And the Quants Shall Inherit the Earth

No surprise here. This trend is only going to accelerate, as hedge funds and asset management firms hire brilliant computer scientists for research and investing roles. It will be interesting to see whether more fundamental funds (long-short equity, special situations, distressed debt) will start hiring quants to guide actual investment decisions.

Given that all these funds are ultimately relying on data, will we see a time when firms such as Greenlight/Baupost/Paulson, etc., become "quant-lite" funds? Or will the typical banker/PE types still rule the world of fundamental investing?

Here is the ft.com/intl/cms/s/0/856bd92c-8fb0-11e5-8be4-3506bf20cc2b.html">article.

 

I agree with your general premise, but we must also remember that some areas of investing require a heavy emphasise on 'qualitative factors'. I'm specifically referring to areas such as VC, where it's predominantly 'story-telling' and being able to translate that story into basic numbers. By the very nature of this field of investment management, there will never be a large amount of 'useful' data, in the same sense that there is for established companies. This stage of the investment process requires more 'vision' than data and that is not something that is going to change.

In other words, there will definitely continue to be a demand for both fundamental and quantitative people in the investment management industry.

 
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I agree with your general premise, but we must also remember that some areas of investing require a heavy emphasise on 'qualitative factors'. I'm specifically referring to areas such as VC, where it's predominantly 'story-telling' and being able to translate that story into basic numbers. By the very nature of this field of investment management, there will never be a large amount of 'useful' data, in the same sense that there is for established companies. This stage of the investment process requires more 'vision' than data and that is not something that is going to change.

In other words, there will definitely continue to be a demand for both fundamental and quantitative people in the investment management industry.

Actually there is a push toward data driven investing in the VC world as well:

http://www.fastcolabs.com/3021903/this-prediction-algorithm-can-tell-if…

 
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I agree with your general premise, but we must also remember that some areas of investing require a heavy emphasise on 'qualitative factors'. I'm specifically referring to areas such as VC, where it's predominantly 'story-telling' and being able to translate that story into basic numbers. By the very nature of this field of investment management, there will never be a large amount of 'useful' data, in the same sense that there is for established companies. This stage of the investment process requires more 'vision' than data and that is not something that is going to change.In other words, there will definitely continue to be a demand for both fundamental and quantitative people in the investment management industry.

Actually there is a push toward data driven investing in the VC world as well:
http://www.fastcolabs.com/3021903/this-prediction-...

Intredasting.

 

It's been interesting to observe over the years how job descriptions for roles such as Investment Analyst, Financial Analyst, Business Analyst (really any analyst) have changed from containing 'requirements' such as 'Undergraduate degree in Accounting, Economics, Finance' to 'Undergraduate Degree in Accounting, Economics, Finance, Computer Science, Mathematics...Master's a plus, python/SQL a plus, CFA progress preferred...'

 

Gray Fox does a great job hiding the fact that he's seething with resentment

But yeah, more and more fundamental asset managers and hedge funds are becoming more quantitative. At the end of the day most of fundamental research is analyzing data, and a computer can do that pretty efficiently

There will always be human components but programming and statistics are getting increasingly prevalent in the industry

 

LTCM was a prime example of when quants took over and had model over dependency. The quants help but you need a solid dose of cynicism that the models are just that, "models" and tails are fatter than we think, and nothing is i.i.d :)

"Finance is a gun. Politics is knowing when to pull the trigger" - Mario Puzo
 

Quants are not taking over anything. The two businesses are fundamentally different.

Quants are there to take advantage of short term movements and statistical factors. Computers have shown effectively no skill in investing over the longer time frames (quarters to years) that real fundamental investors consider. This is because there are a lot of fundamental/ human factors that computers simply are not currently capable of comprehending/ influencing (e.g. the owner is about to retire and his heirs are incentivized to do X, i've been talking to my buddies at big fundamental shops that are also involved and we're all pushing management to do Y). Fundamental investing is very very far from just a numbers game.

And no: I'm not some tech luddite. I have a pretty strong mathematical/technical background and a (much weaker) programming/ start up one. The reality is computer's will have to be pretty darn close to full on artificial intelligence before they can do fundamental investing themselves.

The primary impact computers will have on fundamental investing is just driving greater efficiency for individual analysts by helping to gather and organize (e.g. model) data much faster than you ever could before. To some extent this just means the data gathering/modelling becomes table stakes and less important (though there will always be upside to being more thoughtful/precise about the way you conceptualize the world).

Bottom line though: quants and fundamental investors barely live in the same universe. I had a 30 minute conversation with a quant where we compared jobs and (tried to) share ideas. We came to one conclusion: "momentum is hot right now" (a lot more useful to him that it is to me btw)

 

I have a similar background to dazedmonk, and agree with everything he says. Fundamental investors don't really compete against quants at all; they do different things on different time horizons, though data will matter more in the future (mostly because more data will become available; we still live in a bit of a data-wasteland for now).

One exception: I think that there are a lot of investors who think that they are doing fundamental analysis, but really have just been making money on Fama-French factors. For instance, some investors have been buying low P/E stocks, capturing the value factor like a primitive quant model; they think the reason for their success is analysis, but it is really just the factor, with stock picking not adding additional value. Similarly, there are others who have been buying high-flyer growth stocks effectively at random (though they may not know this), and their good returns are just capturing momentum.

These investors can have decent track records because factor models have historically been very powerful. I suspect, though, that a lot of those track records will start to fall apart as quants/ETFs compete away the returns to those factors.

 
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One exception: I think that there are a lot of investors who think that they are doing fundamental analysis, but really have just been making money on Fama-French factors. For instance, some investors have been buying low P/E stocks, capturing the value factor like a primitive quant model; they think the reason for their success is analysis, but it is really just the factor, with stock picking not adding additional value. Similarly, there are others who have been buying high-flyer growth stocks effectively at random (though they may not know this), and their good returns are just capturing momentum.

