CFA to Math Masters

[false_dichotomy]

A few dimensions to the question at hand so I'll be concise and feel free to provide insight into all or part of the question. Thanks in advance.

Brief background: I'm in my mid 20s, econ/finance undergrad, and passed the first two levels of the CFA but just got into a good university's undergraduate math program. The goal is to complete calculus 2 and 3, linear algebra, differential equations, and apply to a masters program. I'm attempting to optimally allocate my time.

How do colleges (specifically, masters mathematical finance admissions committees) view the CFA?

Is there any "real world" value in having a masters in mathematical finance and the CFA? In other words, does a masters in math significantly outweigh the benefits of the CFA?

If I self-study calc 2 (topics for my course will include: techniques of integration, volume of solids of revolution, infinite sequences and series, differential equations) and enroll in calc 3, how much of calc 2 is applicable to other math classes/topics (e.g. multivariable calculus, linear algebra, stochastic processes, time series modelling, numerical methods, Brownian motion)?

Thanks again.

 

[tjk]

As far as math goes, if it seems like you'll be starting at pretty much literally the beginning and you're already in your mid-20s, what's the goal?

 

[false_dichotomy]

I'm currently on the investment banking side and would like to switch to a hedge fund (obviously in a quantitatively focused fund/position). I think developing a quantitative background will provide much more stability and professional latitude.

 

[tjk]

How would this work exactly? You're working and in your mid-20s, you're going to start a new Bachelor's degree, then do a Master's (all while working), and then presumably get a job at a quant hedge fund at some point when you're in your mid-30s?

 

[false_dichotomy]

Since I'm not technically completing a bachelors degree time works somewhat in my favor. I only need to complete the prerequisites for a masters, not complete the whole bachelor's degree. Most likely I'll need to complete 5 classes (calculus 2 & 3, linear algebra, differential equations, and one additional course). I can conservatively complete a masters by 29-32 (depends on getting into classes when I need them, taking 3-4 classes per year).

The idea isn't to entirely change careers but to open up new positions. For example, portfolio manager at a fund that employs quantative analysis. In other words, I wouldn't be in the weeds of the model but I would understand its output.

 

[tfors]

..

If I self-study calc 2 (topics for my course will include: techniques of integration, volume of solids of revolution, infinite sequences and series, differential equations) and enroll in calc 3, how much of calc 2 is applicable to other math classes/topics (e.g. multivariable calculus, linear algebra, stochastic processes, time series modelling, numerical methods, Brownian motion)?

Thanks again.

calc 2 is very very basic and is applicable to most if not all other math classes you mention. I wonder how you can enter a masters in math with only those very basic courses, almost every science major far from maths knows calc 1, 2, 3, linear algebra and DEs. And I don't know much about CFA, but I don't think it is very mathematically advanced.

 

[bigbadwolf]

Most likely I'll need to complete 5 classes (calculus 2 & 3, linear algebra, differential equations, and one additional course). I can conservatively complete a masters by 29-32 (depends on getting into classes when I need them, taking 3-4 classes per year).

What kind of a master's will be built on such a bare bones stripped-down foundation? Physics majors have much more math than this, let alone math majors.

 

[Pavlos Sakoglou]

What kind of a master's will be built on such a bare bones stripped-down foundation? Physics majors have much more math than this, let alone math majors.

I have seen this before. One of my classmates started his masters in math when he was 30 with 3 kids and a full time banking job with almost zero math background.

Of course he realized that it was impossible to finish, thus he started taking 2-3 undergrad classes / year, and gradually 1 masters class per semester, and today, 6 years later, I can say he is quite knowledgeable, with a high GPA, able to comprehend and work with complex problems in various areas (mathematical statistics, PDEs, real analysis etc.).

My point is that it takes extra commitment to pull something like this off, but its doable if you have the guts to forget comfort for quite some time.

A few dimensions to the question at hand so I'll be concise and feel free to provide insight into all or part of the question. Thanks in advance.

Brief background: I'm in my mid 20s, econ/finance undergrad, and passed the first two levels of the CFA but just got into a good university's undergraduate math program. The goal is to complete calculus 2 and 3, linear algebra, differential equations, and apply to a masters program. I'm attempting to optimally allocate my time.

How do colleges (specifically, masters mathematical finance admissions committees) view the CFA?

Is there any "real world" value in having a masters in mathematical finance and the CFA? In other words, does a masters in math significantly outweigh the benefits of the CFA?

