"Successful trading is one long journey, not a destination" Peter Borish Former Head of Research for Paul Tudor Jones speaking on conversations with John F. Carter

I was in the academic world for a few years and now work in finance services (yep another math guy in finance) and have been trying to learn more about the most interesting parts of my job, i.e. seeing the price time series and wondering about patterns, correlations, etc. I always prefer the mathematical perspective when I look at a time series instead of these traders that use their own built in pattern recognition .

My background is in applied math where I spent most of my graduate studies in signal processing/machine learning. I have my M.S. but no Ph.D yet (working on it part time since I need to pay the bills and not sure if I want to finish at this point). I also worked with a finance professional for awhile and helped him with programming items mainly. It was sort of the beginning of my foray into the finance world which lately I have been finding more and more interesting. Anyway, I've been looking into the field and was just wondering about an insider's perspective. I'll definitely check out those books/links so thanks for that.

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Thanks for your insightful posts Artemiso. Do you also happen to know which books on mathematics are helpful for retail traders who don't have a mathematics background but nonetheless still want to incorporate some more quantitative subjects in their trading? In other words, what mathematical concepts should we learn to better understand quantitative models?

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Applied mathematicians say the same thing about the theoretical ones sometimes, and the theoretical math and many applied people say that physicists are too "loose" with their calculations. There is also some distinction based on what type of "mathematician" are you--Are you an algebraist or a analyst? Analysts would have the error bounds, etc. whereas algebraists would be focused on definite terms. Of course then there's hybrids of both and those silly topologists, but I digress.

Terence Tao said this "Algebra prizes structure, symmetry, and exact formulae; analysis prizes smoothness, stability, and estimates." Most theoretical mathematics majors would have more curriculum from the algebra side, though you can't really get through undergraduate school without taking some form of basic real analysis and algebra courses (like linear algebra). Most theoretical math curricula would include a serious helping of abstract algebra, whereas applied math would be more along the lines of numerical analysis which is all about error estimates. My thing has always been applied math because my interests are sort of a combination of electrical engineering and mathematics. I just stuck to math because I kept putting off EE courses to take something like Dynamics & Chaos which was offered less frequently. All of my core course work was in applied topics like PDE's for engineering, numerical analysis, etc.

Anyway, thanks for the information. Next pay check I'm picking up that first book.

As far as the PhD thing, its just getting to the point where I am sick of coursework, especially since I have to work full time. I'd rather learn things on my own and I am at the point where that is possible. I keep holding out on it because I am so close to finishing, but I'm still 28 years old and way behind some of my peers who went to work right out of undergrad. I have all the credits I need for my PhD except something called "readings" courses and dissertation credits. Of course I still need to take all the comprehensive examinations as well. I already have a pretty strong programming background but I have been wanting to take some time to really focus on developing more skills in that area, and graduate school right now seems to be getting in the way of that as the work load is quite a lot when one also works full time.

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FYI : Kuznetsov's book "The Complete Guide to Capital Markets for Quantitative Professionals" is great. The historical background of the markets and outline of what the major players do and how they make money at the beginning is worth the purchase of the book IMO. I haven't finished it yet but so far it's been very good to fill in gaps in my knowledge.

Thanks!

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Antisyzygy - Thanks for the link about corn, I enjoyed it. (I eat my corn vertically, while rotating the cob.) I'm glad you enjoyed the read. Kuznetsov (or in fact any other book) does not cover trading strategies, but it is the best introduction to the quant industry. I think it will help with your career decisions more than knowing Hamilton-Jacobi-Bellman approaches to trade execution or filtering of high-frequency data. There are lots of jobs for quants at your qualification level and you should definitely consider. I cannot offer as much as what's available on the Wilmott forums, and seriously recommend that you take a look over there. Seeing your conviction in learning more about this field, I've also sent you a PM with some other reference material with more practical details of quantitative trading strategies.

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Coursera is offering a free online course starting in February which might be of interest to readers of this thread. The "Financial Engineering and Risk Management" course is probably not as applied as Artemiso's comments in this thread, but it might give a nice overview of quantitative subjects. I'm looking forward to follow it.