This is a great point. Fundamental analysis will always have its place but it also doesn't seem to hard for quants to pile into value stocks, small cap stocks, illiquid stocks or any other category that may have generated abnormal returns for large periods of time. I can see firsthand ETFs doing it so I can only assume that quants are doing it on a much more sophisticated level. That would take away a tailwind from fundamental investors who play in those spaces. Can anybody more familiar with the quant space offer their opinions on how this is playing out?

 

Excellent point, though right now it works both ways. Naive mathematical models buying the right factors can drive mispricings that fundamental investors exploit (e.g. companies that are basically dead but don't trade as such because value models suggest they are cheap or ridiculously priced growth stocks that just become more ridiculous - until they don't).

I think some places are actively working to combine the computer analysis with fundamental insights (DE Shaw has a 'quantamental' group - I'm guessing this is what they do).

 
Best Response
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Quants are not taking over anything. The two businesses are fundamentally different.

Quants are there to take advantage of short term movements and statistical factors.

It sounds like you're commenting on an industry where you're not familiar enough with the internal mechanics to get everything right. This is an industry I happen to work in, so perhaps I can help clarify a few things. Quant funds- aka systematic strategy funds- can have holding periods that range from minutes to months. I work on the stuff that ranges in the weeks and months, and we may look at similar data to what manual PMs look at (I honestly don't know what you guys look at, and for obvious reasons I can't talk about exactly what we look at). We just try to have a more productionized and systematic approach and can do it across hundreds or thousands of stocks. And we're always looking to pick up insights from traditional PMs with quant backgrounds, although at a large multistrategy hedge fund we also have a lot of in-house talent to speak to. So the process might be a bit more disciplined in some respects, but you can imagine there is less focus on details. A smart, creative human who really focuses on a small basket of stocks can definitely beat most systematic strategies out there... but the gap has narrowed a lot over the past 10 years. I do think there is an opportunity to make these strategies more detail oriented-- although that will also make them a bit more labor intensive, too.
Computers have shown effectively no skill in investing over the longer time frames (quarters to years) that real fundamental investors consider.

And no: I'm not some tech luddite. I have a pretty strong mathematical/technical background and a (much weaker) programming/ start up one. The reality is computer's will have to be pretty darn close to full on artificial intelligence before they can do fundamental investing themselves.

The primary impact computers will have on fundamental investing is just driving greater efficiency for individual analysts by helping to gather and organize (e.g. model) data much faster than you ever could before. To some extent this just means the data gathering/modelling becomes table stakes and less important (though there will always be upside to being more thoughtful/precise about the way you conceptualize the world).

Bottom line though: quants and fundamental investors barely live in the same universe. I had a 30 minute conversation with a quant where we compared jobs and (tried to) share ideas. We came to one conclusion: "momentum is hot right now" (a lot more useful to him that it is to me btw)

I know CAPM and EMH taught us differently in undergrad, but the results at DE Shaw, AQR, Two Sigma, Kepos, and Citadel disagree with this.

On average, quantitative hedge funds may not outperform (professional fundamental investors certainly do not outperform). That does not explain why Citadel, Two Sigma, and DE Shaw have to turn away capital.

This is because there are a lot of fundamental/ human factors that computers simply are not currently capable of comprehending/ influencing (e.g. the owner is about to retire and his heirs are incentivized to do X, i've been talking to my buddies at big fundamental shops that are also involved and we're all pushing management to do Y).

As to the article- I've definitely seen the competition heat up between the hedge funds and silicon valley. We're looking for people with a certain set of backgrounds that competes with them- they've also moved into fields that require quant backgrounds and stuff that goes a little beyond a typical EE or Comp Sci degrees. The quants will not inherit the earth. At least certainly not during my lifetime. But it's always nice to have skills that (at least right now) have a broad base of demand. Perhaps one day they'll be as valuable as investment banking or traditional portfolio management skills.

 

'would appreciate the following information:

  • What programming languages/platforms do you work with?

  • What would be the typical languages used across the industry for quant trading/analytics purposes?

  • Which of the following is more preferred from a hiring point of view in your line of work: a professional programmer without financial training (say a programmer from Microsoft) OR someone with fundamental grasp of financial investing concepts but no coding experience?

Thanks!

 

My initial response focused more on higher frequency styles (didn't want to get too long), but I have the same argument wrt to "systematic" strategies. They are fundamentally different

To keep this from drifting off topic I will ground it in the original question: "Given that all these funds are ultimately relying on data, will we see a time when firms such as Greenlight/Baupost/Paulson, etc., become "quant-lite" funds?"The somewhat tautological answer is "never", because its just a different strategy.

We already have systematic funds (like yours apparently). They cannot do what people like Greenlight/Baupost do. Einhorn convinced Apple to increase its payouts. He made a multi-year bet against Allied Capital based on an in depth understanding of business model/accounting. Activists like Ackman, Jana, etc are an even better example of the kind of work computers are simply capable of - and keep in mind that "suggestivisim" (telling mgmt what to do but not making a stink about it) is part of the repertoire of basically every large fund. The existence of systematic traders makes very little difference to these strategies for now. You can code likelihood of activism (based on balance sheet, ownership, etc) into your model, or include it as a factor in buy/sell decisions, but that does not in any way 'compete away' the advantage of the person who actually does the activism.

Computers do not exercise influence over mgmt, and are still pretty weak wrt the contextual/qualitative understanding to spot frauds. I'm sure a lot of people are working on programs to spot accounting red flags (and I want one), but this is different from doing the groundwork to, for example, spy out a 'factory' and realize that Gowex was literally just making up the numbers investors (human and computer) relied on. Your response completely failed to address my claim that computers cannot comprehend/influence the human issues (cute owl though).

Finally, Citadel is not a quant shop - its a multistrat. I'm pretty sure (but not certain) the vast majority of the risk is in fully human models. DE Shaw is likewise a multi-strat (though less so than Citadel I believe). I'm not sure about the other funds, but in any case its irrelevant. The success of Two Sigma or Hudson River or Marshall Wace's systematic strategy does not imply that we're moving away from human driven investing. The only way for that to happen is to have a future where systematic funds effectively always beat fundamentals over the long term, which is unlikely since fundamental analysts have (human) tools that computers don't.

