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Comment by chollida1 | Hacker News Reader

I liked this article because the roll of the programmer on wall street has been going down recently from my perspective.

Programmers used to work along side quants and were well respected. This was generally because practicing quants didn't used to be able to program. This was especially true in the 80s and 90's where programmers and quants where almost valued identically as one required the other to make things happen.

Somewhere around mid 2000's most quants started to be able to program pretty well. Not necessarily with C++, though lots (especially former physics) could use C++, but certainly with mat-lab, etc. This really shrunk the required programmer head count,

This, coupled with the fact that few programmers were trained in fields like stochastic calc, and the advent of offshoring meant that programming started to be come a lower status job around this time.

Some relatively small fields like HFT kept good programmers in need, but these jobs are relatively few and far between compared to the sell side bank jobs.

Now, programmers are much more valuable/respected once again, due to the requirement for top notch software, not even as a competitive advantage, but just table stakes to compete in the markets.

And like most fields programming in finance has really started to specialize:

- lockless programming, low level Linux, user mode network drivers, etc for HFT

- distributed systems, low latency messaging for quote dissemination in large systems like what most sell side banks run.

- real time risk limits, web UIs for helping to visualize and alert portfolio risk

- "production" modeling of quantitative models, for those that can span the programming/math boundary

View on HN

> This, coupled with the fact that few programmers were trained in fields like stochastic calc,

Anecdotally though, I've met plenty of coders who did this to themselves by refusing to learn more about the domain or the business.

They basically silo'd themselves, then wondered why their colleagues didn't treat them as an integral part of the team when they couldn't speak the language or understand the concerns.

Taught myself enough stochastic calc to change and validate pricing models while on the job.

Coders who understand their domain well are immensely valuable, and are easily worth at least 3x, because they don't over- or under-engineer a solution, and because they can conjure up with technological solutions for problems that nobody else in the company can even conceive of.

> Coders who understand their domain well are immensely valuable, and are easily worth at least 3x, because they don't over- or under-engineer a solution, and because they can conjure up with technological solutions for problems that nobody else in the company can even conceive of.

This is a crucial point to me. Being able to code is good, but being able to code well while also having an intermediate or expert understanding of the domain that you are working within is what is going to set you apart in the long run.

In the industry, developing software can usually be seen as the process of creating a tool that will help to better solve a problem. It seems strange to me that you would want someone who doesn't have a solid understanding of the nature of the problem (or the solution) to be designing and building the tool, just because they claim to be good tool-makers.

> It seems strange to me that you would want someone who doesn't have a solid understanding of the nature of the problem (or the solution) to be designing and building the tool, just because they claim to be good tool-makers.

I couldn't agree more and this is my main objection to "AI will replace [insert any job here]".

A lot of problems are inaccessible to programmers just because not enough of them seem to be willing to understand them. Complex rules about accounting in large companies seems to be one of them for example. This is why I think AI will certainly overtake many professions but mostly professions that are required on a large scale and that are easy to understand: driving, cleaning a house, building a house, ironing, cooking, assembling objects, etc. For complex accounting or legal issues, I am a lot more skeptical. You don't need complex AI to run accounting systems, they can easily be done with regular software. However in large companies you still have huge accounting departments booking and maintaining these complex logics by hand (excel), a lot could be automated now. And the same reason why they haven't been automated in C# now will apply to AI in the future.

Re your AI thesis, I think it’s the exact opposite. Deterministic, rule-based processing applied to lots of similar data are perfect for AI-fication. It’s all in the computer, and you can kick out to a human-driven exception process when required.

All that physical, real-world stuff you mentioned (cleaning, cooking etc) is vastly more complicated, riddled with experience-driven subjective judgements (is this paper on the floor trash or should I put it back on the desk?) and highly situational. Extremely difficult to generalize and handle with an AI. Not to forget it’s messy stuff in the real world, with engineering and hardware and grease and failures.

Most of the complex accounting and legal questions that these departments are doing manually aren't completely trivial either (we are not talking about just adding assets). But the determination of whether the paper on the floor is trash or not is something that pretty much any AI professional can apply his mind on (and will likely do given the size of the market), whereas very few will apply their mind on how IFRS should treat a tax asset in consolidation when the corresponding tax treatment under USGAAP is a still in discussion.

