8 ms·

Getting a Job in a Top Tier Quant Hedge Fund

110 points by shogunmike 13y ago

spot 13y ago
Two Sigma (where I work) is hiring for a variety of positions, not just Math/Physics types but security, systems, UI, networking, etc. anyone with a serious love of and talent for technology should consider it. i left google for two sigma and am loving it, especially the people and culture. feel free to ask me about it either in this forum or by email. http://www.twosigma.com/careers.html http://www.twosigma.com/careers.html
- vonmoltke 13y ago
  I may have sent my resume to Two Sigma a couple years ago. If I did, I never got a response. I was really excited when I found out you had a Houston office, but somewhat deflated when your careers page put all the interesting jobs in NYC. I get the impression Houston is basically just an IT/infrastructure office. Is that the case?
  - spot 13y ago
    The Houston office is mostly infrastructure and data analysis, but we're always looking for good people more than specific roles. Most of the company is here at the HQ in SoHo.
- canttestthis 13y ago
  I understand if you can't answer this, but how does the pay for software engineers at Two Sigma compare to pay at top tech companies, like Google? Glassdoor is ambiguous.
  - spot 13y ago
    I got a raise, but salary is only part of compensation. In the end it will depend on how the stock does (at a tech company) or what your bonus is (in finance).
    - canttestthis 13y ago
      I've read elsewhere that unless you're in a role that directly generates revenue (traders, etc.), you shouldn't rely on bonuses in finance, and should instead maximize the cash portion of your compensation. I assume this would be true for software engineers at Two Sigma too.
      - jchendy 13y ago
        Two Sigma, more than most other companies (financial or otherwise), understands that innovation and success is largely driven by technology. The content of twosigma.com is designed to communicate this, and it's absolutely true. Anything you've heard about how other companies are structured is unlikely to apply here.
      - joonix 13y ago
        I've seen evidence to the contrary. CS guys who get mega-bonuses based on fund performance. And no they don't even work on HFT.
- busterarm 13y ago
  I did a year at DESCO in Systems (didn't go so well, I made some mistakes) and everything that I hear about Two Sigma is that the place is awesome. The number of postings you've had recently has _exploded_ since I last looked at you guys around 2009-10. I would definitely recommend people look into this place and might consider it myself if I thought they'd ever hire me (not likely).
- nachteilig 13y ago
  How did they entice you away from Google initially?
- HockeyPlayer 13y ago
  I was surprised to see an investor relations page. Most prop groups aren't actively looking for more money. And they talk about clients, which is unusual. Can you explain?
ruang 13y ago
Does this mean that most MFE degrees lead to risk management instead of quant trading?
- shogunmike 13y ago
  I would say it's easier to get a job in risk management (likely in investment banking) than quant trading coming out of an MFE degree. This is primarily a consequence of how the MFE programs are set up, what they teach and the network of the professors etc.
  - ruang 13y ago
    So quant funds don't use that much calculus? Primarily statistical techniques? I would guess that might be the case since pure arbitrage no longer works and thus quant funds have to delve into more probabilistic strategies like stat arb.
    - shogunmike 13y ago
      Yeah, this is pretty much the case. The quant derivatives pricing teams at banks are where the stochastic calculus folk tend to head to. Their teams are generally highly respected in this area. Also, banks are doing a different job to funds. Banks are generally interested in assessing the risk or trading risk of these products, either on prop (i.e. with their own funds) or to clients. Funds tend to concentrate more on statistical/machine learning/econometrics research approaches. The culture is generally more like a research institute thank a bank. They tend to hire more PhDs from Comp Sci, whereas banks will hire directly after MFE or straight out of undergrad.
      - deleted 13y ago
        [deleted]
      - ruang 13y ago
        Is that why physicists (vs computer scientists) are no longer recruited as actively for quant trading roles? It seems like all the low hanging fruit has been arbitraged away. I've worked with a Math PhD from Princeton before in prop trading and he always lost money.
tom_b 13y ago
Quantitative trading seems interesting because I would hazard that you need strong math background along with solid hacking skills. There are other problem domains with similar requirements, but I'm quite curious to hear stories from other HN'ers who have tackled quantitative trading either for themselves and in the day job. Specifically, if you can share a bit on your technical work in such a role, that would be cool to hear about.
- shogunmike 13y ago
