price
Compute price for equity instrument with VannaVolga
pricer
Syntax
Description
[
computes the 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.Price,PriceResult] = price(___,inpSensitivity)
Examples
This example shows the workflow to price a DoubleBarrier instrument when you use a BlackScholes model and a VannaVolga pricing method.
Create DoubleBarrier Instrument Object
Use fininstrument to create a DoubleBarrier instrument object.
DoubleBarrierOpt = fininstrument("DoubleBarrier",'Strike',100,'ExerciseDate',datetime(2020,8,15),'OptionType',"call",'ExerciseStyle',"European",'BarrierType',"DKO",'BarrierValue',[110 80],'Name',"doublebarrier_option")
DoubleBarrierOpt =
DoubleBarrier with properties:
OptionType: "call"
Strike: 100
BarrierValue: [110 80]
ExerciseStyle: "european"
ExerciseDate: 15-Aug-2020
BarrierType: "dko"
Rebate: [0 0]
Name: "doublebarrier_option"
Create BlackScholes Model Object
Use finmodel to create a BlackScholes model object.
BlackScholesModel = finmodel("BlackScholes","Volatility",0.02)
BlackScholesModel =
BlackScholes with properties:
Volatility: 0.0200
Correlation: 1
Create ratecurve Object
Create a flat ratecurve object using ratecurve.
Settle = datetime(2019,9,15); 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-2019
InterpMethod: "linear"
ShortExtrapMethod: "next"
LongExtrapMethod: "previous"
Create VannaVolga Pricer Object
Use finpricer to create a VannaVolga pricer object and use the ratecurve object for the 'DiscountCurve' name-value pair argument.
VolRR = -0.0045; VolBF = 0.0037; RateF = 0.0210; outPricer = finpricer("VannaVolga","DiscountCurve",myRC,"Model",BlackScholesModel,'SpotPrice',100,'DividendValue',RateF,'VolatilityRR',VolRR,'VolatilityBF',VolBF)
outPricer =
VannaVolga with properties:
DiscountCurve: [1×1 ratecurve]
Model: [1×1 finmodel.BlackScholes]
SpotPrice: 100
DividendType: "continuous"
DividendValue: 0.0210
VolatilityRR: -0.0045
VolatilityBF: 0.0037
Price DoubleBarrier Instrument
Use price to compute the price and sensitivities for the DoubleBarrier instrument.
[Price, outPR] = price(outPricer,DoubleBarrierOpt,["all"])Price = 1.6450
outPR =
priceresult with properties:
Results: [1×7 table]
PricerData: [1×1 struct]
outPR.Results
ans=1×7 table
Price Delta Gamma Lambda Vega Theta Rho
_____ _______ ______ ______ ______ _______ ______
1.645 0.82818 75.662 50.346 14.697 -1.3145 74.666
Input Arguments
Pricer object, specified as a scalar VannaVolga pricer object.
Use finpricer to create the VannaVolga pricer
object.
Data Types: object
Instrument object, specified as a scalar or vector of Vanilla, Barrier, DoubleBarrier,
Touch, or DoubleTouch
instrument objects. Use fininstrument to create the
Vanilla, Barrier, DoubleBarrier,
Touch, or DoubleTouch
instrument objects.
Data Types: object
(Optional) List of sensitivities to compute, specified as a
NOUT-by-1 or a
1-by-NOUT cell array of character vectors or
string array with supported values.
inpSensitivity = {'All'} or inpSensitivity =
["All"] specifies that the output is 'Delta',
'Gamma', 'Vega', 'Lambda',
'Rho', 'Theta', and 'Price'.
This is the same as specifying inpSensitivity to include each
sensitivity.
Example: inpSensitivity =
{'delta','gamma','vega','rho','lambda','theta','price'}
The sensitivities supported depend on the
inpInstrument.
| inpInstrument | Supported Sensitivities |
|---|---|
Vanilla, | 'delta','gamma','vega','rho','lambda','theta','price' |
Barrier | 'delta','gamma','vega','rho','lambda','theta','price' |
DoubleBarrier | 'delta','gamma','vega','rho','lambda','theta','price' |
Touch | 'delta','gamma','vega','rho','lambda','theta','price' |
DoubleTouch | 'delta','gamma','vega','rho','lambda','theta','price' |
Data Types: string | cell
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 dataPriceResult.PricerData.Overhedge— TBD
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 R2020b
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