The last thing is that effectively every type of investing is subject to crowding/competition, so your systematic models are not on some monotonic improvement path that will make them better than humans. In fact, the only hope for getting rid of human advisors is for the returns to become so negligible that they can only pay the lowest wage workers (computers)

TLDR: Systematic trading is also a fundamentally different (and already fairly mature) business that has had no discernable AUM limiting effect on fundamental strategies.

 

'Quantamental' equity strategies like the ones you describe seem to just (1) abstract out the essentials of the fundamental investment process, (2) systematize it, and (3) apply it in a more disciplined and efficient way.

I can't see how this doesn't eat into the juice of traditional fundamental equity investors, and shift the entire distribution of outcomes for that career path to the left. Given this shift, would you still say that if one is gunning for the top end of the distribution of outcomes, that there is still more upside in the traditional fundamental route than in quantamental equity land?

 

On a long enough time-horizon I'd argue everything will be quant driven. Will that happen in the next 10,25,50,100 years? Who knows.

What you'd be looking at to determine the answer though is where is 'sustainable' return coming from, how complex the process is to achieving that sustainable return, and what are the boundaries of the complexity.

With those three things answered im pretty sure you could make a decently informed prediction. See what's played out in the above discussion is the fundies arguing fundy stuff can't be done by computers, and quants saying that, they sort of can - with enough detail and time.

I'd side with the quants.

But to generalise the reason why - think of it this way, to achieve return you need to cash in on either 'factors' or arbitrage in some way (betting on a mispricing being corrected). Now given capital markets are finite, it naturally must follow that only a certain amount of return available from a capital market is available per period.

If you think about it this way, then there's no distinct difference between 'non-quant' and 'quant' strategies, they are simply fighting to extract return from their requisite strategy. Some strategies get crowded out (say convertible arb, market netural etc), others get phased out (latency arb - tech related strategies), others remain so generalised that it's hard to crowd them out (value-driven buy-and-hold).

So we have a complex environment that at any time offers different opportunities for return at any one point in time. But for arguments sake, we can hold it as a finite pool of return opportunities related as a function of its components (govt policy, tech, liquidity, skill etc etc etc).

But we also have technology - and tech makes things cheaper. If a return extracting strategy which is currently 100% 'human' for a cost of 100x could be implemented at 50x with tech at R&D cost 40x, then provided there's enough competition to pressure margins (which there is), you'd bet there'd be active investement into figuring out how to replace the 'human' element. Because now the fund can outprice other funds.

So combining the two, for not-very-original insight - cost pressures will highlight the benefit of technology to lower prices of running a fund, this will erode the required human capital. To figure out 'when', will be a function of the rate of technological progress, and rate of competitive price pressures. If ever the age of the Quantumn computer comes, a large majority of 'human-only' investing will be eradicted.

 
setarcos:

On a long enough time-horizon I'd argue everything will be quant driven.

It's easy to linearly extrapolate and make this statement. By the same logic, one can argue "on a long enough time-horizon, everything in life will be quant driven." Even programmers will become obsolete by AI. After all, who is better to program computer than a computer who knows itself in and out? Humans will be forever replaced by our own creation. Hence enter the age of the apocalypse, terminators shall reign and this tread will be partially facilitated by computers that use linguistics programming to moderate conversations between humans and promote site track...
 

Execution trading / HFT lend themselves to computers, but value investing or going off of fundamentals still requires the human brain. Research relies heavily on pattern recognition and interpretation of the news, especially event driven research, and most of the time the models already exist and just get updated on a routine basis. IBD and sales, well, I think it's safe to assume that they've already maxxed out how much computers can really do for them.

It can't hurt to learn that stuff, and OP is correct in assuming that the general level of technical competency is going up, but there are plenty of jobs that don't require a high level of programming knowledge.

Get busy living
 

This is the same argument they've been making about the military for years. 'Machines are going to take over and we'll have no more soldiers.' False. There are things that machines just cannot do. Sales, Investor Relations, PR, etc. you have to have people with 'soft skills' as much as the uber dork with the giant computer.

If I had asked people what they wanted, they would have said faster horses - Henry Ford
 

Well, you need everybody, but we're moving to a value society. Folks said that about malls and Best Buy ten years ago when Amazon and Ebay got started, and they're now getting forced into BK. It's only a matter of time until this trend climbs up the value chain and eventually- maybe not today but probably in 15-20 years- it will be starting to cut into margins in trading and banking.

We will always need human beings, but more and more of the population will prefer to save 50% and deal with the machines.

 

Socialism, fascism, or starvation. Either way, freedom seems to be inversely proportional to population.

But honestly, the machines will always need resources to make stuff. Oil, commodities, agriculturals. An old book that you and I both follow dictated that a country would be capitalist for 48 years, but on the 49th year, the resources got nationalized and redistributed to their original families. I wonder if that might be the way to go.

 

Programming or Maths?

I can definitely see many areas of mainstream finance become a lot more mathematical/quantitative or at least require more maths at the junior levels of investment management, but you have to realise that finance is still business and you will need business skills. I don't see programming skills necessarily dominating in the manner suggested in the original post.

I can't see how programming is going to be useful at all to the following lucrative areas of investing and finance: - Distressed investing & special situations - Event driven investing - Anything illiquid or private (real estate, private equity, emerging market securities, etc...) - Value investing - Most of corporate finance and investment banking as well as other relationship driven business

If anything, apart from a few specific hedge fund roles, am I correct in assuming that programming tends to put you in the middle office as oppose to the front office / management / partnership-track of most financial firms?

I think the big question will be, if the "uber dorks with the giant computers" end up getting increasing status within finance and investment management, will it mean that the business-end and senior management of investment firms will have to prove their mathematical credentials? I can see this happen over time. How much of an understanding of their technical expertise is required in order to be able to lead these kind of people and manage this business? So far, not a lot.

