outPR] = price(outPricer,VanillaOpt,["all"])
Price = 1.2046
outPR = 
  priceresult with properties:

       Results: [1x7 table]
    PricerData: []

outPR.Results
ans=1×7 table
    Price      Delta       Gamma      Lambda      Vega       Rho       Theta 
    ______    ________    ________    _______    ______    _______    _______

    1.2046    -0.36943    0.086269    -9.3396    6.4702    -4.0959    -2.3107

This example shows the workflow to price an American option for a 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",'Strike',105,'ExerciseDate',datetime(2022,9,15),'OptionType',"call",'ExerciseStyle',"american",'Name',"vanilla_option")
VanillaOpt = 
  Vanilla with properties:

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

Create BlackScholes Model Object

Use finmodel to create a BlackScholes model object.

BlackScholesModel = finmodel("BlackScholes","Volatility",0.2)
BlackScholesModel = 
  BlackScholes with properties:

     Volatility: 0.2000
    Correlation: 1

Create ratecurve Object

Create a flat ratecurve object using ratecurve.

Settle = datetime(2018,9,15);
Maturity = datetime(2023,9,15);
Rate = 0.035;
myRC = ratecurve('zero',Settle,Maturity,Rate,'Basis',12)
myRC = 
  ratecurve with properties:

                 Type: "zero"
          Compounding: -1
                Basis: 12
                Dates: 15-Sep-2023
                Rates: 0.0350
               Settle: 15-Sep-2018
         InterpMethod: "linear"
    ShortExtrapMethod: "next"
     LongExtrapMethod: "previous"

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: [1x1 ratecurve]
            Model: [1x1 finmodel.BlackScholes]
        SpotPrice: 100
    DividendValue: [1x1 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 = 19.9066
outPR = 
  priceresult with properties:

       Results: [1x7 table]
    PricerData: []

outPR.Results
ans=1×7 table
    Price      Delta       Gamma      Lambda     Vega      Theta      Rho  
    ______    _______    _________    ______    ______    _______    ______

    19.907    0.66568    0.0090971    3.344     72.804    -3.4537    186.68

This example shows the workflow to price a Vanilla instrument for foreign exchange (FX) when you use a BlackScholes model and a BlackScholes pricing method. Assume that the current exchange rate is $0.52 and has a volatility of 12% per annum. The annualized continuously compounded foreign risk-free rate is 8% per annum.

Create Vanilla Instrument Object

Use fininstrument to create a Vanilla instrument object.

VanillaOpt = fininstrument("Vanilla",'ExerciseDate',datetime(2022,9,15),'Strike',.50,'OptionType',"put",'ExerciseStyle',"european",'Name',"vanilla_fx_option")
VanillaOpt = 
  Vanilla with properties:

       OptionType: "put"
    ExerciseStyle: "european"
     ExerciseDate: 15-Sep-2022
           Strike: 0.5000
             Name: "vanilla_fx_option"

Create BlackScholes Model Object

Use finmodel to create a BlackScholes model object.

Sigma = .12;
BlackScholesModel = finmodel("BlackScholes","Volatility",Sigma)
BlackScholesModel = 
  BlackScholes with properties:

     Volatility: 0.1200
    Correlation: 1

Create ratecurve Object

Create a flat ratecurve object using ratecurve.

Settle = datetime(2018,9,15);
Maturity = datetime(2023,9,15);
Rate = 0.035;
myRC = ratecurve('zero',Settle,Maturity,Rate,'Basis',12)
myRC = 
  ratecurve with properties:

                 Type: "zero"
          Compounding: -1
                Basis: 12
                Dates: 15-Sep-2023
                Rates: 0.0350
               Settle: 15-Sep-2018
         InterpMethod: "linear"
    ShortExtrapMethod: "next"
     LongExtrapMethod: "previous"

Create BlackScholes Pricer Object

Use finpricer to create a BlackScholes pricer object and use the ratecurve object for the 'DiscountCurve' name-value pair argument. When pricing currencies using a Vanilla instrument, the DividendType must be 'continuous' and DividendValue is the annualized risk-free interest rate in the foreign country.

