Prometheus Posted December 23, 2014 Share Posted December 23, 2014 (edited) So i want to find the expectation of a geometric Brownian motion: [math]E[e^{K^TW_t}][/math] Where K is a constant vector and [math]W_t[/math] is a vector of normal Brownian motions, both of length n. I assume that as [math]K^TW_t[/math] is a scalar I can just proceed in a similar fashion as the univariate case to get: [math]e^{\frac{1}{2}K^TK}[/math] But is it that simple or am i missing something as i suspect? As always, help very much appreciated. Edited December 23, 2014 by Prometheus Link to comment Share on other sites More sharing options...
Prometheus Posted January 2, 2015 Author Share Posted January 2, 2015 The above is nearly correct, just a small typo. The bit missing from my understanding was simply realising that [latex] K^TW_t = ||K||^2 [/latex] Now stuck on a related question. I now have [latex] e^{iK^TdW_t}[/latex], where [latex]dW_t[/latex] is an infinitesimal Brownian increment. I want to find the Taylor expansion of this - I would know how to proceed in the univariate case, but i don't understand the multivariate case. Does anyone have any hints or good links? Link to comment Share on other sites More sharing options...
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