optSensByBatesFD

Option price and sensitivities by Bates model using finite differences

Since R2019a

Syntax

``[PriceSens,PriceGrid,AssetPrices,Variances,Times] = optSensByBatesFD(Rate,AssetPrice,Settle,ExerciseDates,OptSpec,Strike,V0,ThetaV,Kappa,SigmaV,RhoSV,MeanJ,JumpVol,JumpFreq)``
``[PriceSens,PriceGrid,AssetPrices,Variances,Times] = optSensByBatesFD(___,Name,Value)``

Description

example

````[PriceSens,PriceGrid,AssetPrices,Variances,Times] = optSensByBatesFD(Rate,AssetPrice,Settle,ExerciseDates,OptSpec,Strike,V0,ThetaV,Kappa,SigmaV,RhoSV,MeanJ,JumpVol,JumpFreq)` computes a vanilla European or American option price and sensitivities by the Bates model, using the alternating direction implicit (ADI) method. NoteAlternatively, 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,Variances,Times] = optSensByBatesFD(___,Name,Value)` specifies options using one or more name-value pair arguments in addition to the input arguments in the previous syntax. ```

Examples

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Define the option variables and Bates model parameters.

```AssetPrice = 90; Strike = 100; Rate = 0.03; Settle = datetime(2018,1,1); ExerciseDates = datetime(2018,6,2); V0 = 0.04; ThetaV = 0.04; Kappa = 2; SigmaV = 0.25; RhoSV = -0.5; JumpVol = 0.4; MeanJ = exp(-0.5+JumpVol.^2/2)-1; JumpFreq = 0.2;```

Compute the American put option price and sensitivities using the finite differences method.

```OptSpec = 'Put'; [Price, Delta, Gamma, Rho, Theta, Vega, VegaLT] = optSensByBatesFD(Rate, AssetPrice, Settle, ExerciseDates,... OptSpec, Strike, V0, ThetaV, Kappa, SigmaV, RhoSV, MeanJ, JumpVol, JumpFreq, 'AmericanOpt', 1,... 'OutSpec', ["Price" "Delta" "Gamma" "Rho" "Theta" "Vega" "VegaLT"])```
```Price = 11.2164 ```
```Delta = -0.6988 ```
```Gamma = 0.0391 ```
```Rho = -17.1376 ```
```Theta = -4.7656 ```
```Vega = 13.3283 ```
```VegaLT = 6.1456 ```

Input Arguments

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Continuously compounded risk-free interest rate, specified as a scalar decimal.

Data Types: `double`

Current underlying asset price, specified as a scalar numeric.

Data Types: `double`

Option settlement date, specified as a scalar datetime, string, or data character vector.

To support existing code, `optSensByBatesFD` 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, use a scalar date. For a European option, `ExerciseDates` contains only one value: the option expiry date.

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

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

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

Data Types: `cell` | `string`

Option strike price value, specified as a scalar numeric.

Data Types: `double`

Initial variance of the underling asset, specified as a scalar numeric.

Data Types: `double`

Long-term variance of the underling asset, specified as a scalar numeric.

Data Types: `double`

Mean revision speed for the underlying asset, specified as a scalar numeric.

Data Types: `double`

Volatility of the variance of the underling asset, specified as a scalar numeric.

Data Types: `double`

Correlation between the Weiner processes for the underlying asset and its variance, specified as a scalar numeric.

Data Types: `double`

Mean of the random percentage jump size (J), specified as a scalar decimal where `log`(1+J) is normally distributed with the mean (`log`(1+`MeanJ`)-0.5*`JumpVol`^2) and the standard deviation `JumpVol`.

Data Types: `double`

Standard deviation of `log`(1+J) where `J` is the random percentage jump size, specified as a scalar decimal.

Data Types: `double`

Annual frequency of the Poisson jump process, specified as a scalar numeric.

Data Types: `double`

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,PriceGrid] = optSensByBatesFD(Rate,AssetPrice,Settle,ExerciseDates,OptSpec,Strike,V0,ThetaV,Kappa,SigmaV,RhoSV,MeanJ,JumpVol,JumpFreq,'Basis',7,'OutSpec','delta')```

Day-count basis of the instrument, specified as the comma-separated pair consisting of `'Basis'` and a scalar using a supported value:

• 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

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 an `NDIV`-by-`1` vector.