  I was a quantitative developer working alongside a quantitative trader in a small 'proprietary trading fund'. This is roughly how all quant funds are separated. There is the "technology" side, which builds the data/trading infrastructure and then there is the "research" side that generates the trading strategies to run on the infrastructure. My job involved anything from hooking up to brokerage APIs to optimising MySQL replication topologies. Quite varied! In a way, it wasn't too different from your average startup, with the possible exception that you deal with a non-trivial amount of data from day #1 (hundreds of millions of rows are not uncommon). Open source has gained significant ground in funds these days. Python/R are now the "default" go to languages for quant trading research, with some MatLab too. Libraries such as NumPy, SciPy and pandas have really brought 'algo trading' to the 'retail' (algo) sector as well. .NET is still generally used quite a lot in investment banking, particularly C# for front-office GUI code, and C++ for any legacy number crunching libraries.
- alexkus 13y ago
  > Quantitative trading seems interesting because I would hazard that you need strong math background along with solid hacking skills. Strong maths knowledge can be good for general developer roles anyway. It's one (small) reason why I did a maths degree part time (Open University in the UK) to complement my existing Comp Sci degree. I'm sure you could get a better bang per buck picking and choosing specific areas rather than an entire degree but that wasn't my motivation (I'm equally interested in both in general). A good number theory course (even just plowing through Crandall and Pomerance, or Apostol) will definitely help with understanding/analysing asymmetric encryption.
3327 13y ago
Hi, I worked in both roles. I did an undergrad in theoretical Math and MFE. Its particularly easy to get a risk management job. My first job was for 100k + bonus out of school for BNPP. It is a highly quantitative risk department and was one of the best (if not THE best) institutional risk management gigs on the street. I did not know this at them time but I started in 2007 and after 2008-2009 I came to this conclusion. Anyway back to main subject. Risk jobs are easy to land and you can learn TONS or nothing interesting. Every shop has Risk integrated at different levels. Some shops its a backoffice type job where the risk guys are in the back seat (and this is the dominant case actually 8/10 I'd say). And rarely in places like BNP will you sit on the trading floor and have more power than traders. Yes traders will actually fear you... Rather than vice versa where Traders that are making money are big swinging dicks doing whatever they want (this is still the case at most shops). I started quant trading by chance when some guys running an arb blackbox were started constantly loosing money and were working late hours. I gave them a hand fixed a few bugs and word quickly spread. Next opening they offered me a position and I did an internal transfer... After I went to managing a portfolio (2 years after). And successfully did that for 4 more years. The summary is this. Quant Trading roles actually come in tones of flavors. Banks have option desks and in the recruiters will call these "quant trading roles". Hell, for all they know there is complex math involved and 'quant' sounds sophisticated. Truth is all option traders are proficient and calculus and derivatives to the point good traders are able to calculate pretty accurate 2nd orders in their head. And the tools available are also vast. But this is not a 'quant trading role'. A true 'quant' role is what some institutions have in house 'quant' teams that manage all the pricing models and libs. A 'true' quant trading role is stat-arb or some other arb strategy desk or similar type of strategy. Most banks do not have them anymore so its hedgefunds only. But even these vary vastly in quality. I know desks that would make 2-3 million a day net with very shitty hardware and patchwork system with lowlevel to mediocore guys working on it. And brilliant guys whom struggled (talking tier 1 guys, PHd MIT, princeton). So its a strange game and I would recommend going into a trading role into a medium level shop. Whats important is a good team and having a good vibe with the people you will work with. Trading is high stress and high emotion business so for your sanity in the long term its more important to work with good people rather than a top tier shop in the beginning.
- 13y ago
lutusp 13y ago
Quote: "However, a financial crisis in the Western hemisphere coupled with other macro/socioeconomic factors has lead to a reduction in scientific and engineering budgets and later-stage investment in such technologies." Translation: The recent worldwide economic meltdown was caused in part by quants' inability to accurately assess investment risks, or to influence decision-making, or both. The fallout was public distrust (justifed or not) of quants and what they do for a living. The bottom line is that reliable quantitative analysis hinges on the degree to which economics is a science. Economics isn't a science. Any questions?
- VladRussian2 13y ago
  >Economics isn't a science. A science is a method, not a domain or result or anything else. I.e. one can approach economics or medicine or traveling salesman problem using the scientific method, or one can approach it using woodoo.
  - lutusp 13y ago
    > A science is a method, not a domain or result or anything else. No, this is false. Science is defined more clearly than this. Science is not a method, it is a set of rules for creating a method. Primary among those rules are a requirement for empirical evidence in support of scientific theories, and falsifiability -- meaning scientific ideas must be testable against reality, and those that fail the test must be discarded. TL;DR: Science is more principle than method. > ... one can approach economics or medicine or traveling salesman problem using the scientific method ... By that reasoning, astrology is a science, because it can be studied using the scientific method. But this is not how science works. For X to become a science, scientific study must support the theories that define X. Explanation here: http://arachnoid.com/psychology/index.html#The_Architecture_of_Science http://arachnoid.com/psychology/index.html#The_Architecture_... Economics is not a science. Title: "10 reasons why economics is an art, not a science" Link: http://articles.washingtonpost.com/2013-08-09/business/41217034_1_economists-economic-data-10-reasons http://articles.washingtonpost.com/2013-08-09/business/41217...