If management needs to become more mathematical, what form will this take? More advanced quantitative degrees at all levels? i.e. will your sales guys be required to become more and more quantitative in order to sell products to increasingly quantitative buyside?

If pricing models become more and more complex how will that affect finance education generally and at MBA level? Does it mean that you will need programming and advance maths skills to learn finance even if you aren't set on being a risk manager?

Clues... How much more quantitative are the guys who sell complex securities and trading strategies now than they were 10 - 15 years ago? Any anecdotal evidence or trend?

Any parallels with the tech sector? Does programming lead there and do programmers make most of the money nowadays or is that just a specialist skill for hired "labour" with the business guys taking the cash?

I can't see programming dominating finance. Programming skills are simply unnecessary for most of the value add in the industry and what drives the competitive advantage of most financial firms.

 

Discussing this with a few colleagues, one of them brought up this point.

Automation generally increases productivity by making the work require LESS skill (as well as economies of scope, etc...), i.e. compare the skill required by a Savile Row tailor to a garment worker making shirts at a factory for the Gap.

How would this impact finance? My initial guess: - I can see gains to owners of capital (i.e. partners/senior management) in the short-medium term. - Would probably require fewer investment professionals in relation to AUM when it comes to trading/portfolio management functions. - An increase requirement for skilled professionals who can build and maintain the models & systems. - A key factor is how all of this would impact the delivery of financial services/distribution of products. Can that be automated? If so sales/relationship guys can see their incomes fall as the role becomes de-skilled, if sales can't be automated than they should see their incomes rise over time as they will retain control over a key part of the value chain/could have more capital/bandwidth to work with.

 

Even for the jobs that require "soft skills/relationship skills/creative skills" I would never hire anyone other than a math/science/eng grad. Don't give me that bullshit, "oh they aren't people persons!" Every single math major (American) I've ever interviewed/met is 1000x more creative and personable than any liberal arts grad.

fact.

 
wadtk:
Even for the jobs that require "soft skills/relationship skills/creative skills" I would never hire anyone other than a math/science/eng grad. Don't give me that bullshit, "oh they aren't people persons!" Every single math major (American) I've ever interviewed/met is 1000x more creative and personable than any liberal arts grad.

fact.

I generally agree here. Math, physics etc majors tend to be very passionate people, and that passion shows through.

 
ANT:
For some reason I think people who have a hard science background tend to favor their own.

I'm judging by experience. Problem solvers will always be more valuable than simple number crunchers. There is a difference

 
ANT:
For some reason I think people who have a hard science background tend to favor their own.
Hah. I'll admit to this. That said, while some folks were out partying, others were slaving away through four long years, and I do think the skillset we pick up is a bit more specialized.

There is room for folks with technical skills and folks with people skills in the world. I do think that some of the tail upside experienced by folks with people skills over the past 50 years is going to be shared a bit more with folks with technical skills, though.

 
in_the_money23:
For those who know a good deal of programming, what is the primary programming language (i.e. C++, C#, HTML, etc.) that would be the best to learn for finance? I'm aware that I won't be able to become an expert just from online research, but it would be nice to develop a rudimentary base of knowledge in programming.
The best language is imperative programming pseudocode- and then becoming an expert on data structures and algorithms. As you know, any idiot can code in C++ or any other language, but smart C++ programmers tend to be smart C# programmers, etc.
 

False dichotomy. People aren't one dimensional, i.e. either technical or people persons. It's even more of a mistake to think that your undergraduate education (sciences vs. finance/econ/history) is what determines whether or not you'll be able to be successful in the industry as an investment manager, advisor or financial entrepreneur.

Your technical skills (i.e. ability to do complex analysis, program, etc...) are only useful to the extent you are able to get capital or deal flow to put that to work. The technical skills are a commodity for the most part, it's the people who are able to control networks and flow of capital that the gains go to.

Let's take Kyle Bass as an example. He has a lot of fans on this site because of the money he made shorting the housing market. What many people don't realise is that if he hadn't been a Fixed Income sales guy at Bear Stearns he would have never had the rolodex and ability to raise capital to set up his own fund and eventually put that trade on. If he did it at someone else fund as an employee he would have made a nice bonus, that's it. Instead look at where he is now.

I'm sure most of you have read the Big Short and the book about Paulson's trade. Who made the most of the sub-prime trade? The smartest "technical guys" or the guys who controlled the capital and were able to put the trade on/take a slice of the upside?

You can be the best programmer, mathematician, technical genius in the world with the best ideas, you'll still make less building models as an employee of a hedge fund then the guy who employs you.

Get all the programming skills that you want, just make sure that investors/LPs/clients know you exist and you have relationships with them so you can actually profit from your bright ideas...

 
Relinquis:
False dichotomy. People aren't one dimensional, i.e. either technical or people persons. It's even more of a mistake to think that your undergraduate education (sciences vs. finance/econ/history) is what determines whether or not you'll be able to be successful in the industry as an investment manager, advisor or financial entrepreneur.

Your technical skills (i.e. ability to do complex analysis, program, etc...) are only useful to the extent you are able to get capital or deal flow to put that to work. The technical skills are a commodity for the most part, it's the people who are able to control networks and flow of capital that the gains go to.

Let's take Kyle Bass as an example. He has a lot of fans on this site because of the money he made shorting the housing market. What many people don't realise is that if he hadn't been a Fixed Income sales guy at Bear Stearns he would have never had the rolodex and ability to raise capital to set up his own fund and eventually put that trade on. If he did it at someone else fund as an employee he would have made a nice bonus, that's it. Instead look at where he is now.

I'm sure most of you have read the Big Short and the book about Paulson's trade. Who made the most of the sub-prime trade? The smartest "technical guys" or the guys who controlled the capital and were able to put the trade on/take a slice of the upside?

