matlab, maple, mathematica, java, fortran, C. A lot of the stuff I do isn't just writing code but solving problems and then having the code to solve the problem generated and compiled automatically. I've found a lot of useful stuff in Automatic Differenation Automatic Differentiation (AD) is a set of techniques based on the mechanical application of the chain rule to obtain derivatives of a function given as a computer program. AD exploits the fact that every computer program, no matter how complicated, executes a sequence of elementary arithmetic operations such as additions or elementary functions such as exp(). By applying the chain rule of derivative calculus repeatedly to these operations, derivatives of arbitrary order can be computed automatically, and accurate to working precision. Conceptually, AD is different from symbolic differentiation and approximations by divided differences. AD is used in the following areas: * Numerical Methods * Sensitivity Analysis * Design Optimization * Data Assimilation & Inverse Problems So, my enviornment is pretty varied but C is really what ties it al together and I use code generators that generate exact/fast implementatins based on whatever math is derived in the high-level tools.
Hmmmm, I don't really fully agree with this. Sure, a capable person will pick up the language itself quickly, but these days it's not just the language itself. It's also about the whole framework and APIs and good practices in using the framework(s). I defy anybody, no matter how good a C++ programmer to pick up all of Java in a week - J2SE, J2EE, Swing, 2D, 3D graphics and the endless number of other libraries and API's. Just not possible. You will find yourself constantly lookup up doc or googling for code samples which is not very conducive to getting anything done. The Sun distributed documentation for J2SE alone is 250 Mbytes. To become proficient, as opposed to being able to kock together a bit of code actually takes a lot longer.
I'm not a professional quant, I do software professionalyl though.. right now this is just a hobby and something I'm teaching myself.. It is something I have considered, but I'm very comfortable in my life right now and am able to study and learn and work stress-free for now and do exciting/interesting stuff that is probably frowned upon at more traditional quant places.. Plus, my goal is not to work for someone, unless it is some absurd salary (a few hundred K). but for that you need proven results, or a Phd in some area of math.
Yeah, R has some really nice packages.. I found the interfface to be pretty clunky though.. and it is quite a pain in the ass to use in general.
I don't think so nitro. If you are happy with mediocre C++ skills and merely want to pick up mediocre Python skills, this may be OK. In the days I used to teach C++, I sometimes paraphrased Henri Poincarre's famous dictum: "If you want to become a good programmer, it's sufficient to read the masters." To get some background on C++ and Python mastery, for Python take a look at: http://groups.google.com/group/comp.lang.python?lnk=li&hl=en Posters are by far not all "masters", but some show up regularly. You might perhaps change your mind about some of this. nono
stephencrowley thanks alot for that in-depth post very informative. since looking into it, ive noticed there are actually many ways to look at the market, and many tools u can use.. don't u guys think 'quant' r over-doing it? i mean like surely a guy just looking at the news or playing psychology may be able to give similar results. getting too quantiative can get u lost dont' u think? i think the real question is now how best do u approach the market? technical+quantiative? experience+psychology? c++/matlab? statistics? philosophy? arts? politics? perceptions? we all know traders that are successful from these areas and others.. how do u strike the right balance? does Soros know C++? does Cohen use matlab? alot of people reviewing Livermore say his success was how he changed strategies and adapted over time. maybe Soros didn't need C++ in 92.. do we all need to be half-quants today? i visited a hedge fund a few weeks ago, they showed this data over for the past 5 years about the volumes going through londons trading.. the growth in algorithim executions is astonishing. i honestly can't see how discritionary trades can be successful in 10 years when price gaps r filled in 1/100th of seconds by some blabla+++ computer..
Could somebody tell me what's a quant? Is Jack a quant? I definitely got the impression from wading through a lot of ET that "quant" is one of the most respectable buzzwords. Meaning likely good for nothing if you have set your mind upon making money.
I don't know what defines a "quant" exactly. All I know is I do what works best for me... I have a very analytical mind, so being able design a system mathematically is really helpful because the math can be turned directly into algorithms, which is much easier than just coding blindly without some way to tie it all together. I don't believe there is such a thing as over-doing it, and frankly I don't care what Sorros or Cohen do. Whatever they are doing, is already being done by them so you probably aren't going to be successful by simply trying to copy what they are doing, be creative.
Batman, I can't speak for others, but as to why I don't work as a quant for some firm it's because I prefer to own what I develop and not contribute on the cheap to someone else's venture. As far as teaching this or that and the evolution of technology and the markets, I remember in my old signal processing days talking with Sidney Darlington (you remember him, the guy who made it possible to replace tubes with transistors!) about how far technology had come in the last few years and where it might end-up over the next decade. Well we blew past those predictions in about 2 years. My take on the value of technology in today's market's and what an expert (not quants) can achieve may be equivalent or better than what NASA and the DOD felt work was worth mid-1990's for experts to consult, prototype and architect the Internatoinal Space Station's Horizontal Test Simulator, rehost the B2 Stealth Simulator from Convex systems onto Alpha AXP platforms and things like that. http://en.wikipedia.org/wiki/Darlington_pair http://en.wikipedia.org/wiki/Sidney_Darlington