NAG Toolbox: nag_specfun_opt_jumpdiff_merton_greeks (s30jb)

Purpose

Syntax

Description

References

Parameters

Compulsory Input Parameters

1:     $\mathrm{calput}$ – string (length ≥ 1)

Determines whether the option is a call or a put.

$\mathbf{calput}=\text{'C'}$

A call; the holder has a right to buy.

$\mathbf{calput}=\text{'P'}$

A put; the holder has a right to sell.

Constraint: $\mathbf{calput}=\text{'C'}$ or $\text{'P'}$.

2:     $\mathrm{x}\left(\mathbf{m}\right)$ – double array

$\mathbf{x}\left(i\right)$ must contain $X_{\mathit{i}}$, the $\mathit{i}$th strike price, for $\mathit{i}=1,2,\dots ,\mathbf{m}$.

Constraint: $\mathbf{x}\left(\mathit{i}\right)\ge z\text{ and }\mathbf{x}\left(\mathit{i}\right)\le 1/z$, where $z=\mathbf{x02am}\left(\right)$, the safe range parameter, for $\mathit{i}=1,2,\dots ,\mathbf{m}$.

3:     $\mathrm{s}$ – double scalar

$S$, the price of the underlying asset.

Constraint: $\mathbf{s}\ge z\text{ and }\mathbf{s}\le 1.0/z$, where $z=\mathbf{x02am}\left(\right)$, the safe range parameter.

4:     $\mathrm{t}\left(\mathbf{n}\right)$ – double array

$\mathbf{t}\left(i\right)$ must contain $T_{\mathit{i}}$, the $\mathit{i}$th time, in years, to expiry, for $\mathit{i}=1,2,\dots ,\mathbf{n}$.

Constraint: $\mathbf{t}\left(\mathit{i}\right)\ge z$, where $z=\mathbf{x02am}\left(\right)$, the safe range parameter, for $\mathit{i}=1,2,\dots ,\mathbf{n}$.

5:     $\mathrm{sigma}$ – double scalar

$\sigma$, the annual total volatility, including jumps.

Constraint: $\mathbf{sigma}>0.0$.

6:     $\mathrm{r}$ – double scalar

$r$, the annual risk-free interest rate, continuously compounded. Note that a rate of 5% should be entered as 0.05.

Constraint: $\mathbf{r}\ge 0.0$.

7:     $\mathrm{lambda}$ – double scalar

$\lambda$, the number of expected jumps per year.

Constraint: $\mathbf{lambda}>0.0$.

8:     $\mathrm{jvol}$ – double scalar

The proportion of the total volatility associated with jumps.

Constraint: $0.0\le \mathbf{jvol}<1.0$.

Optional Input Parameters

1:     $\mathrm{m}$ – int64int32nag_int scalar

Default: the dimension of the array x.

The number of strike prices to be used.

Constraint: $\mathbf{m}\ge 1$.

2:     $\mathrm{n}$ – int64int32nag_int scalar

Default: the dimension of the array t.

The number of times to expiry to be used.

Constraint: $\mathbf{n}\ge 1$.

Output Parameters

1:     $\mathrm{p}\left(\mathit{ldp},\mathbf{n}\right)$ – double array

$\mathit{ldp}=\mathbf{m}$.

$\mathbf{p}\left(i,j\right)$ contains $P_{ij}$, the option price evaluated for the strike price ${\mathbf{x}}_i$ at expiry ${\mathbf{t}}_j$ for $i=1,2,\dots ,\mathbf{m}$ and $j=1,2,\dots ,\mathbf{n}$.

2:     $\mathrm{delta}\left(\mathit{ldp},\mathbf{n}\right)$ – double array

$\mathit{ldp}=\mathbf{m}$.

The leading $\mathbf{m}\times \mathbf{n}$ part of the array delta contains the sensitivity, $\frac{\partial P}{\partial S}$, of the option price to change in the price of the underlying asset.

3:     $\mathrm{gamma}\left(\mathit{ldp},\mathbf{n}\right)$ – double array

$\mathit{ldp}=\mathbf{m}$.

The leading $\mathbf{m}\times \mathbf{n}$ part of the array gamma contains the sensitivity, $\frac{{\partial }^{2}P}{\partial S^2}$, of delta to change in the price of the underlying asset.

4:     $\mathrm{vega}\left(\mathit{ldp},\mathbf{n}\right)$ – double array

$\mathit{ldp}=\mathbf{m}$.

$\mathbf{vega}\left(i,j\right)$, contains the first-order Greek measuring the sensitivity of the option price $P_{ij}$ to change in the volatility of the underlying asset, i.e., $\frac{\partial P_{ij}}{\partial \sigma }$, for $i=1,2,\dots ,\mathbf{m}$ and $j=1,2,\dots ,\mathbf{n}$.