If you look at self driving cars, they are already doing the sort of wizardry of your trash example when analysing the other objects in sight.

And again it's not so much a matter of technical complexity, it's a matter of the domain being inaccessible to those who can best automate it.

>Most of the complex accounting and legal questions that these departments are doing manually aren't completely trivial either (we are not talking about just adding assets).

These are exactly the types of problems that machine learning is perfect for. Problems which involve chains of nebulous decisions that would be difficult to program traditionally.

Couldn't agree more. I have met so many programmers in banking who seem to actively avoid having to learn anything about a bank, not even complex math.

In theory, project managers are supposed to bridge the gap between the business and programmers, however my experience is that they usually understand neither the business nor the IT side, and are only adding more confusion.

People with both knowledge of both worlds are incredibly rare and valuable.

what then is the best approach to learning how a bank works? where would one such programmer start?

Work for a bank.

>Anecdotally though, I've met plenty of coders who did this to themselves by refusing to learn more about the domain or the business.

Anything outside of learning enough to do your job should be at the business's expense.

1) some fields are not good for self-teaching. It leaves the possibility open to misunderstanding and writing code to that misunderstanding

2) the business will probably have a good idea of conferences and workshops that impart the knowledge the business is looking for

3) this is more fuel for "unpaid studying outside of work hours"

Based on posts like this, it seems really dumb to enter software first -- better to get a degree in some other technical field and just teach yourself to code.

If it increases your value and allows you to demand a higher salary, that is at the businesses expense. You are a business expense.

It'd add even more value if companies spent more on proper training. Maybe even training geared for software devs learning the field from that perspective if that's available.

But if they think I can become a domain expert by reading junk on the internet with no one really verifying my skills, I'm happy to take their paycheck.

In many environments, you probably can do a lot of that learning at work, just by talking more than strictly necessary to people having the knowledge.

> Anything outside of learning enough to do your job should be at the business's expense.

There's no "should" here — it's an open market with a lot of agents. You're free to pursue certain working conditions and then look for employer that will agree with them. And another developer is also free to go an extra mile and ask something extra in return.

This is why I'm against any kind of unionizing for developers, by the way — too many different situations and opinions about what our working conditions should be.

I could not have formulated this better myself.

All but a few programmers I have met have tried to understand the underlying reason for their employment and the businesses issues they are employed to solve.

This approach have caused programmers to loose a lot of influence and status.

10 years ago companies had developers develop their own customized CRMs, which can really benefit a company if their domain-specific needs and processes can be integrated to such core-business software.

Nowadays, Adobe Campaign have a cake walk selling their bloated, general and non-tailored “CRM” solution to business.

How can they Adobe etc do this? They approach the marketing and sales team and offer a nice slide show.

Why does not IT or programmers even get involved before the purchase? Because no one likes talking to the idiots in IT that does not understand the businesses needs. They only nag about some “technical debt” (that no matter how much money is poured on the teams never disappears) and the need for re-writes of fully functioning parts of the system that introduces new bugs.

I apologize for the off the wall comment. Every time I read about wall street programming, I've got this subliminal voice in the back of my head wondering how anyone could find the motivation to do this work. I'm obviously revealing my biases against the financial industry here. Also, I'm unable to make myself do work if I don't see it contributing to some greater vision or cause. Are there people out there who love finance and learn these types of specializations on the job, or are they hired away from other industries lured by big comp packages?

I guess it's just a case of lack of empathy on my part. I just can't understand why anyone would want to put so much effort and skill into making bots for farming money for a bunch of questionable people.

I don't feel too guilty for saying this. Every time a story about bitcoin is posted to HN, people go off topic and start complaining about everything that is wrong with bitcoin. I don't see the same when we talk about finance in general, even though similar sentiments apply, maybe more so.

Cash motivates plenty of people, as does the joy in solving a problem. Whether the value of that solution to society's benefit is positive or negative does not always factor into a solution architect's moral calculus. This is how I explain your observed point to myself when I see folks stoked to work for $largetechco or $adtechco.

> as does the joy in solving a problem

This is it for me. Futures trading is a zero sum game (negative sum if you factor in fees), so writing a program to automatically extract value from an ever changing market is a nontrivial and ongoing project. But unlike a game, getting good at it can pay the bills in a real way. I understand that in the big picture long term, I'm not making much of a mark on society, but nevertheless it satisfies my personal and financial needs.