You can be the best programmer, mathematician, technical genius in the world with the best ideas, you'll still make less building models as an employee of a hedge fund then the guy who employs you.

Get all the programming skills that you want, just make sure that investors/LPs/clients know you exist and you have relationships with them so you can actually profit from your bright ideas...

^^^ This.

 

How could programming not be an essential skill in the next five to ten years? It is already useful and clearly anyone who has skills in working with computers will be at an advantage. There are ways to make anything more efficient by allowing computers to do mundane tasks.

The beauty of it is that as time passes the tasks that are considered mundane to computers will be more complex. All else being equal why would someone ever take the liberal arts kid vs the guy with math/programming skills?

 
jktecon:
. All else being equal why would someone ever take the liberal arts kid vs the guy with math/programming skills?

I don't understand what the point of these ceteris paribus statements are. Fact is, there is almost no scenario where everything is equal, especially when it comes down to something as subjective as an interview. Even if they are similar quantitatively (i.e. GPA, SAT, ECs, etc.) I can almost guarantee that they'll come across differently in the interviews, which makes all the difference.

Even if magically such a situation occurs, I don't understand what these kinds of statements prove. It's kind of like me stating that ceteris paribus, I'd take the 10/10 victoria's secret model over the 8/10 one (imperfect analogy, but whatever). Yeah, a guy with a CS major who works with numbers and computers all day will be slightly more valuable than a guy who studied Art History for a job revolving around numbers and computers, but that is purely because of the circumstances they are placed under. It's not like I would hire a CS guy over the lib arts guy if I needed a research paper on ancient chinese painting techniques, so I don't even understand how blanket statements like this can be made.

Pretty women make us BUY beer. Ugly women make us DRINK beer.
 

I don't know man. Study what you want. What is this "my major is better than your major" bullshit. Also, you are studying a hard science and then wanting to format power point. Please tell me when you are going to bust out your mad quantum skillz at 2am replacing semi colons.

So much fucking dick measuring on this site. Is this a Wall Street site or a fucking girls magazine.

 
jktecon:
All else being equal why would someone ever take the liberal arts kid vs the guy with math/programming skills?
Nepotism. Target. "Prestige."
My name is Nicky, but you can call me Dre.
 

Okay UFOInsider, let's just say that there is no correlation between how personable someone is and their major. I've noticed that many top math/physics/comp sci majors tend to be socially awkward, but engineering majors tend to be outgoing and believe in the whole "work hard, party harder" philosophy.

You are like that trader who wants hard data for things that don't exist, since that's the only way to shrug an analyst away.

How about rather than quantifying it, what do you think from your life experiences? Engineers are technically smarter than business majors and they are just as personable.

You can teach a hard science/engg major the art of business/sales/trading in 6 months, but you will NEVER be able to teach a business major engineering in 6 months. You need hard evidence for this?

The masked avenger par sexellence
 
lambertoscar:
Okay UFOInsider, let's just say that there is no correlation between how personable someone is and their major. I've noticed that many top math/physics/comp sci majors tend to be socially awkward, but engineering majors tend to be outgoing and believe in the whole "work hard, party harder" philosophy.

You are like that trader who wants hard data for things that don't exist, since that's the only way to shrug an analyst away.

How about rather than quantifying it, what do you think from your life experiences? Engineers are technically smarter than business majors and they are just as personable.

You can teach a hard science/engg major the art of business/sales/trading in 6 months, but you will NEVER be able to teach a business major engineering in 6 months. You need hard evidence for this?

Smarter? Well that would be true if by smart you meant only mathematical skills. Is an engineer smarter than a concert pianist? What about an artist. Or a PhD in psychology?

Is someone with a BS in engineering smarter than someone with a MS in History?

See the point. Intelligence is subjective. People who study hard science do so because they enjoy it. Who gives a fuck.

 
lambertoscar:
Okay UFOInsider, let's just say that there is no correlation between how personable someone is and their major. I've noticed that many top math/physics/comp sci majors tend to be socially awkward, but engineering majors tend to be outgoing and believe in the whole "work hard, party harder" philosophy.

You are like that trader who wants hard data for things that don't exist, since that's the only way to shrug an analyst away.

How about rather than quantifying it, what do you think from your life experiences? Engineers are technically smarter than business majors and they are just as personable.

You can teach a hard science/engg major the art of business/sales/trading in 6 months, but you will NEVER be able to teach a business major engineering in 6 months. You need hard evidence for this?

This is correct. A math genius, for instance, can do well in virtually any subject, but the vast majority of humanities majors will have no clue if you try to teach them advanced math/science/programming.

 
lambertoscar:
You are like that trader who wants hard data for things that don't exist, since that's the only way to shrug an analyst away.
Person made a very strong statement stating what they called "truth". So, let's see the proof. The point I was hinting at is that studying numbers for a little while doesn't have anything to do at all with creativity and the entire statement is absurd.
lambertoscar:
Engineers are technically smarter than business majors and they are just as personable.
...they studied a more quantitative subject for a while. The engineers may be smarter. The may also just have had a lot of time to sit and stare at it until it sank in. An intelligent person will be good at whatever they choose to put their mind to.
lambertoscar:
You can teach a hard science/engg major the art of business/sales/trading in 6 months, but you will NEVER be able to teach a business major engineering in 6 months. You need hard evidence for this?
You really think so?

Just as I could take a crash course in applied math or physics and maybe pass, you could learn a different language or take a course in sales...but to fluently apply this takes time and is not something you will master in six months. I'm merely pointing out that while engineering / math is indicative of intelligence (like going to an Ivy league school), the intellectual snobbery by no means translates into you being justified in insulting other people. Nor does being good at math dictate that you're going to be good at everything else...it just means you're good at math.