ForeignRate = 0.08;
outPricer = finpricer("analytic",'DiscountCurve',myRC,'Model',BlackScholesModel,'SpotPrice',.52,'DividendType',"continuous",'DividendValue',ForeignRate)
outPricer = 
  BlackScholes with properties:

    DiscountCurve: [1x1 ratecurve]
            Model: [1x1 finmodel.BlackScholes]
        SpotPrice: 0.5200
    DividendValue: 0.0800
     DividendType: "continuous"

Price Vanilla FX Instrument

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

[Price, outPR] = price(outPricer,VanillaOpt,["all"])
Price = 0.0738
outPR = 
  priceresult with properties:

       Results: [1x7 table]
    PricerData: []

outPR.Results
ans=1×7 table
     Price       Delta      Gamma     Lambda      Vega        Rho        Theta  
    ________    ________    ______    _______    _______    _______    _________

    0.073778    -0.49349    2.0818    -4.7899    0.27021    -1.3216    -0.013019

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

Create Vanilla Instrument Object

Use fininstrument to create a Vanilla instrument object.

VanillaOpt = fininstrument("Vanilla",'Strike',105,'ExerciseDate',datetime(2022,9,15),'OptionType',"call",'ExerciseStyle',"american",'Name',"vanilla_option")
VanillaOpt = 
  Vanilla with properties:

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

Create BlackScholes Model Object

Use finmodel to create a BlackScholes model object.

BlackScholesModel = finmodel("BlackScholes","Volatility",0.2)
BlackScholesModel = 
  BlackScholes with properties:

     Volatility: 0.2000
    Correlation: 1

Create ratecurve Object

Create a flat ratecurve object using ratecurve.

Settle = datetime(2018,9,15);
Maturity = datetime(2023,9,15);
Rate = 0.035;
myRC = ratecurve('zero',Settle,Maturity,Rate,'Basis',12)
myRC = 
  ratecurve with properties:

                 Type: "zero"
          Compounding: -1
                Basis: 12
                Dates: 15-Sep-2023
                Rates: 0.0350
               Settle: 15-Sep-2018
         InterpMethod: "linear"
    ShortExtrapMethod: "next"
     LongExtrapMethod: "previous"

Create AssetMonteCarlo Pricer Object

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

outPricer = finpricer("AssetMonteCarlo",'DiscountCurve',myRC,"Model",BlackScholesModel,'SpotPrice',150,'simulationDates',datetime(2022,9,15))
outPricer = 
  GBMMonteCarlo with properties:

      DiscountCurve: [1x1 ratecurve]
          SpotPrice: 150
    SimulationDates: 15-Sep-2022
          NumTrials: 1000
      RandomNumbers: []
              Model: [1x1 finmodel.BlackScholes]
       DividendType: "continuous"
      DividendValue: 0

Price Vanilla Instrument

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

[Price, outPR] = price(outPricer,VanillaOpt,["all"])
Price = 61.2010
outPR = 
  priceresult with properties:

       Results: [1x7 table]
    PricerData: [1x1 struct]

outPR.Results
ans=1×7 table
    Price      Delta       Gamma      Lambda     Rho       Theta      Vega 
    ______    _______    _________    ______    ______    _______    ______

    61.201    0.93074    0.0027813    2.2812    313.95    -3.7909    41.626

This example shows the workflow to price an American option for a Vanilla instrument when you use a Heston model and an AssetMonteCarlo pricing method.

Create Vanilla Instrument Object

Use fininstrument to create a Vanilla instrument object.

VanillaOpt = fininstrument("Vanilla",'Strike',105,'ExerciseDate',datetime(2022,9,15),'OptionType',"call",'ExerciseStyle',"american",'Name',"vanilla_option")
VanillaOpt = 
  Vanilla with properties:

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

Create Heston Model Object

Use finmodel to create a Heston model object.