    - 13y ago
lpage 13y ago
"A great way to get into such a fund is to apply as a software developer, with aspirations of becoming a portfolio manager" That's not a path well traveled, especially at banks. At good hedge funds roles are well delineated, and chances are that you'll be working hard enough at your day job that you'll have little chance to explore on your own. Policy may prevent you access to the interesting data sets (execution data and historical P&L is sensitive to reverse engineering, and market data is often subject to expensive licensing). For banks the issue is far more bureaucratic - different teams with different hiring budgets and lines of business yada yada. There are relatively few managers high enough to wall cross between back office (technology) and front office (trading) so there's a stochastic component to your success at moving internally based on what group you end up in and how well connected your MD is. It doesn't help that coders are usually the limiting reagent (and paid less than traders) so the firm's interests aren't necessarily aligned with your own. If you're passionate about trading and coding, HFT is a great way to go. Money makers come from all backgrounds (grad/undergrad/super technical/creative coder) and you'll likely have better control over your coding/research ratio.
- shogunmike 13y ago
  I think I may have suffered somewhat from selection bias when writing that, in that a lot of my friends/colleagues work at smaller shops, where they initially started as technology infrastructure developers and worked very hard to move over to the research side. For instance, these were the guys -running- the data infrastructure so they were looking at it all day, every day. After a while it was probably straightforward to test out intuition on patterns they may have seen. Thanks for pointing out that the difficulties in doing so at a larger firm.
Sukotto 13y ago
Despite the intense competition, it is still possible to shine as a candidate, but you must be very well aware of what the funds are after, and then make sure you are providing it to them. I think this is a truism for any role in any capacity in any organization. Just replace "funds" with the organization/manager/client/whatever name.
anonu 13y ago
The article makes a good point about MFE degrees. They're a dime a dozen these days and most of them can't answer simple interview questions about linear regression. Its pretty shameful, not so much on the student's part, but on the universities that graduate these kids fully unprepared for the jobs that they think they can get...
- hudibras 13y ago
  The article really buried the lead on this one. The bottom line is that it's flat-out crazy for anyone to get an MFE these days. They cost as much as an MBA and won't get you a job as a quant.
  - shogunmike 13y ago
    Indeed, I am considering actually writing an entire article on that whole topic. I haven't done an MFE personally, so I don't feel I can comment too much on what they're like, although I have a few friends who have. A lot of them simply went into research afterwards.
dunster 13y ago
Another solution is to write the algorithm but avoid the hedge fund - lots of suits, and they take most of the money. You're better off if you trade it yourself. People work for hedge funds because hedge funds provide mentorship and really powerful tools and lots of data to sift through. We're trying to provide all of those things, for free, at Quantopian. https://www.quantopian.com/ https://www.quantopian.com/ Check out our community (for mentorship), our backtester (very powerful, and open source), and our 11-years of minute-bar data - all for free.
anoncowherd 13y ago
Dear HN: Stop casually discussing working for a bunch of disgustingly greedy, full-of-shit, and downright evil sociopaths as if you hadn't noticed.
- hudibras 13y ago
  The title of this submission was pretty clear. If you don't want to discuss this topic, then don't click on the comments link. That's what I do when I see, for example, the word "Haskell" in the submission title...
Tycho 13y ago
Sometimes I think of the HFT and quant trading industries are like the Formula 1 of tech. A way for extremely talented people to apply their skills and compete with each other, with lots of money involved, but ultimately the technologies developed for the 'race track' make their way onto 'main street' in some shape or form. I'm sure all this research into ultra low latency infrastructure and live data mining is bound to come in useful somewhere else. Maybe this is off base but why be cynical.
kenster07 13y ago
Getting rich while play poker with others' pensions. And just like a casino, the only sure winner is the house.
bachback 13y ago
RenTech assembled some of the brightest technical minds in the world to trade purely quantitively. They did pretty well for themselves. Jim Simons, famous mathematician, former MIT professor and DIA code cracker, earned the following amounts according to Forbes: 2011: $2.1 Billion 2010: $2.5 billion 2009: $2.8 billion 2008: $1.3 billion 2007: $1.5 billion

