SageMath – Open-Source Mathematical Software System

Do you have any idea what a quant is? I have a PhD in math, and am decently well versed in the math quants use, and it's nothing like undergrad math. Many of the people I got PhD's with became quants, and we've had plenty of discussions on the math they use.

Quants build models using math far beyond what an undergrad learns, including tools such as martingales, stochastic calculus, Black-Scholes (and vast generalizations), Brownian motion, Stochastic differential Equations, numerical methods (usually much more advanced than an undergrad will see), and more.

Quant jobs usually want a PhD in math or related field. If an undergrad math degree covered what they needed they'd not require a PhD for most positions.

What do you think a quant does?

Here's a site [1] for quant jobs. Probably none for someone with only an undergrad math degree.

[1] http://www.quantfinancejobs.com/

I've found that you can generally do most things you can do with MATLAB in Python, but the experience in MATLAB is buttery smooth while the experience with numerical Python is clunky and obnoxious (whether it be all the useless textual noise in the code itself, the inferior quality of the plotting and visualization capabilities or the fact the Python scientific computing library ecosystem is so disjoint (this thing can handle pandas frames, this other thing needs numpy vectors, this other thing expects Python lists, whatever).

I had high hopes for Julia, I have a test for it. How annoying is it to plot(sin(0:0.01:6*pi)) out of the box? For the extreme challenge question, how annoying is it to also open a new plot window and plot(cos(0:0.01:6:pi)) alongside it. I want to be able to pan around and inspect these complicated functions.

So far, it has not yet passed the qualifiers.

1). The domain you posted is for sale and appears to be broken or slow. Given it uses aspx and a Microsoft stack that's ten years out of date I'd say it's perfectly representative of the state of the larger finance industry.

2). What is a quant. Depends on the job. I was hired as a quant for risk management then got switched to algos when the pm found out I have a lot of hard real time experience with Linux. The first job was all discrete math, the second was optimizing x86 assembly.

3). Credential inflation is real. The application of the maths you talked about was something I saw first hand. The assumptions under which the formal models would work were so thread bare a stiff breeze would tear them down quote Keynes:

>The object of our analysis is, not to provide a machine, or method of blind manipulation, which will furnish an infallible answer, but to provide ourselves with an organised and orderly method of thinking out particular problems; and, after we have reached a provisional conclusion by isolating the complicating factors one by one, we then have to go back on ourselves and allow, as well as we can, for the probable interactions of the factors amongst themselves. This is the nature of economic thinking. Any other way of applying our formal principles of thought (without which, however, we shall be lost in the wood) will lead us into error. It is a great fault of symbolic pseudo-mathematical methods of formalising a system of economic analysis, such as we shall set down in section vi of this chapter, that they expressly assume strict independence between the factors involved and lose all their cogency and authority if this hypothesis is disallowed; whereas, in ordinary discourse, where we are not blindly manipulating but know all the time what we are doing and what the words mean, we can keep 'at the back of our heads' the necessary reserves and qualifications and the adjustments which we shall have to make later on, in a way in which we cannot keep complicated partial differentials 'at the back' of several pages of algebra which assume that they all vanish. Too large a proportion of recent 'mathematical' economics are merely concoctions, as imprecise as the initial assumptions they rest on, which allow the author to lose sight of the complexities and interdependencies of the real world in a maze of pretentious and unhelpful symbols.

The above is still excellent advice, most often never followed. Of course the lunch talks we had were very interesting, completely divorced from reality, but very interesting.

4). Most undergrads will never see the mathematics. True. But some will. My numerical methods 4th year project was a symplectic integrator for the gravitational interaction between Jupiter, Mars, the Sun and the asteroid belt. It wasn't new research, the results were known 50 years ago, but it was on par with the state of the art in industry in terms of complexity of implementation (cleanness of implementation was a completely different thing, while not spaghetti code it's rightly never seen the light of day).

I don't use matlab but I don't consider "matlab people" as bad scientists or limited in terms of what they can potentially do due to their tool. The limit of access for matlab due to licensing and expensive external modules such is the problem in my view. That isn't a critique at all of matlab's actual numerical and scientific utility, of course it's apt in that arena otherwise people wouldn't use it.

It attacks a hard, hard problem and I’m super happy that it will eventually replace Mathematica so that anyone who wishes can see how the black box works.