HestonModel = finmodel("Heston",'V0',0.032,'ThetaV',0.07,'Kappa',0.003,'SigmaV',0.02,'RhoSV',0.09)
HestonModel = 
  Heston with properties:

        V0: 0.0320
    ThetaV: 0.0700
     Kappa: 0.0030
    SigmaV: 0.0200
     RhoSV: 0.0900

Create ratecurve Object

Create a flat ratecurve object using ratecurve.

Settle = datetime(2018,9,15);
Maturity = datetime(2023,9,15);
Rate = 0.035;
myRC = ratecurve('zero',Settle,Maturity,Rate,'Basis',12)
myRC = 
  ratecurve with properties:

                 Type: "zero"
          Compounding: -1
                Basis: 12
                Dates: 15-Sep-2023
                Rates: 0.0350
               Settle: 15-Sep-2018
         InterpMethod: "linear"
    ShortExtrapMethod: "next"
     LongExtrapMethod: "previous"

Create AssetMonteCarlo Pricer Object

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

outPricer = finpricer("AssetMonteCarlo",'DiscountCurve',myRC,"Model",HestonModel,'SpotPrice',150,'simulationDates',datetime(2022,9,15))
outPricer = 
  HestonMonteCarlo with properties:

      DiscountCurve: [1x1 ratecurve]
          SpotPrice: 150
    SimulationDates: 15-Sep-2022
          NumTrials: 1000
      RandomNumbers: []
              Model: [1x1 finmodel.Heston]
       DividendType: "continuous"
      DividendValue: 0

Price Vanilla Instrument

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

[Price, outPR] = price(outPricer,VanillaOpt,["all"])
Price = 60.5637
outPR = 
  priceresult with properties:

       Results: [1x8 table]
    PricerData: [1x1 struct]

outPR.Results
ans=1×8 table
    Price      Delta       Gamma      Lambda     Rho       Theta      Vega     VegaLT 
    ______    _______    _________    ______    ______    _______    ______    _______

    60.564    0.94774    0.0011954    2.3473    326.36    -3.7126    35.272    0.31155

This example shows the workflow to price a Bermudan option for a Vanilla instrument when you use a BlackScholes model and a FiniteDifference pricing method.

Create Vanilla Instrument Object

Use fininstrument to create a Vanilla instrument object.

VanillaOpt = fininstrument("Vanilla",'Strike',[110,120],'ExerciseDate',[datetime(2022,9,15) ; datetime(2023,9,15)],'OptionType',"call",'ExerciseStyle',"Bermudan",'Name',"vanilla_option")
VanillaOpt = 
  Vanilla with properties:

       OptionType: "call"
    ExerciseStyle: "bermudan"
     ExerciseDate: [15-Sep-2022    15-Sep-2023]
           Strike: [110 120]
             Name: "vanilla_option"

Create BlackScholes Model Object

Use finmodel to create a BlackScholes model object.

BlackScholesModel = finmodel("BlackScholes","Volatility",0.2)
BlackScholesModel = 
  BlackScholes with properties:

     Volatility: 0.2000
    Correlation: 1

Create ratecurve Object

Create a flat ratecurve object using ratecurve.

Settle = datetime(2018,9,15);
Maturity = datetime(2023,9,15);
Rate = 0.035;
myRC = ratecurve('zero',Settle,Maturity,Rate,'Basis',12)
myRC = 
  ratecurve with properties:

                 Type: "zero"
          Compounding: -1
                Basis: 12
                Dates: 15-Sep-2023
                Rates: 0.0350
               Settle: 15-Sep-2018
         InterpMethod: "linear"
    ShortExtrapMethod: "next"
     LongExtrapMethod: "previous"

Create FiniteDifference Pricer Object

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

outPricer = finpricer("FiniteDifference",'Model',BlackScholesModel,'DiscountCurve',myRC,'SpotPrice',100)
outPricer = 
  FiniteDifference with properties:

     DiscountCurve: [1x1 ratecurve]
             Model: [1x1 finmodel.BlackScholes]
         SpotPrice: 100
    GridProperties: [1x1 struct]
      DividendType: "continuous"
     DividendValue: 0

