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optSensByLocalVolFD

Option price and sensitivities by local volatility model, using finite differences

Description

[PriceSens,PriceGrid,AssetPrices,Times] = optSensByLocalVolFD(Rate,AssetPrice,Settle,ExerciseDates,OptSpec,Strike,ImpliedVolData) compute option price and sensitivities by the local volatility model, using the Crank-Nicolson method.

Note

Alternatively, you can use the Vanilla object to calculate price or sensitivities for vanilla options. For more information, see Get Started with Workflows Using Object-Based Framework for Pricing Financial Instruments.

example

[PriceSens,PriceGrid,AssetPrices,Times] = optSensByLocalVolFD(___,Name,Value) specifies options using one or more name-value pair arguments in addition to the input arguments in the previous syntax.

example

Examples

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Define the option variables.

AssetPrice = 590;
Strike = 590;
Rate = 0.06;
DividendYield = 0.0262;
Settle = datetime(2018,1,1);
ExerciseDates = datetime(2020,1,1);

Define the implied volatility surface data.

Maturity = [datetime(2018,3,6) datetime(2018,6,5) datetime(2018,9,12) datetime(2018,12,10) datetime(2019,1,1) datetime(2019,7,2) datetime(2020,1,1) datetime(2021,1,1) datetime(2022,1,1) datetime(2023,1,1)];
Maturity = repmat(Maturity,10,1);
Maturity = Maturity(:);

ExercisePrice = AssetPrice.*[0.85 0.90 0.95 1.00 1.05 1.10 1.15 1.20 1.30 1.40];
ExercisePrice = repmat(ExercisePrice,1,10)';

ImpliedVol = [...
    0.190; 0.168; 0.133; 0.113; 0.102; 0.097; 0.120; 0.142; 0.169; 0.200; ...
    0.177; 0.155; 0.138; 0.125; 0.109; 0.103; 0.100; 0.114; 0.130; 0.150; ...
    0.172; 0.157; 0.144; 0.133; 0.118; 0.104; 0.100; 0.101; 0.108; 0.124; ...
    0.171; 0.159; 0.149; 0.137; 0.127; 0.113; 0.106; 0.103; 0.100; 0.110; ...
    0.171; 0.159; 0.150; 0.138; 0.128; 0.115; 0.107; 0.103; 0.099; 0.108; ...
    0.169; 0.160; 0.151; 0.142; 0.133; 0.124; 0.119; 0.113; 0.107; 0.102; ...
    0.169; 0.161; 0.153; 0.145; 0.137; 0.130; 0.126; 0.119; 0.115; 0.111; ...
    0.168; 0.161; 0.155; 0.149; 0.143; 0.137; 0.133; 0.128; 0.124; 0.123; ...
    0.168; 0.162; 0.157; 0.152; 0.148; 0.143; 0.139; 0.135; 0.130; 0.128; ...
    0.168; 0.164; 0.159; 0.154; 0.151; 0.147; 0.144; 0.140; 0.136; 0.132];

ImpliedVolData = table(Maturity, ExercisePrice, ImpliedVol);

Compute the European call option price and sensitivities.

OptSpec = 'Call';
[Delta,Gamma,Lambda,Theta,Price]  = optSensByLocalVolFD(Rate, AssetPrice, ...
Settle, ExerciseDates, OptSpec, Strike, ImpliedVolData, 'DividendYield',DividendYield, ...
'OutSpec',["Delta" "Gamma" "Lambda" "Theta" "Price"])
Delta = 
0.5519
Gamma = 
0.0091
Lambda = 
4.9994
Theta = 
-20.9529
Price = 
65.1319

Input Arguments

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Continuously compounded risk-free interest rate, specified by a scalar numeric.

Data Types: double

Current underlying asset price, specified as a scalar numeric.

Data Types: double

Settlement date, specified as a scalar datetime, string, or date character vector.

To support existing code, optSensByLocalVolFD also accepts serial date numbers as inputs, but they are not recommended.

Option exercise dates, specified as a datetime array, string array, or date character vectors:

  • For a European option, there is only one ExerciseDates value and this is the option expiry date.

  • For an American option, use a 1-by-2 vector dates. The American option can be exercised on any date between or including the pair of dates. If only one non-NaN date is listed, the option can be exercised between Settle and the single listed date in ExerciseDates.

To support existing code, optSensByLocalVolFD also accepts serial date numbers as inputs, but they are not recommended.

Definition of the option, specified as a character vector or string array with a value of 'call' or 'put'.

Data Types: char | string

Option strike price value, specified as a nonnegative scalar.

Data Types: double

A table of maturity dates, strike or exercise prices, and their corresponding implied volatilities,specified as a NVOL-by-3 table.

