Derivatives Pricing - Finite Difference Methods

Overview

{% \frac{\partial V}{\partial t} + \frac{1}{2} \sigma ^2 \frac{\partial^2 V}{\partial S^2} + rS \frac{\partial V}{\partial S} -rV = 0 %}

Finite Difference Methods

{% V(S,0) = e^{\alpha ln S}e^{\beta \frac{\sigma^2 T}{2}} u (ln S, \frac{\sigma^2 T}{2}) %}
Converts the problem to forward finite difference.
let fd = await import('/lib/finance/derivatives/black-scholes/v1.0.0/finite-difference.js'); let boundary = function(val){ if(val>45) return val-45; return 0; } let T = 1/3; let variance = 0.4*0.4; let xtop = 200; let xnumber = 1000; let tnumber = 1000; let r = 0.03; let answer = fd.crankNicholson(T, r, variance, xtop, xnumber, tnumber, boundary); //answer for 40 stock price is 2.0236