price
Syntax
Description
[
computes the equity instrument price and related pricing information based on the pricing
object Price,PriceResult] = price(inpPricer,inpInstrument)inpPricer and the instrument object
inpInstrument.
[
adds an optional argument to specify sensitivities. Use this syntax with the input
argument combination in the previous syntax.Price,PriceResult] = price(___,inpSensitivity)
Examples
This example shows the workflow to price a fixed-strike Asian instrument when you use a RoughBergomi model and an RoughVolMonteCarlo pricing method.
Create Asian Instrument Object
Use fininstrument to create an Asian instrument object.
AsianOpt = fininstrument("Asian",'ExerciseDate',datetime(2019,1,30),'Strike',1000,'OptionType',"put",'Name',"asian_option")
AsianOpt =
Asian with properties:
OptionType: "put"
Strike: 1000
AverageType: "arithmetic"
AveragePrice: 0
AverageStartDate: NaT
ExerciseStyle: "european"
ExerciseDate: 30-Jan-2019
Name: "asian_option"
Create RoughBergomi Model Object
Use finmodel to create a RoughBergomi model object.
RoughBergomiModel = finmodel("RoughBergomi",Alpha=-0.32, Xi=0.1,Eta=0.003,RhoSV=0.9)RoughBergomiModel =
RoughBergomi with properties:
Alpha: -0.3200
Xi: 0.1000
Eta: 0.0030
RhoSV: 0.9000
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 RoughVolMonteCarlo Pricer Object
Use finpricer to create an RoughVolMonteCarlo pricer object and use the ratecurve object for the 'DiscountCurve' name-value argument.
outPricer = finpricer("RoughVolMonteCarlo",DiscountCurve=myRC,Model=RoughBergomiModel,SpotPrice=900,simulationDates=datetime(2019,1,30))outPricer =
RoughBergomiMonteCarlo with properties:
DiscountCurve: [1×1 ratecurve]
SpotPrice: 900
SimulationDates: 30-Jan-2019
NumTrials: 1000
RandomNumbers: []
Model: [1×1 finmodel.RoughBergomi]
DividendType: "continuous"
DividendValue: 0
MonteCarloMethod: "standard"
BrownianMotionMethod: "standard"
Price Asian Instrument
Use price to compute the price and sensitivities for the Asian instrument.
[Price, outPR] = price(outPricer,AsianOpt,"all")Price = 103.0639
outPR =
priceresult with properties:
Results: [1×7 table]
PricerData: [1×1 struct]
outPR.Results
ans=1×7 table
Price Delta Gamma Lambda Rho Theta Vega
______ ________ _________ _______ _______ _______ ______
103.06 -0.77793 0.0024128 -6.7932 -166.05 -1.4838 88.272
Since R2024b
This example shows the workflow to price a fixed-strike Asian instrument when you use a RoughHeston model and a RoughVolMonteCarlo pricing method.
Create Asian Instrument Object
Use fininstrument to create an Asian instrument object.
AsianOpt = fininstrument("Asian",ExerciseDate=datetime(2019,1,30),Strike=1000,OptionType="put",Name="asian_option")
AsianOpt =
Asian with properties:
OptionType: "put"
Strike: 1000
AverageType: "arithmetic"
AveragePrice: 0
AverageStartDate: NaT
ExerciseStyle: "european"
ExerciseDate: 30-Jan-2019
Name: "asian_option"
Create RoughHeston Model Object
Use finmodel to create a RoughHeston model object.
RoughHestonModel = finmodel("RoughHeston",V0=0.4,ThetaV=0.3,Kappa=0.2,SigmaV=0.1,Alpha=-0.02,RhoSV=0.3)RoughHestonModel =
RoughHeston with properties:
Alpha: -0.0200
V0: 0.4000
ThetaV: 0.3000
Kappa: 0.2000
SigmaV: 0.1000
RhoSV: 0.3000
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 RoughVolMonteCarlo Pricer Object
Use finpricer to create a RoughVolMonteCarlo pricer object and use the ratecurve object for the DiscountCurve name-value argument.
outPricer = finpricer("RoughVolMonteCarlo",DiscountCurve=myRC,Model=RoughHestonModel,SpotPrice=900,simulationDates=datetime(2019,1,30))outPricer =
RoughHestonMonteCarlo with properties:
DiscountCurve: [1×1 ratecurve]
SpotPrice: 900
SimulationDates: 30-Jan-2019
NumTrials: 1000
RandomNumbers: []
Model: [1×1 finmodel.RoughHeston]
DividendType: "continuous"
DividendValue: 0
MonteCarloMethod: "standard"
BrownianMotionMethod: "standard"
Price Asian Instrument
Use price to compute the price and sensitivities for the Asian instrument.