Price Vanilla Instrument

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

[Price, outPR] = price(outPricer,VanillaOpt,["all"])
Price = 17.3930
outPR = 
  priceresult with properties:

       Results: [1x7 table]
    PricerData: [1x1 struct]

outPR.Results
ans=1×7 table
    Price      Delta      Gamma      Lambda     Theta      Rho       Vega 
    ______    _______    ________    ______    _______    ______    ______

    17.393    0.58203    0.008905    3.3463    -3.1757    203.94    87.324

This example shows the workflow to price a Vanilla instrument when you use a Heston model and various pricing methods.

Create Vanilla Instrument Object

Use fininstrument to create a Vanilla instrument object.

Settle = datetime(2017,6,29);
Maturity = datemnth(Settle,6);
Strike = 80;
VanillaOpt = fininstrument('Vanilla','ExerciseDate',Maturity,'Strike',Strike,'Name',"vanilla_option")
VanillaOpt = 
  Vanilla with properties:

       OptionType: "call"
    ExerciseStyle: "european"
     ExerciseDate: 29-Dec-2017
           Strike: 80
             Name: "vanilla_option"

Create Heston Model Object

Use finmodel to create a Heston model object.

V0 = 0.04;
ThetaV = 0.05;
Kappa = 1.0;
SigmaV = 0.2;
RhoSV = -0.7;

HestonModel = finmodel("Heston",'V0',V0,'ThetaV',ThetaV,'Kappa',Kappa,'SigmaV',SigmaV,'RhoSV',RhoSV)
HestonModel = 
  Heston with properties:

        V0: 0.0400
    ThetaV: 0.0500
     Kappa: 1
    SigmaV: 0.2000
     RhoSV: -0.7000

Create ratecurve object

Create a ratecurve object using ratecurve.

Rate = 0.03;
ZeroCurve = ratecurve('zero',Settle,Maturity,Rate);

Create NumericalIntegration, FFT, and FiniteDifference Pricer Objects

Use finpricer to create a NumericalIntegration, FFT, and FiniteDifference pricer objects and use the ratecurve object for the 'DiscountCurve' name-value pair argument.

SpotPrice = 80;
Strike = 80;
DividendYield = 0.02;

NIPricer = finpricer("NumericalIntegration",'Model', HestonModel,'SpotPrice',SpotPrice,'DiscountCurve',ZeroCurve,'DividendValue',DividendYield)
NIPricer = 
  NumericalIntegration with properties:

                Model: [1x1 finmodel.Heston]
        DiscountCurve: [1x1 ratecurve]
            SpotPrice: 80
         DividendType: "continuous"
        DividendValue: 0.0200
               AbsTol: 1.0000e-10
               RelTol: 1.0000e-10
     IntegrationRange: [1.0000e-09 Inf]
    CharacteristicFcn: @characteristicFcnHeston
            Framework: "heston1993"
       VolRiskPremium: 0
           LittleTrap: 1

FFTPricer = finpricer("FFT",'Model',HestonModel, ...
    'SpotPrice',SpotPrice,'DiscountCurve',ZeroCurve, ...
    'DividendValue',DividendYield,'NumFFT',8192)
FFTPricer = 
  FFT with properties:

                    Model: [1x1 finmodel.Heston]
            DiscountCurve: [1x1 ratecurve]
                SpotPrice: 80
             DividendType: "continuous"
            DividendValue: 0.0200
                   NumFFT: 8192
    CharacteristicFcnStep: 0.0100
            LogStrikeStep: 0.0767
        CharacteristicFcn: @characteristicFcnHeston
            DampingFactor: 1.5000
               Quadrature: "simpson"
           VolRiskPremium: 0
               LittleTrap: 1

FDPricer = finpricer("FiniteDifference",'Model',HestonModel,'SpotPrice',SpotPrice,'DiscountCurve',ZeroCurve,'DividendValue',DividendYield)
FDPricer = 
  FiniteDifference with properties:

     DiscountCurve: [1x1 ratecurve]
             Model: [1x1 finmodel.Heston]
         SpotPrice: 80
    GridProperties: [1x1 struct]
      DividendType: "continuous"
     DividendValue: 0.0200

Price Vanilla Instrument

Use the following sensitivities when pricing the Vanilla instrument.

