Is it worth to take a Bachelor degree in Mathematics now?

[owenho]

Dear all,


I am 29 years old, just completed my PhD in Economics recently.
However, I would like to build up my mathematical knowledge and skills for career enhancement (in Financial Engineering area) and am thinking to enrol in Bachelor of Science (Computational Science and Mathematics) to gain deepth knowledge in Mathematical world.

I am currently working as a commercial analyst in am mining engineering and development company for about a year now. I have been trying to get a job in financial engineering area, unfortunately due to lack of mathematical knowledge/programming skills and relevent work experience my job applications have all been rejected.

Now I am thinking to study Bachelor of Science (Computational Science and Mathematics) while I am working as a commercial analyst.

Do you guys think it is worth to study Bachelor of Science (Computational Science and Mathematics) in my case?

PS. BSc (Computational Science and Mathematics) --> Master of Financial Engineering/Mathematics

 

[alain]

I don't think it is worth. You sound like a professional student to me and managers might see it the same way.

How are you applying to FE jobs? Have you gotten any interviews?

 

[Andy Nguyen]

A Bachelor degree in Math contains around 30 credits in math courses so instead of going a full degree, you should only take those courses. I can even think that any PhD should be able to study those courses at home.
It should take you 1,2 years to fill the gaps instead of a whole 4 years. And 2 years for your MFE. Are you ok with no cash flow for the next 4 years and potentially no guaranteed good outcome at the end?

How are you applying to FE jobs? Have you gotten any interviews?
I think the poster said all his application has been rejected due to no programming/math/experience.

What was your original intention of going PhD in Econ? There must be some kind of role for Econ PhD in IB, right?

 

[alain]

I think the poster said all his application has been rejected due to no programming/math/experience.

Yes but an application being rejected doesn't mean he went to an interview. You would think with a PhD in economics you should be familiar with economy in general and also it should mean you should have to tools to learn everything by yourself and/or being somewhat good in research, right? Isn't that what every PhD claims? So, it would take the original poster very little time to learn quickly either the math or the skills to jump to a finance position, not necessarily a quant position.

owenho, how good are you with econometrics? what about statistics?

 

[bigbadwolf]

Do you guys think it is worth to study Bachelor of Science (Computational Science and Mathematics) in my case?

PS. BSc (Computational Science and Mathematics) --> Master of Financial Engineering/Mathematics

What's your current math background? Not necessarily what you took at U, but what you know well right now.

 

[owenho]

Hi,
I didn't have a chance to get an interview for a quant job. Most of my applications were rejected by recruitment agent at first instance.

I wouldn't say I am good at maths even I am a PhD holder.

 

[alain]

What did you study in your PhD? Why did you pick Economics?

 

[Yuriy]

A Bachelor degree after Ph.D.? Are we talking about the US? It is very unusual to pursue a B.S. after Ph.D. I would rather go for a Master degree in Applied Math or Statistics, or a certificate in Math.

 

[EricFleming]

get an MFE and GET INTERNSHIPS. if you don't get internships, no one will look to hire someone so early in their career yet long in the tooth

 

[John]

you need a career make over, like Eric said, a MFE coupled with a paid internship while completing your education is your best bet.

 

[Polik]

Hi :sos:

I'm not 29 years old but being in a bit similar situation. This semester I will finish my BSc. in Finance and I'd like to move into more technical area of finance, like financial engineering. I think I should continue to finish my MSc. in Finance but after that I'd like to take MSc. course in Probability and Stochastic Processes. To enter this course without an entry examination I need to have some courses (Math Statistics, Probability Theory,...) done obligatorily.
My question is whether I should skip the BSc. course and take just those obligatory courses for MSc. free entry? Do I need courses like Linear Algebra, Discrete Math or Differential Geometry for doing financial engineering???
I could use this time for studying programming languages which I don't know (C++, VBA) and some software (MATLAB for example). Do you think this would be more valuable???

 

[bigbadwolf]

Do I need courses like Linear Algebra, Discrete Math or Differential Geometry for doing financial engineering???
I could use this time for studying programming languages which I don't know (C++, VBA) and some software (MATLAB for example). Do you think this would be more valuable???

