expectation of a stochastic variable (Ito's formula)
This question is from Mathematics for Finance, a chapter on Ito's Formula. I could apply Ito's to calculate the required variable, but I could not follow through the second part, to find its expectation. Perhaps I don't understand the Brownian motion (most likely that I don't). Unfortunately I don't have the solution to this question.
PS
is a multiplication factor to find the value of a deposit/sum of money after t periods, given that the deposit pays interest rate r, and assuming continous compounding.
Question.
The stochastic differential equation for the rate of inflation I is given by

Find the equation satisfied by the real interest rate R defined to be
, where
.
[Hint: Consider
.]
Show that
.
Answer.
I will apply Ito's formula to find dR.
Let =\frac{e^{rt}}{I})



therefore, we calculate df(I,t) from the equation of dI by applying Ito's formula:
![dR_t=[\frac{\partial{f}}{\partial{t}}(I,t)+\mu{I}\frac{\ partial{f}}{\partial{I}}+\frac{1}{2}\frac{{\partia l}^2{f}}{\partial{t}^2}\sigma^2I^2]dt+\frac{\partial{f}}{\partial{I}}\sigma{I}dz_t=(\ frac{re^{rt}}{I}-\frac{e^{rt}\mu}{I}+\frac{e^{rt}\sigma^2}{I})dt-\frac{e^{rt}\sigma}{I}dz_t](http://latex.codecogs.com/png.latex?dR_t=[\frac{\partial{f}}{\partial{t}}(I,t)+\mu{I}\frac{\ partial{f}}{\partial{I}}+\frac{1}{2}\frac{{\partia l}^2{f}}{\partial{t}^2}\sigma^2I^2]dt+\frac{\partial{f}}{\partial{I}}\sigma{I}dz_t=(\ frac{re^{rt}}{I}-\frac{e^{rt}\mu}{I}+\frac{e^{rt}\sigma^2}{I})dt-\frac{e^{rt}\sigma}{I}dz_t)
by dividing this by
, we get
dt-\sigma{dz_t})
Here where it gets tricky,
![E(\frac{dR}{R})=E[(r-\mu+\sigma^2)dt]-E[\sigma{dz_t}]= ??? -0](http://latex.codecogs.com/png.latex?E(\frac{dR}{R})=E[(r-\mu+\sigma^2)dt]-E[\sigma{dz_t}]= ??? -0)
I know that E(dz)=0 as it is a Wiener process with mean=0
But what do I do with the remaining expectation on dt???
Somehow I need to show that
and I can only see that if I have
BUT why T=1???
Is there an implicit assumption that values of
are given on a per annum basis, therefore T=1?
thanks