Financial engineering for autodidacts.
October 24, 2008 7:05 AM   Subscribe

So suppose I wanted to teach myself quantitative finance, computational finance, whatever you want to call it. How would I go about doing so? What books should I get? I imagine there are some standard textbooks that most students use available on amazon, what are they?

I think I have most of the math background needed (I might need to bone up on some things) and I certainly have the computer background. I don't know too much about finance, but I enjoy learning things on my own.
posted by delmoi to Work & Money (9 answers total) 16 users marked this as a favorite
 
Perhaps you could search online for a course syllabus from your local university and then go and buy that book.

My gut feeling is that these types of courses are graduate level only and so there is not really enough demand for Amazon to carry such a book. So go copy whatever your local university does.

I admire your ambition to teach yourself such an obscure topic. As they say in Good Will Hunting "You dropped a hundred and fifty grand on a fuckin' education you could'a got for a dollah fifty in late chahges at the public library" Not that learning was ever the only point of school but...
posted by FastGorilla at 7:28 AM on October 24, 2008 [1 favorite]


Response by poster: My gut feeling is that these types of courses are graduate level only and so there is not really enough demand for Amazon to carry such a book.

I doubt that's the case at all, Amazon has some pretty obscure stuff.
posted by delmoi at 7:42 AM on October 24, 2008


It might be worth browsing through some of MIT's Open Courseware materials, or course resources from other schools.. Not sure what they have at the graduate level, but you might find some gems in there.
posted by mbatch at 8:11 AM on October 24, 2008


Best answer: I did this, it is not that hard to find the graduate level books. I did take some advanced maths in business school (Calc II, some advanced statistics), along with light programming courses, usually involving Matlab and the like. They don't really teach anything more until you get to grad school. I hear that NYU/MIT have more advanced quantfin programs but I don't know, in general you don't take stochastic calculus and other things you need until you get to grad school. So if you have a solid math and programming base, I really don't see how this would unobtainable, I certainly consider myself to at least have a solid theoretical understanding, enough to read journals. This doesn't mean I can build a black box or increased my employment opportunities. In any case, here's what a total unprofessional, uneducated simpleton would recommend:

- Louis Bacheelier's Theory of Speculation: The Origins of Modern Finance
This is invaluable and my favorite text. I really enjoy the history of modern finance (and to that extent, recommend Historia: Empiricism and Erudition in Early Modern Europe, not for a quantfin text, but really gave me perspective of how to view a branch of applied mathematics from an epistimological perspective, really the new stuff in finance is behavioral/decision making, and a lot of the theoretical work by top minds is being done there, at least in my outside the beltway perspective sees it. So it helps get a grasp of what is a science, what isn't a science and how certain concepts came about. Yeah, even basic stuff really needs to be questioned here).

- Option Pricing Models and & Volatility Using Excel-VBA by Ruah & Vainberg, helped me go from theoretical to using Excel to actually do something. I use it as a reference all the time. And it comes with a CD.

- Quantitative Equity Portfolio Management; Modern Techniques and Applicatoins by Qian, Hua and Sorensen. I found it very easy to read, didn't get too academic and is up to date, Don't expect large asides on whether Gaussian distributions are applicable.

- Dynamic Hedging: Managing Vanilla and Exotic Options, by Taleb .... I hear this is on everyone's desk (or whoever is left), very good read. Must have.

- Options, Futures, and Other Derivatives by Hull, again must have

Read through Wilmott where the other quants hang out, you'll pick up on what people read and use quickly.

I have a huge (>1gig) compilation of PDFs from Wiley Finance, including papers and internal docs. If you're interested MeMail me, some of it is rubbish, some of it is classic.

Risk Books is also a great resource and I order books from them all the time.

My preferred way of going about this was to start out with the history and major papers, the theory behind, how it came to be, then try to get into application. Actually application bored me, but I found the history and theory really stimulating (obviously). Hopefully someone more professional can come and chime in, but there's enough there to make you dangerous and look half-literate in discussions.
posted by geoff. at 8:12 AM on October 24, 2008 [4 favorites]


As a first book, I'd go for Paul Wilmott introduces Quantitative Finance. The standard textbook is Hull but that's heavier going.
posted by crocomancer at 8:13 AM on October 24, 2008


Oh I compiled my library using Amazon and going through recommended reading from top courses at universities. It is definitely possible to do this sitting on your ass. The most illuminating ideas came from random papers and outlines by various professors on their web sites. Also you don't have to 100% understand the math behind everything, a lot of times I had to talk myself through the equations, it doesn't come naturally at all. And if you went through calculus thinking that a derivative is infinitely small, stochastic calculus is like, a billion times harder, so get rid of those notions.
posted by geoff. at 8:18 AM on October 24, 2008


Best answer: I saw a Google Tech Talk on the subject, by David J. Leinweber., who keeps a blog called nerds on wallstreet. The video provides a nice overview (with references) of the kinds of things that computers are being used to for in markets, and at the end he recommends a few books, for finance students turned programmers and programmers turned financial students. Of course, he also recommends his own book, so caveat emptor.

The one thing that most computer scientists need is much much better stats training. Sadly, I have no book on the subject.
posted by pwnguin at 1:08 PM on October 24, 2008 [3 favorites]


Asset Pricing by John Cochrane is one that I've heard recommended.
posted by lunchbox at 11:46 PM on October 26, 2008


You might want to take a look at Mutant's profile.
posted by racingjs at 9:54 AM on October 27, 2008


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