Thursday, December 10, 2015

Applying Ito's formula on math problems -- learning notes

Ito's formula in a nutshell -- Given dynamics of a process X, we can derive the dynamics[1] of a function[2] f() of x .

[1] The original "dynamics" is usually in a stoch-integral form like

  dX = m(X,t) dt + s(X,t) dB

In some problems, X is given in exact form not integral form. For an important special case, X could be the BM process itself:

  Xt=Bt

[2] the "function" or the dependent random variable "f" is often presented in exact form, to let us find partials. However, in general, f() may not have a simple math form. Example: in my rice-cooker, the pressure is some unspecified but "tangible" function of the temperature. Ito's formula is usable if this function is twice differentiable.

The new dynamics we find is usually in stoch-integral form, but the right-hand-side usually involves X, dX, f or df.

Ideally, RHS should involve none of them and only dB, dt and constants. GBM is such an ideal case.

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