Hi all - I am trying to develop a final program list. I notice that there are some people who were accepted to both and chose MIT. I see that CMU tends to have higher comp and placement rates, so I wanted to learn their rationale. I think I am missing something about the MIT program - any thoughts?
Why chose MIT MFin over CMU MSCF?
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Compare the coursework between the two programs. In my opinion, they are very different programs in terms of curriculum. Claim: MFin is not a quant program.
Rankings are kind of a flawed proxy from my point of view. MIT is a fantastic program - one of the strengths from my point of view is exposure to corporate finance, which provides the foundation for a broader set of roles than the typical MFE. It seems to assume a higher level of engineering and math background, so it focuses on areas that might be new to the student. US and international brand recognition is top tier, and I have a high level of confidence in the program leadership.
CMU may have less non-finance brand recognition, but is top notch within the industry. Their main strengths are the integrated program, and to be honest, the steering committee's willingness to listen to industry feedback and adjust the curriculum accordingly. The data science and machine learning components I thought would be my favorite, but it turns out StoCal and financial engineering are fascinating. Also, it's been nauseatingly hard for me, but the professors go far out of their way to help. They will not for a second consider lowering their standards, but work to raise the student to them. Keep in mind, I'm far from the brightest bulb among my classmates, so my experience might be different than others.
I also considered straight up comp sci or data science masters, but preferred to have masters program grounded in my field of study. I already had substantial corp fin exposure, so MIT wasn't on my list. Had I been earlier in my career, I would have definitely applied.
Rankings are also a lagging indicator; other programs have made substantial improvements which might take a while to reflect.
CMU may have less non-finance brand recognition, but is top notch within the industry. Their main strengths are the integrated program, and to be honest, the steering committee's willingness to listen to industry feedback and adjust the curriculum accordingly. The data science and machine learning components I thought would be my favorite, but it turns out StoCal and financial engineering are fascinating. Also, it's been nauseatingly hard for me, but the professors go far out of their way to help. They will not for a second consider lowering their standards, but work to raise the student to them. Keep in mind, I'm far from the brightest bulb among my classmates, so my experience might be different than others.
I also considered straight up comp sci or data science masters, but preferred to have masters program grounded in my field of study. I already had substantial corp fin exposure, so MIT wasn't on my list. Had I been earlier in my career, I would have definitely applied.
Rankings are also a lagging indicator; other programs have made substantial improvements which might take a while to reflect.
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I'd refute the claim that it isn't a quantitative program. It is not a financial engineering program, but that does not mean it isn't a quant program. Myself and many more students on the program have accepted roles as buy-side quantitative researchers or sell-side strats. The program is remarkably flexible - in my last semester for example, I am essentially only taking graduate computer science/EECS classes, with little to no direct finance involved.
I think @Onegin's summary is pretty accurate, as per usual!
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That's fair and good to know you can incorporate more computing coursework. I was mainly taking aim at the fact that the required coursework, at least from what I'm able to glean off the website and course syllabi, is far more akin to traditional master's in finance coursework with of course the additional level of mathematical sophistication one would expect from MIT grad finance courses. My claim depends on the assumption that integrated coursework is necessary for a program to be considered a quant one, and so I only disqualified MIT as such because of my limited knowledge of the program's available elective coursework.
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This a fair assesment - of the required courses we have to take, the non-quant oriented would be: Finance Theory, Accounting (Summer 'Bootcamp' term), and then Corporate Finance (Fall Term). There are required quant courses too: Advanced Mathemematical Methods for FE (like a FE primer), Financial Markets (econometrics style financial analysis).
Once you're done with those, which are about 35 credits of the 180+ you can do during the degree, the world is your oyster! I think having access to the whole MIT campus (graduate EECS/CS/Maths/Econ) really goes a long way.
For me the MSCF was the best choice. There's an entire mode of thinking about probability, randomness, and risk neutral pricing I hadn't been exposed to. I also think the equilibrium pricing theory we get is a fantastic framework - not because it's empirically proven, but because it provides a useful starting point for building quantitative strategies. I finished the CFA before I went, but found the finance theory to be an important addition to my way of thinking. I don't think I would have gained the same grounding in the industry literature w/ CS / DS approach. I also bombed the interview for my top DS choice school, so that helped too
Regarding career services, it seems important for a program to have a dedicated career services function. Quant finance is a specific field which requires a lot of relationship building. I'm wary of programs where "you benefit from the career services of our business school" or academic departments who typically place PhD candidates.
For MSCF, I benefited tremendously from their resume and job search training. I can't speak to placement, only because as a mid-career (arguably late-career) candidate I'm so far at the tail of the distribution. I'm not a good fit for analyst / associate roles, so my search after school will depend on relationships I made in the industry prior to school. That said, they seem to be doing a good job and have been incredibly supportive of me every step of the way.
Hi, May I ask which program you finally chose?For me the MSCF was the best choice. There's an entire mode of thinking about probability, randomness, and risk neutral pricing I hadn't been exposed to. I also think the equilibrium pricing theory we get is a fantastic framework - not because it's empirically proven, but because it provides a useful starting point for building quantitative strategies. I finished the CFA before I went, but found the finance theory to be an important addition to my way of thinking. I don't think I would have gained the same grounding in the industry literature w/ CS / DS approach. I also bombed the interview for my top DS choice school, so that helped too
Regarding career services, it seems important for a program to have a dedicated career services function. Quant finance is a specific field which requires a lot of relationship building. I'm wary of programs where "you benefit from the career services of our business school" or academic departments who typically place PhD candidates.
For MSCF, I benefited tremendously from their resume and job search training. I can't speak to placement, only because as a mid-career (arguably late-career) candidate I'm so far at the tail of the distribution. I'm not a good fit for analyst / associate roles, so my search after school will depend on relationships I made in the industry prior to school. That said, they seem to be doing a good job and have been incredibly supportive of me every step of the way.
CMU, but I didn't apply to MIT. If I had a stronger math background, early career with limited finance experience, MIT may have been my top choice. I really think they are doing the right thing with the corporate finance requirements. I had a hard time working on the buyside with MFE interns who couldn't read and didn't understand the logic of financial statements. They had the quantitative apparatus, but lacked the economic intuition.
Thank you for the reply! May I ask why you choose CMU over Columbia? I'd like to know how people compare these two programs, thanks!
I really liked CMU's integrated curriculum, and the strong data science / machine learning component. It's also a joint effort of 4 different schools, which means we're not captive to any one department. Math department programs tend to have strong StoCal, limited programming, stats, and career services. Business School programs may have career services from the business school, but less research-based academic curriculum. And engineering-based programs seem a bit isolated from my point of view.
Also, I didn't apply to Columbia.*
*I applied for 3 cycles. rejected from columbia 1st cycle, and maybe 2nd cycle, but didn't apply for third.
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How did you like the mini format? Did you feel the courses lacked depth?
A lot of the time I wished they lacked depth. Nope. They really make sure you get your money's worth. Really pack it in there.
If you've ever taken a summer course, you know they jam a full semester into 6 weeks. That's kind of what the pace feels like for me, but I think I'm towards the bottom of the distribution. There were a lot of students who were able to overload.
Seriously though, I've been thrilled with the curriculum, especially with how well integrated it is. The classes are kind of hyperlinked between each other.
If you've ever taken a summer course, you know they jam a full semester into 6 weeks. That's kind of what the pace feels like for me, but I think I'm towards the bottom of the distribution. There were a lot of students who were able to overload.
Seriously though, I've been thrilled with the curriculum, especially with how well integrated it is. The classes are kind of hyperlinked between each other.