5:     $\mathrm{theta}\left(\mathit{ldp},\mathbf{n}\right)$ – double array

$\mathit{ldp}=\mathbf{m}$.

$\mathbf{theta}\left(i,j\right)$, contains the first-order Greek measuring the sensitivity of the option price $P_{ij}$ to change in time, i.e., $-\frac{\partial P_{ij}}{\partial T}$, for $i=1,2,\dots ,\mathbf{m}$ and $j=1,2,\dots ,\mathbf{n}$, where $b=r-q$.

6:     $\mathrm{rho}\left(\mathit{ldp},\mathbf{n}\right)$ – double array

$\mathit{ldp}=\mathbf{m}$.

$\mathbf{rho}\left(i,j\right)$, contains the first-order Greek measuring the sensitivity of the option price $P_{ij}$ to change in the annual risk-free interest rate, i.e., $-\frac{\partial P_{ij}}{\partial r}$, for $i=1,2,\dots ,\mathbf{m}$ and $j=1,2,\dots ,\mathbf{n}$.

7:     $\mathrm{vanna}\left(\mathit{ldp},\mathbf{n}\right)$ – double array

$\mathit{ldp}=\mathbf{m}$.

$\mathbf{vanna}\left(i,j\right)$, contains the second-order Greek measuring the sensitivity of the first-order Greek ${\Delta }_{ij}$ to change in the volatility of the asset price, i.e., $-\frac{\partial {\Delta }_{ij}}{\partial T}=-\frac{{\partial }^2{P}_{ij}}{\partial S\partial \sigma }$, for $i=1,2,\dots ,\mathbf{m}$ and $j=1,2,\dots ,\mathbf{n}$.

8:     $\mathrm{charm}\left(\mathit{ldp},\mathbf{n}\right)$ – double array

$\mathit{ldp}=\mathbf{m}$.

$\mathbf{charm}\left(i,j\right)$, contains the second-order Greek measuring the sensitivity of the first-order Greek ${\Delta }_{ij}$ to change in the time, i.e., $-\frac{\partial {\Delta }_{ij}}{\partial T}=-\frac{{\partial }^2{P}_{ij}}{\partial S\partial T}$, for $i=1,2,\dots ,\mathbf{m}$ and $j=1,2,\dots ,\mathbf{n}$.

9:     $\mathrm{speed}\left(\mathit{ldp},\mathbf{n}\right)$ – double array

$\mathit{ldp}=\mathbf{m}$.

$\mathbf{speed}\left(i,j\right)$, contains the third-order Greek measuring the sensitivity of the second-order Greek ${\Gamma }_{ij}$ to change in the price of the underlying asset, i.e., $-\frac{\partial {\Gamma }_{ij}}{\partial S}=-\frac{{\partial }^3{P}_{ij}}{\partial S^3}$, for $i=1,2,\dots ,\mathbf{m}$ and $j=1,2,\dots ,\mathbf{n}$.

10:   $\mathrm{colour}\left(\mathit{ldp},\mathbf{n}\right)$ – double array

$\mathit{ldp}=\mathbf{m}$.

$\mathbf{colour}\left(i,j\right)$, contains the third-order Greek measuring the sensitivity of the second-order Greek ${\Gamma }_{ij}$ to change in the time, i.e., $-\frac{\partial {\Gamma }_{ij}}{\partial T}=-\frac{{\partial }^3{P}_{ij}}{\partial S\partial T}$, for $i=1,2,\dots ,\mathbf{m}$ and $j=1,2,\dots ,\mathbf{n}$.

11:   $\mathrm{zomma}\left(\mathit{ldp},\mathbf{n}\right)$ – double array

$\mathit{ldp}=\mathbf{m}$.

$\mathbf{zomma}\left(i,j\right)$, contains the third-order Greek measuring the sensitivity of the second-order Greek ${\Gamma }_{ij}$ to change in the volatility of the underlying asset, i.e., $-\frac{\partial {\Gamma }_{ij}}{\partial \sigma }=-\frac{{\partial }^3{P}_{ij}}{\partial S^2\partial \sigma }$, for $i=1,2,\dots ,\mathbf{m}$ and $j=1,2,\dots ,\mathbf{n}$.

12:   $\mathrm{vomma}\left(\mathit{ldp},\mathbf{n}\right)$ – double array

$\mathit{ldp}=\mathbf{m}$.

