Is Quantitative Finance an intellectually stimulating field?

  • Thread starter Thread starter MattW
  • Start date Start date
Joined
10/8/16
Messages
2
Points
13
Being a very curious person with a strong drive to learn new things, I was wondering whether becoming a Quantitative Analyst could be the right career move for me. I thought about going into academia in the past to do "proper" science, but I heard some discouraging comments about the way modern research is conducted (and I don't think I would enjoy teaching). That's why I'm thinking of job opportunities that might allow me to constantly learn and apply models to reality, therefore satisfying my curiosity while also overcoming academia's isolation from the real world.

In summary, I would like to know a bit more about what Quantitative Finance - or quantitative analysis/mathematical finance - (it's all the same, right?) consists of. Does a quant do research on the best models for pricing and stuff, or is it just number crunching more akin to what actuaries do (ok, not all actuaries... at least the vast majority I know of)? And also, how different is it from Data Science, another field I'm inclined towards?

I would really appreciate any help. Thanks!
 
In summary, I would like to know a bit more about what Quantitative Finance - or quantitative analysis/mathematical finance - (it's all the same, right?) consists of. Does a quant do research on the best models for pricing and stuff, or is it just number crunching more akin to what actuaries do (ok, not all actuaries... at least the vast majority I know of)? And also, how different is it from Data Science, another field I'm inclined towards?

This is probably not the kind of response you are looking for but it still needs to be said: PhDs and MFEs serve as high-IQ fodder to the voracious maw of finance. Applied brain power, like every other kind of labor, has been thoroughly commoditised in late capitalism. Forget about the aesthetic and intellectually stimulating aspects of the work. If these aspects exist, it is only as incidental and very occasional by-products. For work to be interesting and meaningful it needs to have a historical context and to be a craft. These aspects have been stripped from contemporary work.
 
Full disclosure: I'm not a real quant. I have an MS in statistics from NYU, so at best I'm "quant-lite."

If you find the markets interesting, it's likely you'll find QF interesting. If you happen to be very quantitative and QF looks like an easy way to make money, you will not like it.

I've been doing this for over thirty years. Every day, I come in and deal with smart people and work on solving interesting problems, not all of which are necessarily quantitative in nature. I enjoy reading articles in the NYT and the WSJ and knowing that I know much more about the market or the transaction about which the reporter is writing. I really like being forced to take complex concepts and boiling them down to their barest essentials. I like a good argument and I don't mind when someone younger than I proves me wrong. I figuratively squeal with glee when I succeed in getting my point across, even if I don't carry the argument. It also happens to pay the bills.

If you like it for the sport of it, you'll be fine, else reconsider.

There's a great quote out there in the ether, the ultimate source of which I don't know:
How a bad idea starts - "That looks easy; I could do that."
How a good idea starts - "That looks fun; I should do that."
 
Full disclosure: I'm not a real quant. I have an MS in statistics from NYU, so at best I'm "quant-lite."

If you find the markets interesting, it's likely you'll find QF interesting. If you happen to be very quantitative and QF looks like an easy way to make money, you will not like it.

I've been doing this for over thirty years. Every day, I come in and deal with smart people and work on solving interesting problems, not all of which are necessarily quantitative in nature. I enjoy reading articles in the NYT and the WSJ and knowing that I know much more about the market or the transaction about which the reporter is writing. I really like being forced to take complex concepts and boiling them down to their barest essentials. I like a good argument and I don't mind when someone younger than I proves me wrong. I figuratively squeal with glee when I succeed in getting my point across, even if I don't carry the argument. It also happens to pay the bills.

If you like it for the sport of it, you'll be fine, else reconsider.

There's a great quote out there in the ether, the ultimate source of which I don't know:
How a bad idea starts - "That looks easy; I could do that."
How a good idea starts - "That looks fun; I should do that."