Data Types: table

Name-Value Arguments

Specify 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: PriceSens = Price = optByLocalVolFD(Rate,AssetPrice,Settle, ExerciseDates,OptSpec,Strike,ImpliedVolData,'AssetGridSize',1000,'OutSpec',{'delta','gamma','vega','lambda','rho','theta','price'})

Day-count basis, specified as the comma-separated pair consisting of 'Basis' and a scalar using one of these supported values:

  • 0 = actual/actual

  • 1 = 30/360 (SIA)

  • 2 = actual/360

  • 3 = actual/365

  • 4 = 30/360 (PSA)

  • 5 = 30/360 (ISDA)

  • 6 = 30/360 (European)

  • 7 = actual/365 (Japanese)

  • 8 = actual/actual (ICMA)

  • 9 = actual/360 (ICMA)

  • 10 = actual/365 (ICMA)

  • 11 = 30/360E (ICMA)

  • 12 = actual/365 (ISDA)

  • 13 = BUS/252

For more information, see Basis.

Data Types: double

Continuously compounded underlying asset yield, specified as the comma-separated pair consisting of 'DividendYield' and a scalar numeric.

Note

If you enter a value for DividendYield, then set DividendAmounts and ExDividendDates = [ ] or do not enter them. If you enter values for DividendAmounts and ExDividendDates, then set DividendYield = 0.

Data Types: double

Cash dividend amounts, specified as the comma-separated pair consisting of 'DividendAmounts' and a NDIV-by-1 vector.

For each dividend amount, there must be a corresponding ExDividendDates date. If you enter values for DividendAmounts and ExDividendDates, then set DividendYield = 0.

Note

If you enter a value for DividendYield, then set DividendAmounts and ExDividendDates = [ ] or do not enter them.

Data Types: double

Ex-dividend dates, specified as the comma-separated pair consisting of 'ExDividendDates' and a NDIV-by-1 vector using a datetime array, string array, or date character vectors.

To support existing code, optSensByLocalVolFD also accepts serial date numbers as inputs, but they are not recommended.

Maximum price for price grid boundary, specified as the comma-separated pair consisting of 'AssetPriceMax' and a positive scalar.

Data Types: double

Size of the asset grid for finite difference grid, specified as the comma-separated pair consisting of 'AssetGridSize' and a positive scalar.

Data Types: double

Size of the time grid for finite difference grid, specified as the comma-separated pair consisting of 'TimeGridSize' and a positive scalar.

Data Types: double

Option type, specified as the comma-separated pair consisting of 'AmericanOpt' and a positive integer scalar flag with one of these values:

  • 0 — European

  • 1 — American

Data Types: double

Method of interpolation for estimating the implied volatility surface from ImpliedVolData, specified as the comma-separated pair consisting of 'InterpMethod' and a character vector or string with one of the following values:

  • 'linear' — Linear interpolation

  • 'makima' — Modified Akima cubic Hermite interpolation

  • 'spline' — Cubic spline interpolation

  • 'tpaps' — Thin-plate smoothing spline interpolation

Note

The 'tpaps' method uses the thin-plate smoothing spline functionality from Curve Fitting Toolbox™.

The 'makima' and 'spline' methods work only for gridded data. For scattered data, use the 'linear' or 'tpaps' methods.

For more information on gridded or scattered data and details on interpolation methods, see Gridded and Scattered Sample Data and Interpolating Gridded Data.

Data Types: char | string

Define outputs, specified as the comma-separated pair consisting of 'OutSpec' and an NOUT- by-1 or a 1-by-NOUT cell array of character vectors with possible values of 'price', 'delta', 'gamma', 'vega', 'lambda', 'rho', and 'theta'.

Example: OutSpec = {'delta','gamma','vega','lambda','rho','theta','price'}

Data Types: cell | string

Output Arguments

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Option price and sensitivities, returned as a scalar numeric. OutSpec determines the types and order of the output.

Grid containing prices calculated by the finite difference method, returned as a grid that is two-dimensional with size AssetGridSizeTimeGridSize. The number of columns does not have to be equal to the TimeGridSize, because ExerciseDates and ExDividendDates are added to the time grid. PriceGrid(:, :, end) contains the price for t = 0.

Prices of the asset corresponding to the first dimension of PriceGrid, returned as a vector.

Times corresponding to second dimension of the PriceGrid, returned as a vector.

More About

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Vanilla Option

A vanilla option is a category of options that includes only the most standard components.

A vanilla option has an expiration date and straightforward strike price. American-style options and European-style options are both categorized as vanilla options.

The payoff for a vanilla option is as follows:

  • For a call: max(StK,0)

  • For a put: max(KSt,0)

where:

St is the price of the underlying asset at time t.

K is the strike price.

For more information, see Vanilla Option.

Local Volatility Model

A local volatility model treats volatility as a function both of the current asset level and of time.

The local volatility can be estimated by using the Dupire formula [2]:

σloc2(K,τ)=σimp2+2τσimpσimpτ+2(τd)KτσimpσimpK(1+Kd1τσimpK)2+K2τσimp(2σimpK2d1τ(σimpK)2)d1=ln(S0/K)+((τd)+σimp2/2)τσimpτ

References

[1] Andersen, L. B., and R. Brotherton-Ratcliffe. "The Equity Option Volatility Smile: An Implicit Finite-Difference Approach." Journal of Computational Finance. Vol. 1, Number 2, 1997, pp. 5–37.

[2] Dupire, B. "Pricing with a Smile." Risk. Vol. 7, Number 1, 1994, pp. 18–20.

Version History

Introduced in R2018b

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