Get busy living
 
ANT:
Any subject Brady? That might be a little overboard.
I'm of the same mind. A smart person will do well at any subject, and the smartest people in history have been good at hard science and arts.

examples: * Einstein (physicist) was an excellent violinist and social commentator * Ramanujah (philosopher) formulated brilliant mathematical theorems * Kasparov (chess player) is an outspoken social activist and writer * Ben Franklin (originally a writer) was a major contributor to science * Hume was just good at everything he touched * So was Newton * And DaVinci

I'm not as smart as those guys though :( Does anyone have some NZT?

Get busy living
 

Are we discussing banking? If so, I would prefer a finance student or someone with strong writing skills. Engineering or any science is hardly relevant in most things finance. Maybe some trading positions would benefit from a mathematics background, but outside of that, general business knowledge is all you need.

Engineers are great in engineering tasks. But just because you know complex math doesn't mean you are a super employee. And for every social butterfly with a math degree I have met an awkward geeks who can't interact with people in a normal fashion.

 

Soft kills can largely not be taught and a lot of the people that are predisposed to be the 'types' that go in hard sciences, math, etc. are not the type that do well in these areas. Generally speaking, of course there are outliers.

If I had asked people what they wanted, they would have said faster horses - Henry Ford
 

Again, it's a bit messy, ANT. I think that if you're dealing with an Engineer, there's a certain guaranteed minimum level of quantitative skills. Same with a English major with regards to writing. That said, there's good writers and good math folks just about everywhere.

I would argue that we work in a fairly mathematical discipline. Banks have armies of research staff, traders, quants, risk managers, financial engineers, and programmers. All of this requires a great deal of comfort with accounting, linear algebra, and stats, and many of these roles require an advanced understanding of differential equations and stochastics. Bottom line is that in order to give someone a compelling reason to merge with XYZ, buy QRS, structure deal TUV in a certain way, or derisk ABC, you have to offer a compelling reason to do so. Most of those reasons get back to something fundamentally quantitative.

The meat and potatoes of finance are numbers and it's really tough to get around that. Currently, we add teak paneling, Brooks Brothers suits, letters after folks' names, and well-written prose to make a deal happen or a trading relationship form, but it's easier to see that aspect of the business change than to see the quantitative aspects get taken out of banking.

Both skillsets are very important. I would actually argue that soft skills and people skills are more important since that's what makes us human. One day, if computers are running everything, human beings will still want to have friends and relate to one another, but there will be no more need for math and engineering PhDs. But I would also argue that in the meantime, technical skills are more practical for business purposes than soft skills.

 
IlliniProgrammer:
technical skills are more practical for business purposes than soft skills.
In trading, definitely yes. In banking, sales, brokerage, ER...it's the guys that open their mouth and talk to the most people, talk the best, and listen well that often make $^buku. To be fair, if someone does well in engineering you KNOW they are intelligent and a psych / econ major can be hit or miss, but outside of HFT and a few other niches, high level math just isn't really necessary.
Get busy living
 
IlliniProgrammer:

Both skillsets are very important. I would actually argue that soft skills and people skills are more important since that's what makes us human. One day, if computers are running everything, human beings will still want to have friends and relate to one another, but there will be no more need for math and engineering PhDs. But I would also argue that in the meantime, technical skills are more practical for business purposes than soft skills.

Will still need 'em to build and maintain the machines.

 

The argument behind natural science/engineering backgrounds taking over finance was never that all human interaction should/will cease to exist.

The point is that fewer jobs will be available to people without these skills. It is an almost comical question but seriously; how many social science majors does it take to chat up a CEO?

I dont think it is too hard to visualize the redundant tasks, like filling out spreadsheets or copying files and getting them to their destinations within a corporation being automated within that 10 year time frame.

These automation mechanisms will be the results of business engineers. Finance is the first category of business to create a new field of engineering for its service but I do not think it will end here. Engineers work to take humans out of performing mindless and arduous labor. You should be so lucky to have your misery ended so early, but attempting to fight a 4000 year old force (or however long you believe human beings have been engineering for their advancement) is futile.

 
jktecon:
The argument behind natural science/engineering backgrounds taking over finance was never that all human interaction should/will cease to exist.

The point is that fewer jobs will be available to people without these skills. It is an almost comical question but seriously; how many social science majors does it take to chat up a CEO?

I dont think it is too hard to visualize the redundant tasks, like filling out spreadsheets or copying files and getting them to their destinations within a corporation being automated within that 10 year time frame.

These automation mechanisms will be the results of business engineers. Finance is the first category of business to create a new field of engineering for its service but I do not think it will end here. Engineers work to take humans out of performing mindless and arduous labor. You should be so lucky to have your misery ended so early, but attempting to fight a 4000 year old force (or however long you believe human beings have been engineering for their advancement) is futile.

You're 100% correct. I just want to point out that the vast majority of engineering innovations in finance (again, outside of trading) are in cost saving as opposed to revenue generating roles. People paying other people and the people that sit at that intersection.....THAT'S where the money is.
Get busy living
 

What will happen in the finance world will be analogous to what happened to finance and economics academia. It is always about "standardization" of processes. The formalization and a UML design of workflows in investment banking and logic will eventually happen, there are KPOs for M&A deals now! These kind of firms are always started by some guy who was a jack of all trades, goes into finance, has the mind of a mathematician and realized how he can scale and template solutions for the market. Since a lot of the time, there are a lot of people reinventing the wheel. Thats what happened with stock broking, to algo trading, to firms now taking external software providers to minimize R&D spending on developing an IT infrastructure. All it takes is one Jesus figure to transition the industry.

I mean there were many software dev jobs which were replaced by other softwares which were "generalized" solutions. Generalized solutions in any field are the first stepping stones to software domination.

There are lots of people with engineering degrees who are technically brilliant and who go for an MBA, and then get into M&A... we will be seeing these guys make elegant solutions and try to wipe these monopolistic banks out of the map.

The masked avenger par sexellence
 

No, the machines will fix and build themselves.

You're 100% correct. I just want to point out that the vast majority of engineering innovations in finance (again, outside of trading) are in cost saving as opposed to revenue generating roles. People paying other people and the people that sit at that intersection.....THAT'S where the money is.