Markets are not zero-sum game it is a common misconception.

http://www.businessinsider.com/the-stock-market-is-not-a-zer...

That quote is misleading. He's talking about perceived price. The actual price of an equity is the price at which the execution occurs. And for every execution there are two sides, hence the zero sum game is the only game in town.

That's why I specifically called out futures trading. From [1]:

> In the financial markets, options and futures are examples of zero-sum games, excluding transaction costs. For every person who gains on a contract, there is a counter-party who loses.

[1] https://www.investopedia.com/terms/z/zero-sumgame.asp

You’re comfortable enough to be ethical about your capital, for me it would be a big constraint. I’m sure I’ll get to be picky someday but that’s years from now. And at least there’s cool maths :)

Some make a whole lot less than you and still feel ill at ease working for the finance industry when it seems to soak up so much capital and contribute so little to society

There's actually quite a lot of puzzle solving involved that makes it interesting. I think there are a lot of misconceptions of the industry at large and it suffers from bad PR after the global financial crisis. It's an interesting software problem to try and write algorithms that can earn alpha regardless of what is happening in the market. If anything computers have made our markets more efficient and it is great for price discovery.

It may not be the same as creating a product or service that people love or solves a need, but it is an interesting problem to tackle.

See that's the thing. I don't know what "earning alpha" means and why I should care, and working on "price discovery", which is also something I am unaware of, sounds more like a punishment than a reward.

Price discovery means that anyone can find a fair price for some asset. For example, algorithms that provide liquidity in agriculture products ensure that farmers can easily liquidate their inventory, as well as hedging their risk through derivatives.

I wouldn’t close your mind to it. Finance attracts “questionable people” but finance is also very interesting on many levels and is a central part of life. Work through some finance math. Calculate an IRR. See how it works. If anything there’s a lot of great human history in it.

Thanks. I'm trying to be diplomatic here with my criticism and appreciate the positive and informative responses despite my negativity. You are right, finance is critical to social function and perhaps I've only been focusing on the negative aspects.

alpha is a return in excess of what is expected. If you invest in a low cost index fund you expect alpha of 0 as compared to the index the fund is mirroring. If instead you put money in a hedge fund, alpha is the difference (positive or negative) between the returns the fund gets vs some benchmark like the S&P 500. Negative alpha is bad, positive alpha is good. Earning alpha means you are beating "the market".

There's also beta, which despite being the next greek letter, isn't the same at all! Beta is a measure of the price correlation between an asset and some benchmark in terms of volatility. Beta of 1 means that the asset moves in lockstep with the benchmark. Low beta means the asset doesn't move as much as the benchmark and high beta means the asset moves a lot compared to the benchmark. Tech IPOs are often high beta compared to the S&P 500.

Anyway, finance has a lot of intellectually challenging problems that happen to overlap well with people trained to build mathematical models that attempt to describe stochastic processes. CS, Physics, Stats, some branches of pure Mathematics -- all have direct applications in the work they do to some aspect of being able to understand and predict markets.

Appreciate the explanation. Thank you.

I think it helps to understand that the financial sector provides capital that serves to energize virtually every other sector in every industry.

Without finance, there is no biomedical research (private especially). Without finance, there is no aerospace advancement. Without finance, there is no alternative energy. Being able to facilitate a more liquid, more transparent financial sector is, in my opinion, a calling worthy of any programmer who seeks to make the world a better place.

Your assignment of people as 'questionable' is likely an artifact of the 2007 recession, and that kind of thing is a personal choice. I can guarantee you that there are 'questionable' people in every sector and in virtually every company. Sometimes people are great, and sometimes they aren't. Their field of employment has very little to do with what makes them that way, and I think that it's a little ignorant to be so casual (and I say this because you are certainly not alone in your judgment) with how you view people.

Remember how, as children, we are taught to not judge books by their covers? Why do the same with a programmer who works in finance? Sure, some of the work may be a little pedantic, like squeezing an extra millisecond out of an algorithm, but hey, that's computer science in general, and I liken that to an F1 racing team spending hour upon hour sculpting the perfect frame for their car.