110 points by shogunmike 13y ago

spot 13y ago

Two Sigma (where I work) is hiring for a variety of positions, not just Math/Physics types but security, systems, UI, networking, etc. anyone with a serious love of and talent for technology should consider it. i left google for two sigma and am loving it, especially the people and culture. feel free to ask me about it either in this forum or by email. http://www.twosigma.com/careers.html http://www.twosigma.com/careers.html

vonmoltke 13y ago
I may have sent my resume to Two Sigma a couple years ago. If I did, I never got a response. I was really excited when I found out you had a Houston office, but somewhat deflated when your careers page put all the interesting jobs in NYC. I get the impression Houston is basically just an IT/infrastructure office. Is that the case?
- spot 13y ago
  The Houston office is mostly infrastructure and data analysis, but we're always looking for good people more than specific roles. Most of the company is here at the HQ in SoHo.
canttestthis 13y ago
I understand if you can't answer this, but how does the pay for software engineers at Two Sigma compare to pay at top tech companies, like Google? Glassdoor is ambiguous.
- spot 13y ago
  I got a raise, but salary is only part of compensation. In the end it will depend on how the stock does (at a tech company) or what your bonus is (in finance).
  - canttestthis 13y ago
    I've read elsewhere that unless you're in a role that directly generates revenue (traders, etc.), you shouldn't rely on bonuses in finance, and should instead maximize the cash portion of your compensation. I assume this would be true for software engineers at Two Sigma too.
    - jchendy 13y ago
      Two Sigma, more than most other companies (financial or otherwise), understands that innovation and success is largely driven by technology. The content of twosigma.com is designed to communicate this, and it's absolutely true. Anything you've heard about how other companies are structured is unlikely to apply here.
    - joonix 13y ago
      I've seen evidence to the contrary. CS guys who get mega-bonuses based on fund performance. And no they don't even work on HFT.
busterarm 13y ago
I did a year at DESCO in Systems (didn't go so well, I made some mistakes) and everything that I hear about Two Sigma is that the place is awesome. The number of postings you've had recently has _exploded_ since I last looked at you guys around 2009-10. I would definitely recommend people look into this place and might consider it myself if I thought they'd ever hire me (not likely).
nachteilig 13y ago
How did they entice you away from Google initially?
HockeyPlayer 13y ago
I was surprised to see an investor relations page. Most prop groups aren't actively looking for more money. And they talk about clients, which is unusual. Can you explain?