I disagree. Machines are going to ensure that more and more money stays with folks paying each other the money and less and less goes to the folks sitting at the intersection. It happened with retail 15 years ago; it will eventually happen with finance (though it will probably take longer.)

Machines will simply drop fewer pennies in front of the steamroller than the humans.

 
IlliniProgrammer:
No, the machines will fix and build themselves.
You're 100% correct. I just want to point out that the vast majority of engineering innovations in finance (again, outside of trading) are in cost saving as opposed to revenue generating roles. People paying other people and the people that sit at that intersection.....THAT'S where the money is.

I disagree. Machines are going to ensure that more and more money stays with folks paying each other the money and less and less goes to the folks sitting at the intersection. It happened with retail 15 years ago; it will eventually happen with finance (though it will probably take longer.)

Machines will simply drop fewer pennies in front of the steamroller than the humans.

Will always have to have someone to create what will create itself. Almost like there has to be a God argument ha!

 
IlliniProgrammer:
No, the machines will fix and build themselves.
You're 100% correct. I just want to point out that the vast majority of engineering innovations in finance (again, outside of trading) are in cost saving as opposed to revenue generating roles. People paying other people and the people that sit at that intersection.....THAT'S where the money is.

I disagree. Machines are going to ensure that more and more money stays with folks paying each other the money and less and less goes to the folks sitting at the intersection. It happened with retail 15 years ago; it will eventually happen with finance (though it will probably take longer.)

Machines will simply drop fewer pennies in front of the steamroller than the humans.

Do forgive me for my laziness, however I simply cannot be arsed to read the entire thread. I'm curious, do you actually believe the 'nerd rapture' (i.e singularity) nonsense?

 

I think there is a trade off between the quants(programmers, physicists, Math PHD,etc) and the business school-type (management, IBD, sales, etc).

For one quants, I would assume in general, lack any real useful social skills where as the business school type, that means everything. And this social skill is everything when you're up for a management position. Your ability to make money means a lot, but your ability to deal with people is just as important.

 
low_key:
I think there is a trade off between the quants(programmers, physicists, Math PHD,etc) and the business school-type (management, IBD, sales, etc).

For one quants, I would assume in general, lack any real useful social skills where as the business school type, that means everything. And this social skill is everything when you're up for a management position. Your ability to make money means a lot, but your ability to deal with people is just as important.

empty platitudes ftw!

do people on here ever think before they post?

fwiw both programming and sales skills are a commodity, a manager can hire a programmer and he can hire a salesman, the part that is not a commodity is the risking / entrepreneurship part.

 

Where are you people getting this sociable aspect of business majors. I've met plenty of normal/interesting math/physics/engineering majors. Just wish I could say the same about the business group. That standardized business/marketing lingo has become trite and almost nauseating to a large number of people.

Don't confuse a person letting their real personality out at first meeting with a lack of social skills.

 

Guys, I think we've veered off the topic a bit, but this might bring us back to what I think is the key point...

Spoiler Alert - MoneyBall the movie & book

I've just watched MoneyBall and I think there are some interesting parallels. It's a film about a Baseball manager (Billy Beane) who hires a Yale economics kid (Peter Brand) to successfully apply statistical methods and computer analysis to drafting his players at Oklahoma... They manage to transform their team beyond anything that more experienced professionals had achieved and they give better funded teams a run for their money.

In the end, who was it that was offered a multimillion dollar contract to employ these strategies at another team (manage the RedSox)? Was it the whiz kid or the manager? It was the manager. Why? The kid is smarter, more quantitative, educated and has more programming skills while still being personable. It's because the RedSox can hire another Yale quant, that skill eventually becomes a commodity. It is just highly skilled labour. The manager is the one who was able to take advantage of that and apply it to his team and he has the credibility, skill-set, experience and network to do it again at another team. The whiz kid could (and does to some extent) develop some of the negotiating & interpersonal skills, but he simply doesn't have the full range of networks, credibility, experience in other areas to fill the manager's spot at the RedSox... yet.

Another parallel, what happens to the role of the traditional baseball scout in the movie? It's pretty much gone (in reality it probably still exists, it's just that the role is a shadow of it's former self).

Key takeaways for me when it comes to finance/investment management: - Be aware of how new methods and tools will impact your business & strategy. Adapt. - It takes more than just possessing this new skill set to capture the full value of the new technology/strategy. It's not enough just to be smarter. - It pays more to control/run/own the business than to be an employee, skilled or otherwise. - Don't become a dinosaur.

As an aside, I wonder if there is a way to apply more advanced analysis to areas of finance that don't lend themselves to obvious quantification. (e.g. PE, REPE, Distress Debt / Special Situations, etc...). Is anyone doing this successfully or is working on this academically? I would take a year off to do a masters that would help me develop this.

FYI, SB to lambertoscar for an insightful post.

 
Relinquis:
Key takeaways for me when it comes to finance/investment management: - Be aware of how new methods and tools will impact your business & strategy. Adapt. - It takes more than just possessing this new skill set to capture the full value of the new technology/strategy. It's not enough just to be smarter. - It pays more to control/run/own the business than to be an employee, skilled or otherwise. - Don't become a dinosaur.

I couldn't agree more. I just had a similar conversation with my taxi driver (as he was driving me from the apartment of the chick I just got with...what up!). He has an undegrad in economics from India and a masters from UCSD, but is now driving a taxi. The short of the long story is that eventhough he's quite smart, he failed to adapt to new technologies quickly enough and ended up becoming a "dinosaur". By 50, one should be one's own boss. That's the point when you'll find it impossible to get a new job, unless you've developed some niche skill noone else has.

Relinquis:
As an aside, I wonder if there is a way to apply more advanced analysis to areas of finance that don't lend themselves to obvious quantification. (e.g. PE, REPE, Distress Debt / Special Situations, etc...). Is anyone doing this successfully or is working on this academically? I would take a year off to do a masters that would help me develop this.