Thanks for the very detailed response. Indeed, I do find markets interesting, but I also feel the need to have quantitative data to back up my beliefs about them instead of just believing financial journalists or so called "experts". In what sense are some problems non-quantitative then?

Most importantly though, what you said about boiling down concepts to their essence totally appeals to me. I'm someone who likes to have a general picture of what I do, getting to know the theory of how the pieces fit together and what justifies each step. Most of the time, this tends to be a problem though, so I'm not sure I would have the motivation to become a quant if I'd just have to apply formulas that I don't know much about (and I'm worried this is going to be the case if differential equations are so commonplace in models). Would you mind telling me a bit more about this particular aspect?

This is probably not the kind of response you are looking for but it still needs to be said: PhDs and MFEs serve as high-IQ fodder to the voracious maw of finance. Applied brain power, like every other kind of labor, has been thoroughly commoditised in late capitalism. Forget about the aesthetic and intellectually stimulating aspects of the work. If these aspects exist, it is only as incidental and very occasional by-products. For work to be interesting and meaningful it needs to have a historical context and to be a craft. These aspects have been stripped from contemporary work.

Well, I'm not sure if that's necessarily the case. Work in general tends to be dull and exhausting; it's been that way for most of humanity. So I'm not sure if capitalism itself has to take the blame for that.

Anyhow, that leads to a different discussion. What I want to find out is what's the best career that this society can offer me. Compared to a couple of decades ago, the opportunities are almost infinite, so I'm hopeful there's something out there for me.
 
Anyhow, that leads to a different discussion. What I want to find out is what's the best career that this society can offer me. Compared to a couple of decades ago, the opportunities are almost infinite, so I'm hopeful there's something out there for me.[/QUOTE]

It was once more difficult having a career. What would you like to offer to society?


Compared to a couple of decades ago, the opportunities are almost infinite,
LOL! every generation says that.
My maths education cost 300 per year and student:teacher ratio was 1:6. The 70's.
 
Last edited:
This is probably not the kind of response you are looking for but it still needs to be said: PhDs and MFEs serve as high-IQ fodder to the voracious maw of finance. Applied brain power, like every other kind of labor, has been thoroughly commoditised in late capitalism. Forget about the aesthetic and intellectually stimulating aspects of the work. If these aspects exist, it is only as incidental and very occasional by-products. For work to be interesting and meaningful it needs to have a historical context and to be a craft. These aspects have been stripped from contemporary work.

Bigbadwolf, I'm genuinely curious what your job is. You do nothing but shit on this field, but it's not clear to me that there are greener pastures for us quantitative folk. Once something is profitable it gets commoditized, including intellectual work, and that's true irrespective of the domain of application. No matter what industry you work in, your job is to make your employer money, full stop, and later on for all that intellectually stimulating nonsense.

What has you so jaded about quant finance in particular, is it really so different in its gestalt from other purportedly quantitative areas like data science or software engineering?
 
You do nothing but shit on this field, but it's not clear to me that there are greener pastures for us quantitative folk. Once something is profitable it gets commoditized, including intellectual work, and that's true irrespective of the domain of application. No matter what industry you work in, your job is to make your employer money, full stop, and later on for all that intellectually stimulating nonsense.

What has you so jaded about quant finance in particular, is it really so different in its gestalt from other purportedly quantitative areas like data science or software engineering?

Au contraire, I'm doing no such thing. And you give the answer I would have in the rest of your post: there are few or no alternatives. That's why Ph.D.s have gravitated towards finance. My gripe is with the general nature of work these days -- not quant finance in particular. Quant finance is part of the general job market and not something anomalous and exotic. In addition, the supply/demand ratio has changed completely in the past decade or so, and the prospective quant has to shoulder the onerous financial burden -- and concomitant risk -- by himself. Numerous posters other than myself have written on this here.

And perhaps better to go in jaded than naive and starry-eyed.
 
ok but I need to get that 6 figure quant job and goldman from goldman and sachs won't return my phone calls.