ruang 13y ago

Does this mean that most MFE degrees lead to risk management instead of quant trading?

shogunmike 13y ago
I would say it's easier to get a job in risk management (likely in investment banking) than quant trading coming out of an MFE degree. This is primarily a consequence of how the MFE programs are set up, what they teach and the network of the professors etc.
- ruang 13y ago
  So quant funds don't use that much calculus? Primarily statistical techniques? I would guess that might be the case since pure arbitrage no longer works and thus quant funds have to delve into more probabilistic strategies like stat arb.
  - shogunmike 13y ago
    Yeah, this is pretty much the case. The quant derivatives pricing teams at banks are where the stochastic calculus folk tend to head to. Their teams are generally highly respected in this area. Also, banks are doing a different job to funds. Banks are generally interested in assessing the risk or trading risk of these products, either on prop (i.e. with their own funds) or to clients. Funds tend to concentrate more on statistical/machine learning/econometrics research approaches. The culture is generally more like a research institute thank a bank. They tend to hire more PhDs from Comp Sci, whereas banks will hire directly after MFE or straight out of undergrad.
    - deleted 13y ago
      [deleted]
    - ruang 13y ago
      Is that why physicists (vs computer scientists) are no longer recruited as actively for quant trading roles? It seems like all the low hanging fruit has been arbitraged away. I've worked with a Math PhD from Princeton before in prop trading and he always lost money.

tom_b 13y ago

Quantitative trading seems interesting because I would hazard that you need strong math background along with solid hacking skills. There are other problem domains with similar requirements, but I'm quite curious to hear stories from other HN'ers who have tackled quantitative trading either for themselves and in the day job. Specifically, if you can share a bit on your technical work in such a role, that would be cool to hear about.

shogunmike 13y ago
I was a quantitative developer working alongside a quantitative trader in a small 'proprietary trading fund'. This is roughly how all quant funds are separated. There is the "technology" side, which builds the data/trading infrastructure and then there is the "research" side that generates the trading strategies to run on the infrastructure. My job involved anything from hooking up to brokerage APIs to optimising MySQL replication topologies. Quite varied! In a way, it wasn't too different from your average startup, with the possible exception that you deal with a non-trivial amount of data from day #1 (hundreds of millions of rows are not uncommon). Open source has gained significant ground in funds these days. Python/R are now the "default" go to languages for quant trading research, with some MatLab too. Libraries such as NumPy, SciPy and pandas have really brought 'algo trading' to the 'retail' (algo) sector as well. .NET is still generally used quite a lot in investment banking, particularly C# for front-office GUI code, and C++ for any legacy number crunching libraries.
alexkus 13y ago
> Quantitative trading seems interesting because I would hazard that you need strong math background along with solid hacking skills. Strong maths knowledge can be good for general developer roles anyway. It's one (small) reason why I did a maths degree part time (Open University in the UK) to complement my existing Comp Sci degree. I'm sure you could get a better bang per buck picking and choosing specific areas rather than an entire degree but that wasn't my motivation (I'm equally interested in both in general). A good number theory course (even just plowing through Crandall and Pomerance, or Apostol) will definitely help with understanding/analysing asymmetric encryption.

