With Finance Disgraced, Which Career Will Be King?
nytimes.com
nytimes.com
Lazy!?! Investment bankers tend to be douchebags, but they put 90-100 hours per week, 50 weeks a year. Sure, there's a lot of face time to be put, too... but "lazy" is not the word.
I get the impression you don't even know what you're talking about. There are many areas in the financial industry: investment banking, trading, risk management, insurance, private equity. These areas attract all sorts of people, with all sorts of academic backgrounds and personalities. Traders are completely different beasts than, say, investment bankers.
"That being said, 90% of the "quantitative finance" world was and still is utter nonsense that legitimately drains other fields of technically savvy people, so it will be good to see them in other places."
Nonsense. There are simply not enough positions in academia and industrial research labs for all the Math, Physics PhD's out there.
compare this with careers in CS... dont know about the valley, but here in Sydney, engineers rarely negotiate for salaries and benefits the same way bankers do (ie directly arguming risk and rewards). Having to work crazy hours for "prestige" is still the norm... and engineers are treated as "costs" in most organisations...
Also, it's not the case that the most talented undergraduates pursue careers in finance. It's more accurate to note that finance is a backup plan for the most talented people, because it's available and pays well. Only the douches specifically tailor their college experience to getting an investment banking job. So to the extent that there are a lot of talented people in finance, it's because a lot of smart people end up falling back on plan B, usually because of the intractable systemic problems and corruption within academia and the sciences.
He doesn't use them as his main strategy, but if he is, e.g. betting that GM will go bankrupt, he still wants a quant to tell him which CDS to buy, or to determine what happens to his portfolio as a whole if X happens to the market.
It would have been better if you mentioned Renaissance or one of the funds that are actually driven by quant strategies.
It's also very unlikely that Soros is going to have an undergraduate building new quant models in his first year. If he's lucky, he might get to write the code to test someone else's models. There really isn't an undergraduate course that sets you up to be a quant, and most quant jobs are unattainable without a PhD.
An MFE degree (Master's in Financial Engineering) can give you the basic skills expected of a junior-level quant trader, but tends to underplay a critical component: programming. (Most quant jobs are programming jobs; unfortunately, the lingua franca is C++, and at most financial firms, the quants are strong mathematicians but third-rate coders.)
Not really, you just need to do your summer internships at hedge funds and make them lots of money.
Truer words have never been written. Various friends of mine who are former mathematicians / physicists now working as quants do rock at stochastic calculus, but suck at C++. Maybe a solution would be to separate the coding tasks from the modeling tasks. A friend of mine recently took a quant position at a hedge fund, and while he gets to do a lot of modeling and data analysis, the actual implementation is carried out by a 1st rate coder with whom he works in tandem. That sounds very smart to me...
I am not supplying a guess now, because this comes as a total surprise.
I'm not very good at math but I'd prefer working through a trigonometry textbook to working on another ruby on rails website.
The type of programming and the language matter a lot. Most PhDs despise programing because of the problems they encounter in the professional sphere: most numeric programming focuses on details (numeric behavior of algorithms, efficiency in speed and memory use) that most researchers would find boring. A cutting-edge algebraist doesn't want to spend his time cutting clock cycles off of a vanilla matrix multiplication, nor does an academic analyst ("analysis" being a specific field of math, as in real/complex analysis) want to spend his time fretting over the (often jarring and unpredictable) discrepancies between floats and real numbers. There are people who love those kinds of problems, but they're rarely research mathematicians.
I find cutting clock cycles quite gratifying. Admittedly there is less math in that than having a bottom-up understanding of what's going on. But you could also reframe it like any other optimization problem, given some number of inputs of a certain type. You can also prove your solution correct. It is a math problem all over.
Is it safe to say that those that despise programming, also despise certain branches of math?
I should add a little story. I once asked one of my friends who is very gifted in math why he prefers CS instead of pure math. His answer was something like: CS is the only field where mathematical truths can be immediately applied to reality (within the machine). It's a good balance between limitless mental masturbation and unpredictability of nature.
Yes. At the graduate level, the various branches of math are quite different, especially between pure vs. applied. A logician would probably not enjoy a course that involved a lot of PDEs, for example.
Speaking strictly for myself (physics grad), it's easy for me to get caught up in some sort of interesting data analysis, but programming can be a bore because it involves so much extra stuff. I firmly believe that this is the reason software like Matlab survives: not because its analysis functions are faster or better, but because it tends to push everything but the math and visualization out of the way.
Writing code requires knowledge of code conventions, syntax, and as importantly, the libraries. This is a declarative/episodic memory task, less so of working memory, symbolic manipulation, and abstract reasoning task. The latter traits are dominatingly important in math/physics. In coding there is a mix of the two, with the former taking precedence after the program logic has been deduced.
Which brings about the next question. The mathematician part cannot be learned merely through patience, but becoming expert at a language can be. Now, why is it that your brilliant math/physicist friends cannot become such experts? Do they lack the patience? Or, does coding simply not "click" with them? Is there a causal relationship? Now my intuition says there is none, and so we are back to square one: it is perplexing that they are not good programmers, unless there is some personality reason behind it.
It doesn't help that they're trapped in C++ and an environment that rewards guts-'n'-glory over finely crafted code.
I strongly disagree. Finance is not Theoretical Physics. In Physics, the best and brightest are in Academia and have access to high-quality experimental data (unless you're doing high-energy stuff, where experimental data is hard to get). In Finance, the best and brightest are in the financial services industry, and the finance academics have no access to high-quality data because such data costs millions. Data aside, the kind of Finance which is taught in college is somewhat of a fantasy. I will be crude and claim that Academic Finance is as scientific as literary criticism...
Cutting a long story short: anyone who's proficient at building models (like a physicist or a math-oriented engineer) can build models for a hedge fund without having been trained to do that in college. At D.E. Shaw they like to say that "you can teach smart people how to do finance, but you can't teach financial people how to be smart".
I submit that you are not aware of what is actually taught in academic finance. What principles of it do you disagree with?