And some do -- and bully for them. But even in their case, they're often being worked to the bone. The "intellectual satisfaction" part is incidental and serendipitous if it is there.
 
Nothing is permanent in life.
In 1980 oil and gas was the place to be. If you had a PhD in maths you could develop a reservoir engineering Finite Element package from scratch (cool), now you can download it from the Web.

And the research jobs are not the privilege of North America and Europe any more, by no means.

And not so long ago PhDs wanted to work for themselves..
 
Nothing is permanent in life.
In 1980 oil and gas was the place to be. If you had a PhD in maths you could develop a reservoir engineering Finite Element package from scratch (cool), now you can download it from the Web.

And the research jobs are not the privilege of North America and Europe any more, by no means.

And not so long ago PhDs wanted to work for themselves..

Career risk is something very few people understand, as I have said before. I saw someone on LinkedIn advise an applied mathematician "you will easily get a job in oil and gas" about 3 years ago, such is people's lack of understanding of change (judging by his profile he graduated in the late 70s). And I can see guys my age telling people the same about QF in 2036, no matter what the market reality is, which says a lot about people - most senior modellers I know complain about this all the time, especially when it is their own firm applying 1980s approaches to 2010s problems (I was in this situation in my first firm when they applied a 1980s insurance approach to their strategy in 2007).

Back to the OP - you are asking the wrong question. Interesting or intellectually stimulating is not what firms want - useful is what they want. With maths careers intellectual stimulation is often incidental and can sometimes happen when there is no marketing or business origination involved, when markets are calm and when complex maths is unavoidable. At least any jobs I did in finance that involved client work were not intellectually stimulating, while middle office roles could involve learning a new trick with correlation, modelling etc.

The thing is I still thrived in some of those jobs that involved marketing - had I followed the "follow your passion" directive I would have gone back into middle office and had a very sharp but narrow skillset. But I learnt a lot of other soft skills and a lot of non-mathematical skills that proved useful in my current career. In fact I worked with an ex-engineer that was one of those guys that had become an expert in Finite Element methods and that kept harping on about developing marketing and soft skills as he had hit a glass ceiling before he moved into banking as he was seen as "too intellectual to become a manager" as he had not looked at these things. He is now a senior partner at an infrastructure fund as his change of strategy and broadening of skills served him better in his new career.

I had a similar experience where I don't deal with clients but where I am a lot more ahead of the political game thanks to picking up skills that don't strictly speaking relate to "intellectual stimulation".

Where people get confused is with things like the difference between being an actuary or an accountant, where I know people with maths background in both that call them boring jobs. The difference is vast - although actuary is reportedly boring most maths guys I know in the field like it as they are usually the most useful on their team and, they already knew a huge chunk of the knowledge when entering the field, they become senior managers very quickly. In contrast any mathematician I know that got sucked into the whole atrocious "accountancy has numbers you'll be brilliant at it!" found that in accountancy they were learning an entire new field while calculators and Excel performed the tiny fraction of their skill set, and to round it all off after all this education (I know one accountant with a PhD in physics) people that did, guess what, an accountancy degree kicked their ass at the job, irrespective of enthusiasm.

Usefulness and seeing the way the tide turns is king NOT intellectual stimulation or even passion. I'm not sure I can comment on research as I have no experience of PhD environments.
 
Last edited:
Usefulness and seeing the way the tide turns is king NOT intellectual stimulation or even passion.

A related remark is that skills have a half-like of about 5-6 years. They become obsolete, are outsourced or must be upgraded.
 
Last edited:
Usefulness and seeing the way the tide turns is king NOT intellectual stimulation or even passion.

A related remark is that skills have a half-like of about 5-6 years. They become obsolete, are outsourced or must be upgraded.

Depends upon the skills, and the upgrade can sometimes be minimal.