$\mathbf{vomma}\left(i,j\right)$, contains the second-order Greek measuring the sensitivity of the first-order Greek ${\Delta }_{ij}$ to change in the volatility of the underlying asset, i.e., $-\frac{\partial {\Delta }_{ij}}{\partial \sigma }=-\frac{{\partial }^2{P}_{ij}}{\partial {\sigma }^2}$, for $i=1,2,\dots ,\mathbf{m}$ and $j=1,2,\dots ,\mathbf{n}$.

13:   $\mathrm{ifail}$ – int64int32nag_int scalar

$\mathbf{ifail}=\mathbf{0}$ unless the function detects an error (see Error Indicators and Warnings).

Error Indicators and Warnings

   $\mathbf{ifail}=1$

On entry, $\mathbf{calput}=\_$ was an illegal value.

   $\mathbf{ifail}=2$

Constraint: $\mathbf{m}\ge 1$.

   $\mathbf{ifail}=3$

Constraint: $\mathbf{n}\ge 1$.

   $\mathbf{ifail}=4$

Constraint: $\mathbf{x}\left(i\right)\ge \_$ and $\mathbf{x}\left(i\right)\le \_$.

   $\mathbf{ifail}=5$

Constraint: $\mathbf{s}\ge \_$ and $\mathbf{s}\le \_$.

   $\mathbf{ifail}=6$

Constraint: $\mathbf{t}\left(i\right)\ge \_$.

   $\mathbf{ifail}=7$

Constraint: $\mathbf{sigma}>0.0$.

   $\mathbf{ifail}=8$

Constraint: $\mathbf{r}\ge 0.0$.

   $\mathbf{ifail}=9$

Constraint: $\mathbf{lambda}>0.0$.

   $\mathbf{ifail}=10$

Constraint: $\mathbf{jvol}\ge 0.0$ and $\mathbf{jvol}<1.0$.

   $\mathbf{ifail}=12$

Constraint: $\mathit{ldp}\ge \mathbf{m}$.

   $\mathbf{ifail}=-99$

An unexpected error has been triggered by this routine. Please contact NAG.

   $\mathbf{ifail}=-399$

Your licence key may have expired or may not have been installed correctly.

   $\mathbf{ifail}=-999$

Dynamic memory allocation failed.

Accuracy

Further Comments

Example

Open in the MATLAB editor: s30jb_example

function s30jb_example


fprintf('s30jb example results\n\n');

put    = 'C';
lambda = 5;
s      = 100.0;
sigma  = 0.25;
r      = 0.08;
jvol   = 0.25;
x      = [80.0, 90.0];
t      = [0.5];

[p, delta, gamma, vega,   theta, rho, ...
    vanna, charm, speed, colour, zomma, vomma, ifail] = ...
    s30jb(...
          put, x, s, t, sigma, r, lambda, jvol);


fprintf('\nMerton Jump-Diffusion Model\n European Call :\n');
fprintf('  Spot       =   %9.4f\n', s);
fprintf('  Volatility =   %9.4f\n', sigma);
fprintf('  Rate       =   %9.4f\n', r);
fprintf('  Jumps      =   %9.4f\n', lambda);
fprintf('  Jump Vol   =   %9.4f\n\n', jvol);

fprintf(' Time to Expiry : %8.4f\n', t(1));

fprintf('%8s%9s%9s%9s%9s%9s%9s\n','Strike','Price','Delta','Gamma',...
        'Vega','Theta','Rho');
for i=1:2
  fprintf('%8.4f%9.4f%9.4f%9.4f%9.4f%9.4f%9.4f\n', x(i), p(i,1), ...
          delta(i,1), gamma(i,1), vega(i,1), theta(i,1), rho(i,1));
end

fprintf('\n%26s%9s%9s%9s%9s%9s\n','Vanna','Charm','Speed','Colour',...
        'Zomma','Vomma');
for i=1:2
  fprintf('%17s%9.4f%9.4f%9.4f%9.4f%9.4f%9.4f\n', ' ', vanna(i,1), ...
          charm(i,1), speed(i,1), colour(i,1), zomma(i,1), vomma(i,1));
end

s30jb example results


Merton Jump-Diffusion Model
 European Call :
  Spot       =    100.0000
  Volatility =      0.2500
  Rate       =      0.0800
  Jumps      =      5.0000
  Jump Vol   =      0.2500

 Time to Expiry :   0.5000
  Strike    Price    Delta    Gamma     Vega    Theta      Rho
 80.0000  23.6090   0.9431   0.0064   8.1206  -7.6718  35.3480
 90.0000  15.4193   0.8203   0.0149  18.5256  -9.9695  33.3037

                     Vanna    Charm    Speed   Colour    Zomma    Vomma
                   -0.6334   0.1080  -0.0006  -0.0035   0.0315  70.6824
                   -0.7726   0.0770  -0.0009   0.0109  -0.0186  49.7161