Try this one: http://papers.ssrn.com/sol3/papers.cfm? ... id=1480174

(1 - alpha) ?

Compute the covariance matrix, do an SVD to determine r. With the rank determined just take the square-root of the rank reduced covariance matrix. Hth

For example d B_T = B_T' dt and so on. Replace A and B by their known analytical forms and do the math.

I've stumbled upon this some time ago that has a mixed approach...http://www.springerlink.com/content/6p3 ... /HthIulian

I liked this: http://arxiv.org/abs/0907.4290Not 100% sure this is what you're looking for...

Use the martingale PDE condition Take f(t,x) = e^{t/2} cos(x) and see if f_{t} + 1/2 f_{xx} =0. If yes it's a local martingale. Then check if f_{x} is in H^2.Hth

Programming: Principles and Practice Using C++ by Strostroup

Jorion, Value-at-risk 3rd edition

If you've never programmed in C++ before I would say beginner.

<t>It's not only CAPM it's in general and you can find the link when you look at the problem as the optimization of the index of satisfaction(I'm following Meucci's, "Risk and Asset Allocation", 6.5.1). The only markets, for which the approximation of the investor's satisfaction in terms of the firs...

<r>Check out this paper: <URL url="http://papers.ssrn.com/sol3/papers.cfm?abstract_id=992748"><LINK_TEXT text="http://papers.ssrn.com/sol3/papers.cfm? ... _id=992748">http://papers.ssrn.com/sol3/papers.cfm?abstract_id=992748</LINK_TEXT></URL> and the references therein. It'll give you an idea how to...

Hi Mona, Find the SDE for log(S) using Ito ( d log(S) = (a- 0.5 b^2) dt + b dW ) and then you'll get the solution by integrating. Applying Ito to f(S) = log(S) you'll understand where the extra term is coming from. hth

<r>Check out eq (4.1) here <URL url="http://avikram.freeshell.org/uploads/73.pdf">http://avikram.freeshell.org/uploads/73.pdf</URL>, that's what you theta is(it depends on your parameters sigma and alpha). You will need to interpolate your yield curve to obtain a smooth forward curve.You can calibra...