You need a standard one-semester linear algebra course (that usually ends with eigenvectors and maybe the finite-dimensional version of the spectral theorem). From discrete math, you need very basic results from permutations and combinations (for baby probability theory). If your stochastic course is going to use measure theory, a bit of set theory (also to be found in a discrete math course) will come in handy. But these bits and pieces from discrete math you can teach yourself within a week. And you definitely do not need differential geometry. But once you have some linear algebra under your belt, you will want to learn something about ODEs and then PDEs, particularly numerical methods for calculating their solutions.

Quants work at the interstice or overlap of computing and applied math: ideas relating to time series, principal component analysis, PDEs, optimisation, and stochastic theory are implemented via computer code. A quant is (or should be) an applied mathematician who can convert mathematical ideas into tight, elegant, and accurate code. So don't ignore the math part of it.

 

[Polik]

Thank you Bigbadwolf, I see it will be better to take BSc. in General Math at first.

 

[bigbadwolf]

I see it will be better to take BSc. in General Math at first.

Be careful: most math degrees are not targeted at FE. Ideally it should be something like the undergrad program at Baruch. What you want is statistics, probability, linear algebra, ODEs, PDEs, stochastic processes, numerical analysis/scientific computing, linear programming and other topics in optimisation and courses in C#/C++. What you don't want is courses in topology, abstract algebra, complex analysis, and differential geometry.

 

[Polik]

Well, I see there is maybe better MSc. course on my Uni for purposes of FE. It's called "Numerical and Computing Mathematics" and obligatory Undergrad courses for this MSc. are the ones you've mentioned (Numerical Methods, ODEs, PDEs, Numerical Linear Algebra and also Finite Elements Methods and Functional Analysis).
"Probability and Stochastic Processes" MSc. course seems to be more theoretical what, I suppose, is better for Quantitative Research, right?

 

[bigbadwolf]

Well, I see there is maybe better MSc. course on my Uni for purposes of FE. It's called "Numerical and Computing Mathematics" and obligatory Undergrad courses for this MSc. are the ones you've mentioned (Numerical Methods, ODEs, PDEs, Numerical Linear Algebra and also Finite Elements Methods and Functional Analysis).

Functional analysis may be a bit of a problem: we are looking at Banach spaces and Hilbert spaces of functions. Some advanced theoretical numerical analysis (e.g., approximation theory) takes place in this context. But functional analysis is a fairly abstract subject, and it presupposes a fairly rigorous command of real analysis. Take a look at Rudin's Real and Complex Analysis or Rudin's Functional Analysis (or any number of other books) to get some idea of the flavor. Other than this, the course looks ideal.

"Probability and Stochastic Processes" MSc. course seems to be more theoretical what, I suppose, is better for Quantitative Research, right?

You want the right kind and right amount of stochastic theory and probability. For example, you don't need to know anything about Markov chains. And even the stochastic theory that quants do use is not at the level of Karatzas and Shreve's Brownian Motion and Stochastic Calculus, or Revuz and Yor's Continuous Martingales and Brownian Motion. What you need can be found in the two volumes of Shreve's Stochastic Calculus for Finance (or any number of other books explaining basic probability and stochastic theory to finance people). Instead of too much attention devoted to stochastic theory, pay more attention to numerical analysis and scientific computing (C++/C#, design of algorithms, agile methods (or others of the ilk), UML, etc.).

 

[LTCM]

H.B.Sc. Financial Modelling

Be careful: most math degrees are not targeted at FE. Ideally it should be something like the undergrad program at Baruch. What you want is statistics, probability, linear algebra, ODEs, PDEs, stochastic processes, numerical analysis/scientific computing, linear programming and other topics in optimisation and courses in C#/C++. What you don't want is courses in topology, abstract algebra, complex analysis, and differential geometry.

These are relatively new program but I think the curriculum is a good mix of applied math and computer science. The business school at Western, (Ivey), does pretty well in rankings.
http://www.westerncalendar.uwo.ca/2008/pg1340.html
http://www.westerncalendar.uwo.ca/2008/pg966.html