Sorry for the rant, I've spent a decent amount of time working on financial algorithms, and what you said touched a nerve.

Have a great day!

WELL said! :)

I stumbled into finance a few years ago and I’ve had overall the best bosses and work env ofanyone I know. I’m also doing a more audacious program of research engineering/ computer science than I could likely do anywhere else.

I like to sometimes describe my work as some combination of “making the systems that fund aerospace at least as reliable as commercial aircraft”, as transparent as intergalactic vacuum, and easy to use to boot! Or at least that’s the idea :)

On the hft front I recently started at poking at how to get accurate time on a dev computer, which gets fiddly the moment you want really interesting accuracy on commodity hardware :)

Thanks for the praise, and for the insight per your experience. Sounds like a great gig!

I looked you up, and see that you are likely working exclusively in Haskell, but thought you might derive some value from Carl Cook's presentation on optimizing HFT code at the most recent cpp convention. I recognize the languages are distinctly different, but he provides some interesting theoretical points along the way that might be advantageous to you.

Here's a link: https://www.youtube.com/watch?v=NH1Tta7purM&feature=youtu.be

Also, I can sympathize with your plight to run scalable sims. I've done some work in bioinformatics, and am building a small cluster at home so that I can learn to write code that'll scale to more massively parallel systems that are de rigueur in that domain.

Cheers!

I’ll have a gander! Thx for the link. I do code in other stuff when it makes sense ;)

Yeah building stuff that works easily in the small and sanely in the large is a fun challenge. Also hard.

Possibly because of your original comment, or perhaps unrelatedly, I’ve been lately saying “finance done right is the lock free wait free scheduling algorithm for moving society’s resources around” —— all the other stuff folks think of as finance is really just icing and fancy wrapping on top of that core truth

As someone who works (hard) in the part of finance you're describing, it's a mix of a few things. From a purely intellectual standpoint, it's a very hard, very interesting quantitative/modeling problem to solve (ie. predict the price N seconds in the future is non-trivial). It's an extremely competitive field (you vs. other teams like you in the world competing for a slice of the pie), and you get results back from your experiments very quickly, so you know exactly where you stand. And finally, to your following point --

>Also, I'm unable to make myself do work if I don't see it contributing to some greater vision or cause

This simply is not something I experience. I've never felt any particular satisfaction from that particular aspect of a job, it's just something that never crosses my mind and incentive me in any way.

You are completely ignoring the enormous value that financial activities provide for society. Efficient capital markets, risk pricing and exchange are fundamental ingredients to an effective economy. Do you think these businesses get paid for nothing?

>farming money for a bunch of questionable people.

The "questionable people" include grandparents, firemen, teachers, etc with pensions and retirement funds.

>I don't see it contributing to some greater vision or cause. [...] I guess it's just a case of lack of empathy on my part.

Your sentiment is common and I think it's caused by people not connecting the dots from grandparents' retirement pension to the hedge fund trader.

As one example, at the micro level, grandparents are depending on a pension.[1] They also don't want their _real_ purchasing power to diminish. The "real" not "nominal" purchasing power is an important distinction because if the price of bread is $2 in 2017 but becomes $4 in 2037, they want to have adequate future money to buy food. In other words, they want their money to grow and keep up with inflation.

Your grandparents stashing money in a savings account paying less than 1% will not protect their purchasing power from inflation. Likewise, the pension manager that oversees a $1 billion retirement fund to pay retired teachers will declare it bankrupt if it only gets a 1% return by buying Treasury Bills. The pension's assumptions to avoid insolvency might require 8% or better annual returns.

Therefore, all these participants in the economy are looking for better returns. You can't get 8% from savings accounts and t-bills. That's where money managers like private equity, hedge funds, and VCs in Silicon Valley come in. They sell their ability to generate higher returns. This expertise attracts capital from entities like pension funds.

So basically, a bunch of programmers are fine tuning algorithms because [...connect a bunch of dots...] your grandmother doesn't want to be a starving destitute and live under a bridge in her retirement years. If you multiply millions of everyday people not wanting to be destitute (macro level), you end up with hedge fund managers with billions to play with.

