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In Battle to Recruit New Quants, Hedge Funds Outpay Banks
- melling 7y agoWhat does a quant do? Machine learning, linear regression, moving averages? Lots of statistics on time series data?
- npo9 7y agoFurthermore, what is a good way to become a quant?
- Akababa 7y agoOne way to get interviews at least is by doing well in math contests.
- tansey 7y agoThe type of quants talked about in this article probably has a PhD in math, stats, CS (with a focus on machine learning), or something similar.
- Akababa 7y agoThis particular article is about MFE students from one school, but hedge funds love PhDs too.
- sukilot 7y agoand especially physics, since financial modeling is based on physical modeling.
- curiousgal 7y agoWell not directly, it's just that they both make use of stochastic calculus.
- melling 7y agoAny good MOOCs, etc for the topic?
- Nostra 7y agoA Master Quant here ... ask me anything
- computer_czar 7y agoWhat's your education background?
- Nostra 7y agoMath, advance geometry, CS
- pretendscholar 7y agoIsn't math, advanced geometry redundant?
- millstone 7y agoNo: topology, analysis, number theory, etc.
- anonu 7y agoadvanced geometry? what about advanced arithmetic? I hear thats a much needed discipline.
- XMPPwocky 7y ago...they just did!
- gentaro 7y agoHow much do you get paid?
- xchaotic 7y agoIs the job repetitive ? What % of work is solving Math and coding and how much PowerPoint ?
- CoryG89 7y ago
- tansey 7y agoYes. Exactly this. Building models that assess risks and potential gains. A quant is a catch-all term though, so one person may be working on models that predict some sector of the market and another person could be looking at online allocation algorithms for maximizing risk-adjusted returns.
- ham_sandwich 7y agoQuant is a pretty broad term. Some would say it’s often working on nonlinear desks to implement/calibrate volatility surfaces and things like that or working more on the risk management side. There’s also the whole HFT world (Jane St, Virtu, Jump etc) many would call ’quant’ but really is a different game than the HF space. On the machine learning side, in my experience it’s often simple, linear models that work best in the messy world of financial data. I’m sure there are shops out there breaking out the GPU clusters and training NNs with 6 trillion parameters but in no way will your super deep NN guarantee alpha whatsoever.
- lordnacho 7y agoIt's a very wide category, but all those things could apply. I used to be a partner in a couple of funds, and at the time the major distinction was between people who priced complex derivatives and people who thought about how to use data to guess what the market would do. You'd be more likely to find deriv quants at a bank selling such things to people, whereas the strategy quants would be what you'd find in the funds. But even within that fund side I'd imagine the job looks very different depending on what firm you're at and what they ask you to do. Not everything is glamourous blue-sky "what should I buy or sell" stuff. A fair bit of it is things like cleaning the data. And there's going to be a lot of tooling. Since nobody says what they are doing, everyone has their own version of a research pipeline, and that needs to be kept clean. Likewise on the execution side, there's a load of code to be looked at, and a lot of data coming out relating to trading costs and such.
- JumpCrisscross 7y ago> It's a very wide category The term is historical, not functional. Before option-pricing theory, securities pricing was an art. Yes, there were capital asset pricing theories for fundamental analysts. But at banks, a phone and hustle were the tools of the trade. With Black-Scholes (and put-call parity) came the ability to (a) manufacture options out of other securities and (b) print objectively-wrong quotes. The former gave banks an incentive to build the business. The latter gave them the incentive to automate. The people they hired to do that were quants. The first generations of quants automated option-pricing models. Through the 80s, they found themselves involved in more products, e.g. securitised loans and mortgages. By the 90s, they were launching funds. Today, almost everyone on a modern trading desk is a quant to some degree.
- candiodari 7y agoI thought now with securities with negative interest there were a lot of securities that now had to take that into account and black-scholes is just no help whatsoever there. Is there any answer to it yet ?
- 7y ago
- hermitdev 7y agoThat's part of it. There's also classical modelling, some natural language processing probably more techniques. In short it's trying to find the signal in a huge amount of noise/data. I'm not a quant but I support the Quants at my firm. Some of our datasets are hundreds of millions of rows with up to 450 factors/features per row. They also run NLP on terabytes of SEC filings (like quarterly and annual reports). Not sure how they analyze the results of that.
