price
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
Use FiniteDifference
Pricer and BlackScholes
Model to Price Barrier
Instrument
This example shows the workflow to price a Barrier
instrument when you use a BlackScholes
model and a FiniteDifference
pricing method.
Create Barrier
Instrument Object
Use fininstrument
to create a Barrier
instrument object.
BarrierOpt = fininstrument("Barrier",'Strike',105,'ExerciseDate',datetime(2019,1,1),'OptionType',"call",'ExerciseStyle',"american",'BarrierType',"DO",'BarrierValue',40,'Name',"barrier_option")
BarrierOpt = Barrier with properties: OptionType: "call" Strike: 105 BarrierType: "do" BarrierValue: 40 Rebate: 0 ExerciseStyle: "american" ExerciseDate: 01-Jan-2019 Name: "barrier_option"
Create BlackScholes
Model Object
Use finmodel
to create a BlackScholes
model object.
BlackScholesModel = finmodel("BlackScholes",'Volatility',0.30)
BlackScholesModel = BlackScholes with properties: Volatility: 0.3000 Correlation: 1
Create ratecurve
Object
Create a flat ratecurve
object using ratecurve
.
Settle = datetime(2018,1,1); Maturity = datetime(2023,1,1); Rate = 0.035; myRC = ratecurve('zero',Settle,Maturity,Rate,'Basis',1)
myRC = ratecurve with properties: Type: "zero" Compounding: -1 Basis: 1 Dates: 01-Jan-2023 Rates: 0.0350 Settle: 01-Jan-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 Barrier
Instrument
Use price
to compute the price and sensitivities for the Barrier
instrument.
[Price, outPR] = price(outPricer,BarrierOpt,["all"])
Price = 11.3230
outPR = priceresult with properties: Results: [1x7 table] PricerData: [1x1 struct]
outPR.Results
ans=1×7 table
Price Delta Gamma Lambda Theta Rho Vega
______ _______ ______ ______ _______ ______ ______
11.323 0.54126 0.0132 4.7802 -7.4408 42.766 39.627
Input Arguments
inpPricer
— Pricer object
FiniteDifference
object
Pricer object, specified as a scalar FiniteDifference
pricer object. Use finpricer
to create the FiniteDifference
pricer object.
Data Types: object
inpInstrument
— Instrument object
Vanilla
object | Barrier
object | DoubleBarrier
object | ConvertibleBond
object
Instrument object, specified as a scalar or vector of Vanilla
, Barrier
, DoubleBarrier
, or
ConvertibleBond
instrument objects. Use fininstrument
to create the
Vanilla
, Barrier
, DoubleBarrier
, or
ConvertibleBond
instrument objects.
Data Types: object
inpSensitivity
— List of sensitivities to compute
[ ]
(default) | string array with values "Price"
, "Delta"
,
"Gamma"
, "Vega"
, "Rho"
,
"Theta"
, "Lambda"
, "Vegalt"
,
and "All"
| cell array of character vectors with values 'Price'
,
'Delta'
, 'Gamma'
, 'Lambda'
,
'Vegalt'
, 'Vega'
, 'Rho'
,
'Theta'
, and 'All'
(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'
, 'Vegalt'
,
'Lambda'
, 'Rho'
, 'Theta'
, and
'Price'
. This is the same as specifying
inpSensitivity
to include each sensitivity.
Note
When you price a Barrier
or ConvertibleBond
instruments using a BlackScholes
model,
'Vegalt'
is not supported.
Example: inpSensitivity =
{'delta','gamma','vega','vegalt','rho','lambda','theta','price'}
The sensitivities supported depend on the
inpInstrument
.
inpInstrument | Supported Sensitivities |
---|---|
Vanilla , | 'delta','gamma','vega','vegalt','rho','lambda','theta','price' |
Barrier | 'delta','gamma','vega','rho','lambda','theta','price' |
DoubleBarrier | 'delta','gamma','vega','vegalt','rho','lambda','theta','price' |
ConvertibleBond | 'delta','gamma','vega','rho','lambda','theta','price' |
Data Types: string
| cell
Output Arguments
Price
— Instrument price
numeric
Instrument price, returned as a numeric.
PriceResult
— Price result
PriceResult
object
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
Delta
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.
Gamma
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.
Vega
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.
Theta
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.
Rho
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.
Lambda
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 R2020a
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