3327 13y ago

Hi, I worked in both roles. I did an undergrad in theoretical Math and MFE. Its particularly easy to get a risk management job. My first job was for 100k + bonus out of school for BNPP. It is a highly quantitative risk department and was one of the best (if not THE best) institutional risk management gigs on the street. I did not know this at them time but I started in 2007 and after 2008-2009 I came to this conclusion. Anyway back to main subject. Risk jobs are easy to land and you can learn TONS or nothing interesting. Every shop has Risk integrated at different levels. Some shops its a backoffice type job where the risk guys are in the back seat (and this is the dominant case actually 8/10 I'd say). And rarely in places like BNP will you sit on the trading floor and have more power than traders. Yes traders will actually fear you... Rather than vice versa where Traders that are making money are big swinging dicks doing whatever they want (this is still the case at most shops). I started quant trading by chance when some guys running an arb blackbox were started constantly loosing money and were working late hours. I gave them a hand fixed a few bugs and word quickly spread. Next opening they offered me a position and I did an internal transfer... After I went to managing a portfolio (2 years after). And successfully did that for 4 more years. The summary is this. Quant Trading roles actually come in tones of flavors. Banks have option desks and in the recruiters will call these "quant trading roles". Hell, for all they know there is complex math involved and 'quant' sounds sophisticated. Truth is all option traders are proficient and calculus and derivatives to the point good traders are able to calculate pretty accurate 2nd orders in their head. And the tools available are also vast. But this is not a 'quant trading role'. A true 'quant' role is what some institutions have in house 'quant' teams that manage all the pricing models and libs. A 'true' quant trading role is stat-arb or some other arb strategy desk or similar type of strategy. Most banks do not have them anymore so its hedgefunds only. But even these vary vastly in quality. I know desks that would make 2-3 million a day net with very shitty hardware and patchwork system with lowlevel to mediocore guys working on it. And brilliant guys whom struggled (talking tier 1 guys, PHd MIT, princeton). So its a strange game and I would recommend going into a trading role into a medium level shop. Whats important is a good team and having a good vibe with the people you will work with. Trading is high stress and high emotion business so for your sanity in the long term its more important to work with good people rather than a top tier shop in the beginning.

13y ago

lutusp 13y ago

Quote: "However, a financial crisis in the Western hemisphere coupled with other macro/socioeconomic factors has lead to a reduction in scientific and engineering budgets and later-stage investment in such technologies." Translation: The recent worldwide economic meltdown was caused in part by quants' inability to accurately assess investment risks, or to influence decision-making, or both. The fallout was public distrust (justifed or not) of quants and what they do for a living. The bottom line is that reliable quantitative analysis hinges on the degree to which economics is a science. Economics isn't a science. Any questions?

VladRussian2 13y ago
>Economics isn't a science. A science is a method, not a domain or result or anything else. I.e. one can approach economics or medicine or traveling salesman problem using the scientific method, or one can approach it using woodoo.
- lutusp 13y ago
  > A science is a method, not a domain or result or anything else. No, this is false. Science is defined more clearly than this. Science is not a method, it is a set of rules for creating a method. Primary among those rules are a requirement for empirical evidence in support of scientific theories, and falsifiability -- meaning scientific ideas must be testable against reality, and those that fail the test must be discarded. TL;DR: Science is more principle than method. > ... one can approach economics or medicine or traveling salesman problem using the scientific method ... By that reasoning, astrology is a science, because it can be studied using the scientific method. But this is not how science works. For X to become a science, scientific study must support the theories that define X. Explanation here: http://arachnoid.com/psychology/index.html#The_Architecture_of_Science http://arachnoid.com/psychology/index.html#The_Architecture_... Economics is not a science. Title: "10 reasons why economics is an art, not a science" Link: http://articles.washingtonpost.com/2013-08-09/business/41217034_1_economists-economic-data-10-reasons http://articles.washingtonpost.com/2013-08-09/business/41217...
  - 13y ago