Unfortunately not yet. There's 3 reasons for this: Not enough data, lack of an analytical formula, lack of liquidity. Let me elaborate:

There's 2 kinds of mathematical approaches in quantiative finance - econometric (a lot of data fitting e.g.: stat arb) and analytical (a system that can be solved to gives you a formula that doesn't change over time e.g: Black-Scholes). The former needs a lot of data for the regression, while the latter needs the problem to be formulated in a few variables that can be solved. Neither of these is true for the fields you mentioned - the data points are too unique for a regression, and there are too many variables for a formula.

Also, historically, quant strategies have been employed in very liquid markets. In Aug 2007, when people needed liquidity, what did they first get rid of? Quant books (the event was called the Quant meltdown). None of the fields you mentioned are particularly liquid. Ofcourse, this last point applies to quant trading, not to applying quantitative tools to human trading.

 

Funny how this has morphed into a faux Jets / Sharks turf war.

Arguing about your background is pointless. No one cares, in business, if your not able to generate revenue.

...and to the "in the future everything will be automated and there will be no need for intermediaries". This argument must have been predicated in the same breath as the strong market hypothesis.

 

Umm one would only hope that all the useless banking middlemen would be cut out of the picture to have an efficient market. And I believe the argument was that a new efficiency in engineering systems would take these jobs

How many arguments in life are not mental turf wars being played out?

And I can tell you are one of the useless middlemen so it appears you have drawn your line in the sand as well.

 
jktecon:
Umm one would only hope that all the useless banking middlemen would be cut out of the picture to have an efficient market. And I believe the argument was that a new efficiency in engineering systems would take these jobs

How many arguments in life are not mental turf wars being played out?

And I can tell you are one of the useless middlemen so it appears you have drawn your line in the sand as well.

I'm in PE, if you bothered to check you wouldn't make a fool of yourself.

And to your conjecture, middle men equals inefficient market. Please back up this statement.

 

If I had a quarter for every time someone mentions programming on this forum...

Seriously, why do you feel the need to justify this?

Shit will get a little bit more automated in the future, but S&T wont succumb to just machines and the nerds who run them. And in terms of skills you might need, VBA would be the only useful thing if you are front office. Those who program "more convenient" trading software, etc..., are not revenue generators.

 

I think the point that's being missed is that the stereotypical programmer (i.e. socially awkward nerd sitting in a closet coding) is becoming a thing of the past. More and more "normal" talent, i.e. kids that are both smart and socially adept are studying comp sci. So, while you don't see the possibility of the nerd stealing away the "revenue generation" jobs (i.e. customer facing), you might be blindsided by the up and coming kids that can do both. And they are the game changers - they are the ones who can say "fuck your current business model, my friends and I will do it our way, and in 5 years you'll be gone because we're making a better model.". Any barriers that you think exist, can and will disappear over time.

 
Brady4MVP:
The trend towards automation has been ongoing for some time and is only accelerating. Lately I've been talking to a lot of headhunters and others in the industry, and they all echo the same thing. Programming knowledge is increasingly becoming a must.

Hedge funds and prop trading firms are now aggressively targeting people at tech firms like google/facebook/microsoft/amazon, as well as start-ups, due to their programming skill sets. Even the more fundamental funds are starting to look for quants who can develop sophisticated models.

In the next 5-10 years, are we gonna reach a point where if you don't know programming, you will have very few job options in finance?

Yes. It is clear that programming is a must-have skill as the industry evolves. However, leadership and communication skills will still remain paramount. Those individuals that have both advanced quant and soft skills will inherit the earth moving forward.

 

This doesn't address whether you'll need programming skills, but I think its conceivable that machines could take some of the IBD jobs eventually and do some of the DD, they've been developing programs to analyze legal documents (article). As the technology evolves, it could cut in. I think soft skills will still be important, especially at the highest levels.

http://www.slate.com/articles/technology/robot_invasion/2011/09/will_ro…

 

I agree:

I think the point that's by djfiii (Gorilla, 637 Points) on 12/25/11 at 11:23pm

I think the point that's being missed is that the stereotypical programmer (i.e. socially awkward nerd sitting in a closet coding) is becoming a thing of the past. More and more "normal" talent, i.e. kids that are both smart and socially adept are studying comp sci. So, while you don't see the possibility of the nerd stealing away the "revenue generation" jobs (i.e. customer facing), you might be blindsided by the up and coming kids that can do both. And they are the game changers - they are the ones who can say "fuck your current business model, my friends and I will do it our way, and in 5 years you'll be gone because we're making a better model.". Any barriers that you think exist, can and will disappear over time.

This is true of human evolution over time: Just look at how Mark Zuckerberg is now. Totally transformed. And this will be true of others following suite.

"Kept feeding him dollars 'till it all started to make cents."
 

"Eliminated" is a very strong word. There will always be value investors. I do think that it's increasingly more difficult for value investors to generate alpha since the markets are continually increasing in efficiency. We also need to differentiate between public equities, which is insanely competitive, and less liquid transparent markets such as distressed debt where a savvy hard working investor can have a huge edge.

The most interesting trend is the move towards passively managed vehicles such as ETFs, as investors realize that active investing for the most part is a pseudo-scam, especially when on takes into account taxes and fees.

 

There's a tremendous difference between Ackman shorting Herbalife and an HFT firm making 800,000 trades in a day, they aren't even playing the same game. Both strategies take advantage of different market inefficiencies.

 
undefined:

Just got back from an interview with yet another global macro fund asking for coding abilities. Can one really break in without a STEM background?

Break into what without a STEM background? You obviously need a STEM background for quant roles - that much is obvious. If you don't have a STEM background, then you should be applying to roles that are suited towards your skills.

 

I would suppose interviewing for a macro fund meant wanting to break in. The problem is I am not interviewing for structured programmes - and the only openings that are available based on the feedback I've gotten are quant / developer roles.

The macro scene here isn't huge, and finding discretionary roles isn't proving to be a walk in the park.

 

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