That said, can we "reconfigure society" so that all this competitive activity of shuffling money from one pile to another isn't done? Maybe. It would involve fundamental changes that we all can't agree on. For example, if you stop inflation you can stop the incentive to generate returns that try to beat inflation; but then some would say that "deflation" would lead to people hoarding money and the economy would crash. Inflation is the current winning ideology for the modern economy. It's hard to see how we could alter society such that Wall Street traders go away.

[1] for example, the $300 billion California Public Employees pension fund provides these benefits: https://en.wikipedia.org/wiki/CalPERS#Benefits

> That said, can we "reconfigure society" so that all this competitive activity of shuffling money from one pile to another isn't done? Maybe.

Your proposals boil down to ending deficit spending. Aside from the authority issue (no single entity has authority to do this, not even congress, definitely not the president), that means the US Federal government has to cut $650 billion dollars in spending.

Or to put it more directly: We currently have pensions, social security, an army (meaning having an army at all). Pick 2. The other one gets destroyed.

Still sounds reasonable ?

You wouldn’t be able to type this comment on your computer (and neither would I) were it not for financial markets to organize funding for the company that produces your device. Or you might not have gotten a mortgage to buy your home.

Financial markets serve a hugely important social function of allocating capital (intermediating between people who have money and those who need money).

Finance is a vast world and unfortunately too often reduced to pure speculation.

First you have basic lending and borrowing activities. The bank can afford to pay you interest (well not now that interest rates are at zero) only because your money is invested, usually in loans.

Then you have payments, cash management for companies.

Then you have more complex services offered to larger companies, raising capital (equity and debt) on the market, helping them manage their risk with derivatives (interest rate, currency, commodities (oil, metals, livestock, etc prices), inflation, etc) plus some advisory on corporate actions (mergers, IPOs, etc).

You have insurance, reinsurance.

And then you have asset management, which you can call speculation if you want, but which is essentially people managing investment portfolios on behalf of savers, pension funds, insurance premium for long term risks, etc. With a wide variety of approaches from very conservative money market funds which invest in highly safe and liquid assets, to trackers who try to replicate a benchmark by over performing it by a little, to investments in illiquid assets (property, non listed companies) or very aggressive/leveraged strategies (hedge funds). Fundamentally what they are doing is to ensure your money gets invested wisely (at least they try).

And of course all sorts of intermediaries: consultants, brokers, market data providers, research (sort of financial journalists), prime brokers (who provide financing when you leverage liquid financial assets), system providers, auditors, rating agencies, etc.

Now you could call everything speculation: when a bank lends you money, it bets on your financial soundness. When an investor takes the opposite side of a commodity (say oil) transaction, it bets on the price of oil. But that allowed you to get money to run a business or to offset an oil price risk that could have made you lose money if oil increased (say your are an airline company). There is no real dinstinction between risk taking / risk transfer and speculation. But in most instances it does have a social benefit.

I do HFT and think about this a lot. I am essentially a middleman that facilitates trading across:

1. Time - I quote buy and sell prices continuously in Microsoft stock trying to earn the spread between them. You want to buy stock and my offer to sell is the cheapest in the market. We trade. Later, someone else comes along to sell and I have the highest bid, so I buy the stock back from them.

In between I'm exposed to price fluctuations, so sometimes I make money and sometimes I lose, but I make a profit on average by charging a spread between my buy/sell prices and predicting small price movements. The two of you could have met had you waited, but I let you lock in a sure thing by bearing risks you didn't want. Think of this like insurance. Odds are you spend more on car insurance than you're expected to receive in payments, otherwise the insurers would go out of business. But you probably prefer spending $1000 a year vs. spending $0 most years and $30000 once in your life.

2. Place - You're in the US and want to buy Nokia stock. Someone in Finland wants to sell for a cheaper price. You don't have access to the European exchanges and she doesn't have access to US exchanges, but I do. I trade against both your orders and earn a couple cents per share in profit. I helped you meet halfway across the world and also keep prices efficient to reflect global supply and demand.

3. Product - You want to invest in an index ETF that holds 40 different stocks. I quote an offer to sell based on where they're trading in the market plus a small profit margin. You buy my offer. I turn around and buy the stocks to hedge my risk.

I'm better at trading than you are and have very low costs. Even considering my profit margin, it's cheaper and less risky for you to buy the ETF from me than 40 individual stocks. I keep the ETF and stock prices aligned and also helped people who wanted to sell stocks get their orders filled. Win win win.