Note

Each dividend amount must have a corresponding ex-dividend date. If you enter values for `DividendAmounts` and `ExDividendDates`, then set `DividendYield` = `0`.

Data Types: `double`

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

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

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

Data Types: `double`

Maximum variance for the variance grid boundary, specified as the comma-separated pair consisting of `'VarianceMax'` as a scalar numeric.

Data Types: `double`

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

Data Types: `double`

Number of nodes of the variance grid for the finite difference grid, specified as the comma-separated pair consisting of `'VarianceGridSize'` and a scalar numeric.

Data Types: `double`

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

Data Types: `double`

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

• `0` — European

• `1` — American

Data Types: `double`

Define outputs, specified as the comma-separated pair consisting of `'OutSpec'` and a `NOUT`- by-`1` or a `1`-by-`NOUT` string array or cell array of character vectors with supported values.

Note

`'vega'` is the sensitivity with respect to the initial volatility sqrt(`V0`). In contrast, `'vegalt'` is the sensitivity with respect to the long-term volatility sqrt(`ThetaV`).

Example: ```OutSpec = ['price','delta','gamma','vega','rho','theta','vegalt']```

Data Types: `string` | `cell`

Output Arguments

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Option price or sensitivities, returned as a numeric. The name-value pair argument `OutSpec` determines the types and order of the outputs.

Grid containing prices calculated by the finite difference method, returned as a two-dimensional grid with size `AssetGridSize``TimeGridSize`. The number of columns is not necessarily equal to the `TimeGridSize` because the function adds exercise and ex-dividend dates 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.

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

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

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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: $\mathrm{max}\left(St-K,0\right)$

• For a put: $\mathrm{max}\left(K-St,0\right)$

where:

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

K is the strike price.

Bates Stochastic Volatility Jump Diffusion Model

The Bates model [1] extends the Heston model by including stochastic volatility and (similar to Merton) jump diffusion parameters in the modeling of sudden asset price movements.

The stochastic differential equation is

`$\begin{array}{l}d{S}_{t}=\left(r-q-{\lambda }_{p}{\mu }_{J}\right){S}_{t}dt+\sqrt{{v}_{t}}{S}_{t}d{W}_{t}+J{S}_{t}d{P}_{t}\\ d{v}_{t}=\kappa \left(\theta -{v}_{t}\right)dt+{\sigma }_{v}\sqrt{{v}_{t}}d{W}_{t}\\ \text{E}\left[d{W}_{t}d{W}_{t}^{v}\right]=pdt\\ \text{prob(}d{P}_{t}=1\right)={\lambda }_{p}dt\end{array}$`

where:

r is the continuous risk-free rate.

q is the continuous dividend yield.

St is the asset price at time t.

vt is the asset price variance at time t.

J is the random percentage jump size conditional on the jump occurring, where `ln`(1+J) is normally distributed with mean $\mathrm{ln}\left(1+{\mu }_{J}\right)-\frac{{\delta }^{2}}{2}$ and the standard deviation δ, and (1+J) has a lognormal distribution:

`$\frac{1}{\left(1+J\right)\delta \sqrt{2\pi }}\mathrm{exp}\left\{{\frac{-\left[\mathrm{ln}\left(1+J\right)-\left(\mathrm{ln}\left(1+{\mu }_{J}\right)-\frac{{\delta }^{2}}{2}\right]}{2{\delta }^{2}}}^{2}\right\}$`

where:

v0 is the initial variance of the asset price at t = 0 (v0> 0).

θ is the long-term variance level for (θ > 0).

κ is the mean reversion speed for (κ > 0).

σv is the volatility of variance for (σv > 0).

p is the correlation between the Weiner processes Wt and ${W}_{t}^{v}$ for (-1 ≤ p ≤ 1).

μJ is the mean of J for (μJ > -1).

δ is the standard deviation of `ln`(1+J) for (δ ≥ 0).

${\lambda }_{p}$ is the annual frequency (intensity) of Poisson process Pt for (${\lambda }_{p}$ ≥ 0).

References

[1] Bates, D. S. "Jumps and Stochastic Volatility: Exchange Rate Processes Implicit in Deutsche Mark Options." The Review of Financial Studies. Vol. 9, Number 1, 1996.

Version History

Introduced in R2019a

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