 
 
 
 
 SYLLABUS  Previous: 4.3.1 Transformation to log-normal
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SYLLABUS  Previous: 4.3.1 Transformation to log-normal
 Up: 4.3 Methods for European
 Next: 4.3.3 Black-Scholes formula
4.3.2 Solution of the normalized diffusion equation 
 
 
[ SLIDE Fourier-Laplace
fwd -
bck || Solution
binary options || same 
VIDEO                as previous section: 
modem -
LAN -
DSL]
Readers interested in solving the diffusion equation (4.3.1#eq.5) 
analytically are likely to be familiar with the Fourier-Laplace transform
that is commonly used to solve initial and boundary value problems.
Others may skip the whole derivation and verify that the final result 
(4.3.2#eq.11) indeed satisfies the Black-Scholes equation (3.4#eq.4).
Start by transforming (4.3.1#eq.5) with a Laplace transform in time
| ![$\displaystyle \int_0^\infty d\tau \exp(i\omega \tau)\left[ \pd{u}{\tau} -\pd{^2 u}{x^2} \right] = 0, \qquad \Im m(\omega)>0$](s4img92.gif) | (4.3.2#eq.1) | 
 
Note that the condition 
 is important to ensure causality.
Integrate the first term by parts and substitute a Dirac function
 is important to ensure causality.
Integrate the first term by parts and substitute a Dirac function 
 for the initial condition
 for the initial condition  
| ![\begin{displaymath}\begin{split}\left. u\exp(i\omega \tau) \right\vert _0^\infty...
... u(x,\omega) -\pd{^2 u(x,\omega)}{x^2} \right] &= 0 \end{split}\end{displaymath}](s4img95.gif) | (4.3.2#eq.2) | 
 
The notation 
 refers to the Laplace transform of
 refers to the Laplace transform of  . 
Spatial derivatives are dealt with a Fourier transform
. 
Spatial derivatives are dealt with a Fourier transform
|  | (4.3.2#eq.3) | 
 
and yields an explicit solution in Fourier-Laplace space
|  | (4.3.2#eq.4) | 
 
The pole in the complex plane for 
 needs to be taken 
into account when inverting the Laplace transform in a causal manner
 needs to be taken 
into account when inverting the Laplace transform in a causal manner
|  | (4.3.2#eq.5) | 
 
where the residue theorem has been used to evaluate the complex integral, 
closing the contour in the lower half plane where the phase factor 
 decays exponentially.
Invert the Fourier transformation
 decays exponentially.
Invert the Fourier transformation
|  | (4.3.2#eq.6) | 
 
and use the formula (3.323.2) from Gradshteyn & Ryzhik [9]
| ![$\displaystyle \int_{-\infty}^{\infty} dx \exp(-p^2x^2)\exp(\pm qx) = \frac{\sqrt{\pi}}{p}\exp\left[\frac{q^2}{4p^2}\right] \qquad p>0$](s4img104.gif) | (4.3.2#eq.7) | 
 
here with 
 and
 and 
 to write down a solution of the 
diffusion equation
 to write down a solution of the 
diffusion equation
| ![$\displaystyle u(x,\tau)=\frac{1}{2\sqrt{\pi \tau}}\exp\left[-\frac{(x-\xi)^2}{4\tau}\right]$](s4img107.gif) | (4.3.2#eq.8) | 
 
This shows that a Dirac function 
 assumed as initial 
condition in (4.3.2#eq.2) spreads out into a Gaussian as
time evolves forward.
A superposition of a whole series of Dirac functions can now be 
used to decompose any arbitrary initial condition
 assumed as initial 
condition in (4.3.2#eq.2) spreads out into a Gaussian as
time evolves forward.
A superposition of a whole series of Dirac functions can now be 
used to decompose any arbitrary initial condition  
|  | (4.3.2#eq.9) | 
 
and after evolving each Dirac functions separately using 
(4.3.2#eq.8), can again be superposed at a later 
time when  :
:
| ![$\displaystyle u(x,\tau)=\frac{1}{2\sqrt{\pi \tau}}\int_{-\infty}^\infty d\xi u_0(\xi)\exp\left[-\frac{(\xi-x)^2}{4\tau}\right]$](s4img110.gif) | (4.3.2#eq.10) | 
 
Transforming back into financial variables (4.3.1#eq.1), some 
algebra finally yields a general formula for the price of a binary 
option with a terminal payoff 
 
| ![$\displaystyle V(S,t)=\frac{\exp[-r(T-t)]}{\sigma\sqrt{2\pi(T-t)}} \int_0^\infty...
...) -(r-D-\frac{\sigma^2}{2})(T-t)\right)^2} {2\sigma^2(T-t)} \right]\frac{dX}{X}$](s4img111.gif) | (4.3.2#eq.11) | 
 
SYLLABUS  Previous: 4.3.1 Transformation to log-normal
 Up: 4.3 Methods for European
 Next: 4.3.3 Black-Scholes formula