What's an IT Quant?

<t>Machine learning will give you an excellent background in applied statistics and probability theory (and stochastic processes, as Gaussian processes are very popular in machine learning and they are stochastic processes). You don't really need to know PDE (or you can study it by yourself) necessa...

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You might want to look into this paper by Jong and Nijman (http://ideas.repec.org/p/dgr/kubcen/199534.html).

PhD is not a programme! As msperlin said it's research and it's upto you how to drive it. If you do a PhD in similar area, probably you will be able to speed it up because of your Masters but there is nothing such as an accelerated PhD programme.

4) Neftci. I found it very useful. There is a solution manual on his website as well so that you can check if your answers to the exercises are correct.

select a series for what?

I think you should try for an internship first.

If you matrix is not positively definite, there is not much you can do!

<r>Another neater approach could be to sort to Bayesian calibration methods as in (<URL url="http://www.ingentaconnect.com/content/bpl/rssb/2001/00000063/00000003/art00001"><LINK_TEXT text="http://www.ingentaconnect.com/content/b ... 3/art00001">http://www.ingentaconnect.com/content/bpl/rssb/2001/00...

Unfortunately (or fortunately), this ain't a chat-room. Don't expect people to have live convo here.

<t>How long is your postdoc contract? If you have some time on your contract, you can wait until market gets bit better (may be Q1 next year?).Ultimately what you do at energy company will matter. May be you will be involved in pricing futures/forward in there. That might be directly related to what...

<t>In one of my recent interviews, I was tested entirely on the subjects I claimed to know quite well in my CV. In my opinion, the interviewers asked good questions testing the depth of the subjects which mattered the most to them for the specified position and which were in my CV. In fact, the inte...

<t>Dominic has mentioned two approaches to QF in his P&D guide. 1) Probabilistic and 2) Applied maths (finite-difference methods, PDEs) approach.Both approaches have their pros and cons. Are they both use in parallel in practice? or some firms prefer probabilistic approach and some applied maths...

<t>Thank you all for your comments.@veeruthakur: During my phd, I developed probabilistic projection algorithms for projecting high-D data onto lower dimensions. Mostly I implemented the algos by myself (but in matlab and used the matlab toolboxes as well). I also developed a user-interface promotin...