the idea is to simulate price returns thus to be normally distributed i 'am trying to use subordinated arithmetic brownian motion subordinated to time activity (volume) stock prices are following GBM then you can say $$ dS_t=μS_tdt+σS_tdW_t $$ where the time considered is not the calendar time but activity time (Ané & Geman 2000). I faced problems while implementing it in matlab so any help would be appreciated.
$\begingroup$
$\endgroup$
1
-
1$\begingroup$ Can you say what these problems were that you faced in Matlab? Can you post your Matlab code here? $\endgroup$– chrisaycockSep 23, 2013 at 16:10
Add a comment
|
1 Answer
$\begingroup$
$\endgroup$
Here it is. Returns here are normally distributed by construction. It doesn't involve time scale, you can use time, volume, or any other "activity".
>> sigma = 0.001;
>> mu = 0;
>> returns = mu + sigma * randn(1000,1);
>> price = cumprod(1 + returns);
>> plot(price)