- Nostra 7y agoA Master Quant here ... Ask me anything
- netfl0 7y agoFine, detail your compensation please.
- Nostra 7y agoIm in the shade for 18 years now ... Just me ... compensation = unlimited
- ferros 7y agoWhat percent of ‘ideas’ make it to live trading. How much time is spent on average validating idea. How much of the testing is automated/reuse of code and how much is custom per idea.
- ydnaclementine 7y agoWhat are some good resources to learn things that are need to know and good to know if you want to work in this area?
- Trias11 7y agoDo you leverage Deep Learning / AI? How successful if yes?
- orange3xchicken 7y agoLegit shops might employ DL algorithms as a way to recover behavioral indicators, but no one is relying on DL or using DL for decision-making.
- JumpCrisscross 7y ago> recent graduates working at hedge funds made significantly more than their peers working at banks This has always been true, for the entirety of my career. Buy side pays more than sell side for alpha-generating activities. (Sell side pays more for flow and scaling advantages.) This article strikes me as a submarine [1] for Baruch’s program. [1] http://paulgraham.com/submarine.html http://paulgraham.com/submarine.html
- Waterluvian 7y agoIs "submarine" just "Trojan horse"?
- chillacy 7y agoIf you read the linked article you'd see that it's a more specific phenomenon to news articles. Maybe you'd consider it a type of trojan horse because it's misleading.
- elfexec 7y agoYou could call it the news industry's equivalent of tv/movie's sneaky product placement. A paid ad pretending to be a legitimate news story just like a product placement is a paid ad pretending to be part of the plot.
- elfexec 7y agoAgreed. Otherwise the story makes no sense. It's always been the case that hedge funds pay more than banks just like silicon valley pays more than government. This is so well known, I knew it when I was a kid and people outside of the finance industry are aware of it.
- jgalt212 7y agoseriously, no disrespect to Baruch, but if Baruch grads are making up to $1MM, are MIT grades making $5MM?
- sukilot 7y ago
- CodeSheikh 7y agoIs Financial Engineering still relevant these days? I thought it is all Data Science now.
- natalyarostova 7y agoNah, most data scientists don’t know stochastic calc, even if they are capable of learning it.
- ajaalto 7y agoQuant here. I used to be a seismologist but switched to finance one year ago. This year I earned well below 100k€.
- ck425 7y agoOut of curiosity how did you switch to being a quant?
- dorchadas 7y agoI'm not the OP, but it's a switch I'm strongly considering making. I'm looking at doing it by going back to get a Masters in Quantitative Finance, so that's one possible option.
- amiga_500 7y agoBecause the west is collapsing as rentier work dominates over true wealth creation!
- finolex1 7y agoWould you rather that resources be allocated blindly? The fact that some people can live comfortably off their investments does not mean that the very investments themselves do not create wealth. Hedge funds do the latter, it's up to the government and society to decide on the former - i.e. how to distribute this wealth.
- amiga_500 7y agoResources are being allocated into a bubble, because every time the market falls the Fed prints money via QE. Hedge funds aren't looking for companies doing valuable work, they are trying to figure out if Powell will print more, or gaming Bank of England APIs. The system is not functioning.
- ajaalto 7y agoI worked as a software developer before I got the seismologist position. It was not too difficult to interview for various data science positions.
- caymanjim 7y agoNot going to fight the paywall to read the article, but as a developer consultant (not a quant), hedge fund clients pay better across the board than both commercial and investment banks. They tend to be small shops, so it's not really a fair comparison. I've worked for boutique hedge funds, market makers, wealth management funds, pension funds, and two huge investment banks. The small hedge funds pay a lot more and the work is more interesting and less bureaucratic. Just my anecdotal take.
- fishingisfun 7y agodo they also work you more?
- caymanjim 7y agoNo. Working hard is almost always counter-productive.
- RookyNumbas 7y agoHedge Funds have always paid quants significantly better. In the past decade or so many banks have built out their engineering teams. Goldman is now 25% engineers. More recently these banks have started to compete with hedge funds for the same quant talent that can better take advantage of their new technical prowess. But the comparatively strict compensation structure still means you can make a lot more on the buy side.