Option Pricing Model

Option pricing model

This shows option pricing model in mathematics. Described as Langevin equation, it assumes that the price change of underlying asset stock price or stock indices rely on the Winner process.


The value of X after time t which relies on the winner process shows following a differential equation.


dXt = r Xt dt + σ Xt dWt


the payoff function of call option as g(x)


g(St) = max{ St-K, 0 }


C(St, t) =E[max{Xt-K,0} e-r(T-t)| Xt=St]


Xt = Xt e (r-(1/2)σ2)(T-t)+σ(WT-Wt)


where definition of the winner process,(WT-Wt) relies on the normal distribution which is average 0, variance (T-t), Z defined as stochastic variable relies on the normal distribution of the average 0, variance 1, replace with √(T-t)・Z


C(St・t)=E[max{St e (r-(1/2)σ2)(T-t)+σ√(T-t)Z ) -K, 0}] e -r(T-t)


C(St・ t)=∮-∞max{S, e(r-(1/2)σ2)(T-t)+σ√(T-t)Z )}f(z)dz e-r(T-t)


where

f(z) = (1/√2π)e -(1/2)z"2


to solve this integral

omit the calculation procedure.

where put the function N(x) of normal standard distribution


C(St,t) = St N(ht) - K e -r(T-t) N(ht - σ√(T-t)) -----------------(※)


put ht as


ht = 1/(σ√(T-t))log(St/K e -r(T-t))+ (1/2)σ√(T-t)


This equation (*) is well known pay off function of call option of the Black-Shoerls equation.