lpage 13y ago

"A great way to get into such a fund is to apply as a software developer, with aspirations of becoming a portfolio manager" That's not a path well traveled, especially at banks. At good hedge funds roles are well delineated, and chances are that you'll be working hard enough at your day job that you'll have little chance to explore on your own. Policy may prevent you access to the interesting data sets (execution data and historical P&L is sensitive to reverse engineering, and market data is often subject to expensive licensing). For banks the issue is far more bureaucratic - different teams with different hiring budgets and lines of business yada yada. There are relatively few managers high enough to wall cross between back office (technology) and front office (trading) so there's a stochastic component to your success at moving internally based on what group you end up in and how well connected your MD is. It doesn't help that coders are usually the limiting reagent (and paid less than traders) so the firm's interests aren't necessarily aligned with your own. If you're passionate about trading and coding, HFT is a great way to go. Money makers come from all backgrounds (grad/undergrad/super technical/creative coder) and you'll likely have better control over your coding/research ratio.

shogunmike 13y ago
I think I may have suffered somewhat from selection bias when writing that, in that a lot of my friends/colleagues work at smaller shops, where they initially started as technology infrastructure developers and worked very hard to move over to the research side. For instance, these were the guys -running- the data infrastructure so they were looking at it all day, every day. After a while it was probably straightforward to test out intuition on patterns they may have seen. Thanks for pointing out that the difficulties in doing so at a larger firm.

Sukotto 13y ago

Despite the intense competition, it is still possible to shine as a candidate, but you must be very well aware of what the funds are after, and then make sure you are providing it to them. I think this is a truism for any role in any capacity in any organization. Just replace "funds" with the organization/manager/client/whatever name.

anonu 13y ago

The article makes a good point about MFE degrees. They're a dime a dozen these days and most of them can't answer simple interview questions about linear regression. Its pretty shameful, not so much on the student's part, but on the universities that graduate these kids fully unprepared for the jobs that they think they can get...

hudibras 13y ago
The article really buried the lead on this one. The bottom line is that it's flat-out crazy for anyone to get an MFE these days. They cost as much as an MBA and won't get you a job as a quant.
- shogunmike 13y ago
  Indeed, I am considering actually writing an entire article on that whole topic. I haven't done an MFE personally, so I don't feel I can comment too much on what they're like, although I have a few friends who have. A lot of them simply went into research afterwards.

dunster 13y ago

Another solution is to write the algorithm but avoid the hedge fund - lots of suits, and they take most of the money. You're better off if you trade it yourself. People work for hedge funds because hedge funds provide mentorship and really powerful tools and lots of data to sift through. We're trying to provide all of those things, for free, at Quantopian. https://www.quantopian.com/ https://www.quantopian.com/ Check out our community (for mentorship), our backtester (very powerful, and open source), and our 11-years of minute-bar data - all for free.

anoncowherd 13y ago

Dear HN: Stop casually discussing working for a bunch of disgustingly greedy, full-of-shit, and downright evil sociopaths as if you hadn't noticed.

hudibras 13y ago
The title of this submission was pretty clear. If you don't want to discuss this topic, then don't click on the comments link. That's what I do when I see, for example, the word "Haskell" in the submission title...

Tycho 13y ago

Sometimes I think of the HFT and quant trading industries are like the Formula 1 of tech. A way for extremely talented people to apply their skills and compete with each other, with lots of money involved, but ultimately the technologies developed for the 'race track' make their way onto 'main street' in some shape or form. I'm sure all this research into ultra low latency infrastructure and live data mining is bound to come in useful somewhere else. Maybe this is off base but why be cynical.

kenster07 13y ago

Getting rich while play poker with others' pensions. And just like a casino, the only sure winner is the house.

bachback 13y ago

RenTech assembled some of the brightest technical minds in the world to trade purely quantitively. They did pretty well for themselves. Jim Simons, famous mathematician, former MIT professor and DIA code cracker, earned the following amounts according to Forbes: 2011: $2.1 Billion 2010: $2.5 billion 2009: $2.8 billion 2008: $1.3 billion 2007: $1.5 billion