I think the work I do clearly benefits the market and natural investors. All of these trades are competitive too, so I can only earn razor thin margins per trade, or someone else will undercut me.

I do sometimes question how the market picks winners and losers, typically based on speed. Is someone whose system is hundreds of nanoseconds faster more deserving of arbitrage profits? Do high technology costs naturally lead to consolidation and reduced competition? https://faculty.chicagobooth.edu/eric.budish/research/HFT-Fr... this paper has some interesting thoughts on the topic.

FWIW I do think continuous price-time priority trading is flawed in that it creates an arms race in speed, but it's the least bad option. Other mechanisms like batch auctions are even worse. As a thought experiment, consider the #3 ETF trade I described. If I can't immediately hedge my risk and instead go into a batch auction for each stock, how will that affect the price I offer in the ETF?

PS: I do think it's a fun job. You get to play with cool technology and it's like a game that gets harder every day against very skilled opponents. Even the arms race isn't all bad. HFT firms have effectively bankrolled modern innovations in high speed ethernet, FPGAs, low latency kernel bypass networking, etc. that have knock-on benefits for other applications.

> As a thought experiment, consider the #3 ETF trade I described. If I can't immediately hedge my risk and instead go into a batch auction for each stock, how will that affect the price I offer in the ETF?

My idea for this is that when you rest an order, you should be able to attach a set of hedge orders to it that will initially be inactive, but will fire when the owning order is filled. This would let everyone get hedges done at better-than-HFT speed, and make things like speed bumps or batches a lot more tolerable for market makers.

You'd want some kind of pro-rata, or multiple orders at fill thresholds, so you could show big size and respond sensibly to partial fills. You might want alternative hedges to cope with price moves in the hedge target. You might want some mechanism whereby the exchange will pull the owning quote if the hedge disappears. There's all sorts of fun you could have.

For this to work really well, you'd want the hedges to be processed synchronously with the fill of the owning order, so there's no HFTable window of vulnerability between fill and hedge. That couldn't be done across different matching engines in the typical architecture current exchanges use. For futures, though, it might be workable - i think all the different expiries of a given underlying, and their spreads, are already handled synchronously, so that the exchange can do implied matching. That might not include some of the more exotic constructs which aren't in the implied chain, though.

This sounds similar to OneChronos, though I don't know if they've launched anything: https://www.onechronos.com/

You're right that there's precedent for this:

-Implied engines as you mentioned where traders can atomically express a view on the term structure without legging risk. For the benefit of non-finance readers: Say you believe the fair price difference between Dec and March futures is 2 index points, you could quote in the spread between the contracts (long one, short the other) buying 1.75 selling 2.25 without being fastest to respond to every shift in the index itself. Your order in the spread will create implied orders in the underlying contracts themselves and you can only be filled if both your long and short trade.

-IEX's D-Peg effectively runs a high frequency pricing model inside the matching engine to predict when an adverse price tick is likely.

-I think D.E. Shaw has a patent on a domain-specific language for complex orders where they can be priced off any other instrument(s), ratios between instruments, features of the order book, etc.

The real problem with batch auctions is coordination. So long as you have other exchanges trading correlated assets in continuous time, there will still be a race to adjust orders in the batch auction market after a pricing signal occurs. Even with a random delay or crossing time, it's still beneficial in statistical expectation to be faster.

You'd need to trade most similar products worldwide on a single platform. Since exchanges are a network effect business, this would likely lead to monopoly profits for the exchange operator.

I'm not sure "no high-speed arbitrage/monopoly exchange" is net better than "some high speed arbitrage/competing exchanges." I suppose you could have the government run the exchange as a utility, but that would stifle innovation. A lot of things we now take for granted started in experimental ATS and ECN startup markets.

Doesn't this sentiment preclude you from almost every programming job?

It's almost always going to be about finding the optimal way to funnel money toward whoever is in control of your employer.

Yes, it took me about 20 years to find an employer I am happy with, and that included myself for a while in the list of those I wasn't happy with.

May I ask what industry you ended up in? I assume it's something that you feel is adding value to the world?