I still see people coming up to me at data science conferences looking to hire someone to solve very specific problems with Hadoop nodes that need Java. If the product gets changed so such problems are no longer an issue, or the business invests in something more organised (such as products in the Hadoop Ecosystem) then their specific skillset is obselete.
However if I am a programmer in R+MapReduce and really a data and ML expert then we have a reusable skill in the latter. And in data science the maths is the same kind of stuff and many ex-quants or ex-statisticians had little difficulty moving, even externally, where it was more a change of use than skills upgrade. Also, as I used to be a business originator, I am valued as I know (more or less) how the business guys approach things and can translate this stuff into something succinct, while a data science graduate doesn't have that (yet) and some quants stuck in a MO role might not be that good at that if they have just been building libraries of pricing while their boss covers for their poor documentation style.
 
Last edited:
Depends upon the skills, and the upgrade can sometimes be minimal.

I still see people coming up to me at data science conferences looking to hire someone to solve very specific problems with Hadoop nodes that need Java. If the product gets changed so such problems are no longer an issue, or the business invests in something more organised (such as products in the Hadoop Ecosystem) then their specific skillset is obselete.
However if I am a programmer in R+MapReduce and really a data and ML expert then we have a reusable skill in the latter. And in data science the maths is the same kind of stuff and many ex-quants or ex-statisticians had little difficulty moving, even externally, where it was more a change of use than skills upgrade. Also, as I used to be a business originator, I am valued as I know (more or less) how the business guys approach things and can translate this stuff into something succinct, while a data science graduate doesn't have that (yet) and some quants stuck in a MO role might not be that good at that if they have just been building libraries of pricing while their boss covers for their poor documentation style.
Liam, I don't know who you are, but I think Andy should hire you as as an advice columnist. This and your earlier post should be required reading for aspiring quants.
 
Depends upon the skills, and the upgrade can sometimes be minimal.

I still see people coming up to me at data science conferences looking to hire someone to solve very specific problems with Hadoop nodes that need Java. If the product gets changed so such problems are no longer an issue, or the business invests in something more organised (such as products in the Hadoop Ecosystem) then their specific skillset is obselete.
However if I am a programmer in R+MapReduce and really a data and ML expert then we have a reusable skill in the latter. And in data science the maths is the same kind of stuff and many ex-quants or ex-statisticians had little difficulty moving, even externally, where it was more a change of use than skills upgrade. Also, as I used to be a business originator, I am valued as I know (more or less) how the business guys approach things and can translate this stuff into something succinct, while a data science graduate doesn't have that (yet) and some quants stuck in a MO role might not be that good at that if they have just been building libraries of pricing while their boss covers for their poor documentation style.

Technological savvy tends to be commoditized and easier as time goes on, mainly due to new libraries and interfaces. My own feeling is that ML will become part of the development environment; so it will be like "Create empty ML cloud" project in Visual Studio(?) What I'm saying is that the mainstream will catch up on the trend-setters and trail-blazers. All the difficult stuff will be automated.

Look at parallel programming; by knowing what design pattern you need it is implemented directly in a library. In a sense, the august topic of design patterns becomes almost redundant. And you can probably get away with not having to know the joys of thread programming.

Core knowledge tends to be future-proof.
 
Technological savvy tends to be commoditized and easier as time goes on, mainly due to new libraries and interfaces. My own feeling is that ML will become part of the development environment; so it will be like "Create empty ML cloud" project in Visual Studio(?) What I'm saying is that the mainstream will catch up on the trend-setters and trail-blazers. All the difficult stuff will be automated.

Look at parallel programming; by knowing what design pattern you need it is implemented directly in a library. In a sense, the august topic of design patterns becomes almost redundant. And you can probably get away with not having to know the joys of thread programming.

Core knowledge tends to be future-proof.

What do you regard to be the core-knowledge?
 
What do you regard to be the core-knowledge?
By definition, stuff that will be needed in [10,30] years time, for example. In a sense, product knowledge rather than technology knowledge I suppose.

I suppose core stuff I what adds 'to the business'. Even that can be outsourced these days.
 
Back
Top Bottom