FRM. 391 hours left

Penera

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FRM. 391 hours left

Ito Process

It is a generalized Wiener process in which the parameters a and b are functions of the variable x and t: dx = a\times (x,t) dt + b\times (x,t) dz

This is Markov because the value of x only depends on time t. Both the drift rate and volatility rate are changing overtime.

For the change \Delta x in small time interval \Delta t,

\Delta x = a\times (x,t)\Delta t + b\times (x,t) \sqrt{\Delta t}

Ito Process

Generalized Wiener Process

If the change \Delta z in a small period of time \Delta t is independent, with a standardized normal distribution (0,1), then z follows the basic Wiener process (Brownian motion). \Delta z = normal(0, \Delta t); for any period T, z = normal(0,T)

A generalized Wiener process of variable x: dx = a\times dt + b\times dz, where a and b are constants

In a \Delta t, the change

\Delta x = a\times \Delta t + b\times \sqrt{\Delta t}

\Delta x has a normal distribution with an expected drift rate of a and a variance of b^2.

x in any time interval T is normally distributed with mean of change in x = aT, and variance of change in x = b^2\times T

Generalized Wiener Process