> how anyone could find the motivation to do this work

There a lot of challenging problems in the finance. Some people like the problem solving and $$

> I just can't understand why anyone would want to put so much effort and skill into making bots for farming money for a bunch of questionable people

Its making money for yourself as well. Many jobs in Wall Street at % of profits based rather than a fixed salary.

My feeling is that most criticisms of finance are based on a combination of a lack of understanding of what finance is and does, and indignation about how much money some people in the industry get paid. It's any easy target. Absolutely there are 'questionable people' in it, but are programers focused on getting users to click on more ads or spend time on a given app any better? Is tech really saving the world? There is so much more to tech than that, and most people in tech don't feel that's a fair representative of what they do. I think finance is similar, but I don't work in it so maybe I'm wrong...

Most of the quants and quant devs I work with are out-of-work physicists who want to provide for their families. Most of them would rather be tenured. I work in this industry because I cannot find employment in my field of engineering near my friends.

I don't work in finance, but I see the modern global financial system as one of the greatest achievements of humankind and one of the main reason behind humanity's prosperity. I would love to work there if I had the skills or patience to gain them (instead, I work in gamedev, where I acquired immense domain knowledge over the years).

To add an angle from someone who shares your concerns about the financial industry, the high pay makes it so you can donate large amounts of money to charitable organizations of your choice.

It's actually a recommended route in the effective altruism community for those with the aptitude.

I just can't understand why anyone would want to put so much effort and skill into making bots for farming money for a bunch of questionable people.

Be aware that a large part of the Internet industry consists of persuading people to click ads, in order to enrich the Saudi sovereign wealth fund.

https://www.nytimes.com/2017/11/06/technology/unsavory-sourc...

Does that float your boat?

Has offshoring ever been a significant factor in this arena? Given the profoundly proprietary nature of the systems being built, I would think that unlikely. Offshoring development is a good way to find your custom software reskinned and sold to a competitor without much legal recourse.

Also, is 'mainstream' programming that common of a need? I had read (here on a HN comment thread) awhile ago that many organizations use commercial languages that simply aren't available outside of the financial services sector (I forget the name, it was 1 or 2 letters... KQ or something like that, an array programming language whose code looks like APL). I wondered how people broke into such a market. It's always seemed like an environment with interesting challenges which would have pretty objective goals and practices out of need.

Huh. I see C++, Java, and Python as the go-to languages with my wall-street programming and modeling acquaintances. Very little esoterica.

Jane Street's famous for its obsession with OCaml.

Honestly, OCaml is hardly esoteric. It's not a major language, but it's not a specialty language either. I'd put it in the same category as Elm, Erlang, or even something like Julia. Scala takes a ton of inspiration from OCaml, to the point where you pretty much feel like you know one if you know the other (at least speaking for myself that's been true).

https://en.wikipedia.org/wiki/K_(programming_language)

You are thinking of Q and Kdb which are used to process high throughput tick data.

Yes you are exactly correct! Kdb and the Q language that back it. I thought that was really prevalent in the trading arena just based on other postings I'd come across on HN.

Additionally, financial institutions are getting geared up for major participation in the cryptocurrency markets. Will be interesting to see how that changes the landscape.

To be fair, quant vs. programmer is a false dichotomy since most quants did degrees like mathematical finance, actuarial science, etc. where computer science and numerical programming courses are part of their degrees.

Depends where you go. Some firms have a very bright line between "quants" and "programmers", and you don't want to wind up on the "programmer" side of it.

Agree 100%. First firm where I worked the programmers were treated like monkeys, and the traders, some of whom weren't even that bright at the time, were almost godlike.

Some other person wrote on here about traders being angry assholes. That firm had a ton of angry asshole traders because they'd push and push and push on deadlines, didn't understand the system at all, got hacked up buggy code, never invested in unit or system tests. It was an absolute disaster.

Little anecdote: First year I was out with a more senior trader on my team over drinks. He was talking about the glory days of 08 where every single trader earned a million dollar bonus or more. I asked about the one infrastructure developer who came up with a system to use multicast to simultaneously publish our EuroStoxx signal to DAX along with a dozen other instruments. Nothing earth shattering in 2017, but it quadrupled our P&L and market share at the time.

He got 10 grand.

Thanks for the detailed response. A lot of good stuff to Google.

I can program way better on average than a quant, but what does that matter to a quant

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