InpSensitivity = ["delta", "gamma", "theta", "rho", "vega", "vegalt"];

Use price to compute the price and sensitivities for the Vanilla instrument that uses the NumericalIntegration pricer.

[PriceNI,  outPR_NI]  = price(NIPricer,VanillaOpt,InpSensitivity)
PriceNI = 4.7007
outPR_NI = 
  priceresult with properties:

       Results: [1x7 table]
    PricerData: []

Use price to compute the price and sensitivities for the Vanilla instrument that uses the FFT pricer.

[PriceFFT, outPR_FFT] = price(FFTPricer,VanillaOpt,InpSensitivity)
PriceFFT = 4.7007
outPR_FFT = 
  priceresult with properties:

       Results: [1x7 table]
    PricerData: []

Use price to compute the price and sensitivities for the Vanilla instrument that uses the FiniteDifference pricer.

[PriceFD,  outPR_FD]  = price(FDPricer,VanillaOpt,InpSensitivity)
PriceFD = 4.7003
outPR_FD = 
  priceresult with properties:

       Results: [1x7 table]
    PricerData: [1x1 struct]

Aggregate the price results.

[outPR_NI.Results;outPR_FFT.Results;outPR_FD.Results]
ans=3×7 table
    Price      Delta      Gamma       Theta      Rho       Vega     VegaLT
    ______    _______    ________    _______    ______    ______    ______

    4.7007    0.57747     0.03392    -4.8474    20.805    17.028    5.2394
    4.7007    0.57747     0.03392    -4.8474    20.805    17.028    5.2394
    4.7003    0.57722    0.035254    -4.8483    20.801    17.046    5.2422

Compute Option Price Surfaces

Use the price function for the NumericalIntegration pricer and the price function for the FFT pricer to compute the prices for a range of Vanilla instruments.

Maturities = datemnth(Settle,(3:3:24)');
NumMaturities = length(Maturities);
Strikes = (20:10:160)';
NumStrikes = length(Strikes);

[Maturities_Full,Strikes_Full] = meshgrid(Maturities,Strikes);

NumInst = numel(Strikes_Full);
VanillaOptions(NumInst, 1) = fininstrument("vanilla",...
    "ExerciseDate", Maturities_Full(1), "Strike", Strikes_Full(1));
for instidx=1:NumInst
    VanillaOptions(instidx) = fininstrument("vanilla",...
        "ExerciseDate", Maturities_Full(instidx), "Strike", Strikes_Full(instidx));
end

Prices_NI = price(NIPricer, VanillaOptions);
Prices_FFT = price(FFTPricer, VanillaOptions);

figure;
surf(Maturities_Full,Strikes_Full,reshape(Prices_NI,[NumStrikes,NumMaturities]));
title('Price (Numerical Integration)');
view(-112,34);
xlabel('Maturity')
ylabel('Strike')

figure;
surf(Maturities_Full,Strikes_Full,reshape(Prices_FFT,[NumStrikes,NumMaturities]));
title('Price (FFT)');
view(-112,34);
xlabel('Maturity')
ylabel('Strike')

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Tips

After creating a Vanilla instrument object, you can use setExercisePolicy to change the size of the options. For example, if you have the following instrument:

VanillaOpt = fininstrument("Vanilla",'ExerciseDate',datetime(2021,5,1),'Strike',29,'OptionType',"put",'ExerciseStyle',"European")
To modify the Vanilla instrument's size by changing the ExerciseStyle from "European" to "American", use setExercisePolicy:
VanillaOpt = setExercisePolicy(VanillaOpt,[datetime(2021,1,1) datetime(2022,1,1)],100,'American')

Introduced in R2020a