[Price, outPR] = price(outPricer,AsianOpt,"all")Price = 131.2194
outPR =
priceresult with properties:
Results: [1×8 table]
PricerData: [1×1 struct]
outPR.Results
ans=1×8 table
Price Delta Gamma Lambda Rho Theta Vega VegaLT
______ ________ _______ _______ ______ _______ ______ ______
131.22 -0.67246 0.00155 -4.6122 -152.4 -74.841 105.65 0
Input Arguments
Pricer object, specified as a previously created RoughVolMonteCarlo
pricer object. Create the pricer object using finpricer.
Data Types: object
Instrument object, specified as a scalar or a vector of previously created
instrument objects. Create the instrument objects using fininstrument. The following
instrument objects are supported:
Data Types: object
(Optional) List of sensitivities to compute, specified as an
NOUT-by-1 or
1-by-NOUT cell array of character vectors or
string array.
The supported sensitivities depend on the pricing method.
inpInstrument Object | Supported Sensitivities |
|---|---|
Vanilla | {'delta','gamma','vega',
'theta','rho','price','lambda'} |
Asian | {'delta','gamma','vega','theta','rho','price','lambda'} |
Cliquet | {'delta','gamma','vega','theta','rho','price','lambda}' |
Binary | {'delta','gamma','vega','theta','rho','price','lambda'} |
inpSensitivity = {'All'} or inpSensitivity =
["All"] specifies that all sensitivities for the pricing method are
returned. This is the same as specifying inpSensitivity to include
each sensitivity.
Example: inpSensitivity =
["delta","gamma","vega","lambda","rho","theta","price"]
Data Types: cell | string
Output Arguments
Instrument price, returned as a numeric.
Price result, returned as a PriceResult object. The object has
the following fields:
PriceResult.Results— Table of results that includes sensitivities (if you specifyinpSensitivity)PriceResult.PricerData— Structure for pricer data
More About
A delta sensitivity measures the rate at which the price of an option is expected to change relative to a $1 change in the price of the underlying asset.
Delta is not a static measure; it changes as the price of the underlying asset changes (a concept known as gamma sensitivity), and as time passes. Options that are near the money or have longer until expiration are more sensitive to changes in delta.
A gamma sensitivity measures the rate of change of an option's delta in response to a change in the price of the underlying asset.
In other words, while delta tells you how much the price of an option might move, gamma tells you how fast the option's delta itself will change as the price of the underlying asset moves. This is important because this helps you understand the convexity of an option's value in relation to the underlying asset's price.
A vega sensitivity measures the sensitivity of an option's price to changes in the volatility of the underlying asset.
Vega represents the amount by which the price of an option would be expected to change for a 1% change in the implied volatility of the underlying asset. Vega is expressed as the amount of money per underlying share that the option's value will gain or lose as volatility rises or falls.
A theta sensitivity measures the rate at which the price of an option decreases as time passes, all else being equal.
Theta is essentially a quantification of time decay, which is a key concept in options pricing. Theta provides an estimate of the dollar amount that an option's price would decrease each day, assuming no movement in the price of the underlying asset and no change in volatility.
A rho sensitivity measures the rate at which the price of an option is expected to change in response to a change in the risk-free interest rate.
Rho is expressed as the amount of money an option's price would gain or lose for a one percentage point (1%) change in the risk-free interest rate.
A lambda sensitivity measures the percentage change in an option's price for a 1% change in the price of the underlying asset.
Lambda is a measure of leverage, indicating how much more sensitive an option is to price movements in the underlying asset compared to owning the asset outright.
Version History
Introduced in R2024aThe price function supports pricing when using a RoughHeston model and a RoughVolMonteCarlo
pricing method.
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