If I self-study calc 2 (topics for my course will include: techniques of integration, volume of solids of revolution, infinite sequences and series, differential equations) and enroll in calc 3, how much of calc 2 is applicable to other math classes/topics (e.g. multivariable calculus, linear algebra, stochastic processes, time series modelling, numerical methods, Brownian motion)?

Thanks again.

A masters in math is more significant than CFA.

If you want to understand what you are doing in mathematics and be good at your job later, I would recommend you to start with real analysis and elementary topology, then move on to probability and number theory, mathematical statistics and combinatorics, differential equations, and finally to stochastic processes and SDEs.

Otherwise, you would have so many gaps that you would barely understand a single word from the theorems you would be learning and you will be wasting your time, trying to get your hands clear with procedural calculations that you don't really know their mechanics. Would you hire such a candidate?

 

[HereToLearn]

I wouldn't take most of these comments too seriously. The notion that you need more than the basic calc sequence, linear algebra, and diff-eq is really unfounded for the most part, especially if you're wanting to go into the buy side of things. I think a lot of people on here just assume because you didn't study mathematics or engineering as an undergraduate, you must be a complete moron. For example, I started my MS in Econ and Statistics about a year ago. I entered the program with only Calc II. At this point, I've had to take Calc III and Linear Algebra as prereqs for other courses. So don't let anyone tell you that you can't "get in". Given, I have done a tremendous amount of self study and I love the material, so its not so bad for me.

I'm in my second year now, and I have taken pretty much every class that you might take in a FinMath program besides numerical methods and financial calculus: Time Series Econometrics, Monte Carlo Simulation, Numerical Linear Algebra, Generalized Linear Models, Mathematical Statistics, and Machine Learning. If you want to work in the buy side, most of your work will deal with econometric and statistical analysis and machine learning. If you're wanting to work on the sell side, then yeah, go study fluid dynamics so you can come back to this same board and tell someone they're wasting their time with even the slightest thought of doing something quantitative. I hear it's not that cool anyways.

My point is that I now work at a start up quant hedge fund trading derivatives, and I did pretty much the opposite of what everyone else has said here. It's doable. Here's what I would do:

1. Go to a community college and knock out at least Calc 2/3 and Linear Algebra
2. Apply for a statistics or economics degree that will teach you the same things you want, but without the red-tape of certain math /engineering department prerequisites
3. Network like crazy and learn this stuff on your own. Practice a lot. Learn R, learn Pyhton. Read the literature. Read mathematics, a lot. Become invested and highly interested in the subject. A lot of quant finance outside of the academic realm will be self taught, especially the programming.

Good luck, man

 

[tjk]

I wouldn't take most of these comments too seriously. The notion that you need more than the basic calc sequence, linear algebra, and diff-eq is really unfounded for the most part, especially if you're wanting to go into the buy side of things. I think a lot of people on here just assume because you didn't study mathematics or engineering as an undergraduate, you must be a complete moron. For example, I started my MS in Econ and Statistics about a year ago. I entered the program with only Calc II. At this point, I've had to take Calc III and Linear Algebra as prereqs for other courses. So don't let anyone tell you that you can't "get in". Given, I have done a tremendous amount of self study and I love the material, so its not so bad for me.

I'm in my second year now, and I have taken pretty much every class that you might take in a FinMath program besides numerical methods and financial calculus: Time Series Econometrics, Monte Carlo Simulation, Numerical Linear Algebra, Generalized Linear Models, Mathematical Statistics, and Machine Learning. If you want to work in the buy side, most of your work will deal with econometric and statistical analysis and machine learning. If you're wanting to work on the sell side, then yeah, go study fluid dynamics so you can come back to this same board and tell someone they're wasting their time with even the slightest thought of doing something quantitative. I hear it's not that cool anyways.

My point is that I now work at a start up quant hedge fund trading derivatives, and I did pretty much the opposite of what everyone else has said here. It's doable. Here's what I would do:

1. Go to a community college and knock out at least Calc 2/3 and Linear Algebra
2. Apply for a statistics or economics degree that will teach you the same things you want, but without the red-tape of certain math /engineering department prerequisites
3. Network like crazy and learn this stuff on your own. Practice a lot. Learn R, learn Pyhton. Read the literature. Read mathematics, a lot. Become invested and highly interested in the subject. A lot of quant finance outside of the academic realm will be self taught, especially the programming.

Good luck, man

And he's the former Fed chairman to boot (nothing to sneer at) (y)