The most selective MFE, quant master programs in the U.S.

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This article has been updated in June 2024.
What are the most selective MFE programs? There is no single metric that will definitely answer this question. Undergraduate GPAs, GRE scores are important indicators. But for many, the following are popular metrics of admission selectivity: acceptance rates, yield rate and applicants per available classroom seat. When it comes to acceptance rates, here are the top 10 most selective quant programs in the U.S.

ProgramAcceptance RateYieldApplications per SeatApplicationsAdmitsEnrolled
Baruch College (Financial Engineering)
7.1%
89%​
15.8​
379​
27​
24​
Princeton University (Master in Finance)
7.7%
84%​
18.2​
574​
44​
37​
Massachusetts Institute of Technology (Master of Finance)
9.2%
72%​
15​
1903​
176​
127​
Columbia University (Financial Engineering)
10.1%
86%​
11.4​
1213​
123​
106​
New York University (Mathematics in Finance)
14.4%
32%​
22​
529​
76​
24​
North Carolina State University (Financial Mathematics)
16.7%
73%​
8.1​
269​
45​
33​
Columbia University (Mathematics of Finance)
18.1%
48%​
10.7​
1200​
217​
105​
Cornell University (FE concentration)
19.4%
34%​
11.4​
793​
154​
53​
Carnegie Mellon University (Computational Finance)
20%
61%​
8.2​
781​
156​
95​
University of California, Berkeley (Financial Engineering)
20.8%
69%​
6.9​
529​
110​
76​

* All data is for the entering 2023 cohort of full-time students
Program​
Acceptance Rate​
Yield​
Applications per Seat​
Applications​
Admits​
Enrolled​
Princeton University (Master in Finance)
4.8%
83%​
25​
625​
30​
25​
Baruch College (Financial Engineering)
6.7%
92%​
16.4​
360​
24​
22​
Massachusetts Institute of Technology (Master of Finance)
9.3%
75%​
15.6​
1913​
177​
133​
Columbia University (Financial Engineering)
11.1%
69%​
13.1​
1242​
138​
95​
North Carolina State University (Financial Mathematics)
16.9%
70%​
8.4​
278​
47​
33​
Columbia University (Mathematics of Finance)
18.6%
50%​
10.7​
1105​
206​
103​
University of California, Berkeley (Financial Engineering)
19.3%
68%​
7.6​
590​
114​
78​
New York University (Mathematics in Finance)
21.9%
40%​
11.5​
529​
116​
46​
Cornell University (FE concentration)
22.1%
32%​
14.2​
811​
179​
57​
Carnegie Mellon University (Computational Finance)
22.1%
52%​
8.8​
842​
186​
96​
* All data is for the entering 2022 cohort of full-time students

Acceptance rate: The acceptance rate is the percentage of applicants who are admitted to the program. Generally, a lower acceptance rate indicates a more selective program.
Yield: The yield rate is the percentage of the admitted applicants who eventually enrolled in the program. Generally, a higher yield rate is more desirable for programs. It indicates the ability of a program to attract and retain a high percentage of admitted applicants.

What do you think makes a program selective? Let us know in the comments section below.
 
Last edited:
This article has been updated with data from 2023 incoming cohort vs 2022. The top 3 most selective programs according to acceptance rate are Baruch MFE (7.1%), Princeton MFin (7.7%) and MIT MFin (9.2%).
 
I think that we need a more wholesome picture. For example, the IAQF doesn't have plans to rank programs. the reason behind it is that many think that different aspects are important to different students. A few professionals are I spoke with agree that statistics like class size, employment, cost, etc. should be collected & published. However, they consider them to be misleading to determine a rankings.
 
This article has been updated with data from 2023 incoming cohort vs 2022. The top 3 most selective programs according to acceptance rate are Baruch MFE (7.1%), Princeton MFin (7.7%) and MIT MFin (9.2%).
So this data is for students already enrolled in school. Not for students enrolling in Fall 2024 correct?
 
This article has been updated in June 2024.
What are the most selective MFE programs? There is no single metric that will definitely answer this question. Undergraduate GPAs, GRE scores are important indicators. But for many, the following are popular metrics of admission selectivity: acceptance rates, yield rate and applicants per available classroom seat. When it comes to acceptance rates, here are the top 10 most selective quant programs in the U.S.

ProgramAcceptance RateYieldApplications per SeatApplicationsAdmitsEnrolled
Baruch College (Financial Engineering)
7.1%
89%​
15.8​
379​
27​
24​
Princeton University (Master in Finance)
7.7%
84%​
18.2​
674​
44​
37​
Massachusetts Institute of Technology (Master of Finance)
9.2%
72%​
15​
1903​
176​
127​
Columbia University (Financial Engineering)
10.1%
86%​
11.4​
1213​
123​
106​
New York University (Mathematics in Finance)
14.4%
32%​
22​
529​
76​
24​
North Carolina State University (Financial Mathematics)
16.7%
73%​
8.1​
269​
45​
33​
Columbia University (Mathematics of Finance)
18.1%
48%​
10.7​
1200​
217​
105​
Cornell University (FE concentration)
19.4%
34%​
11.4​
793​
154​
53​
Carnegie Mellon University (Computational Finance)
20%
61%​
8.2​
781​
156​
95​
University of California, Berkeley (Financial Engineering)
20.8%
69%​
6.9​
529​
110​
76​

* All data is for the entering 2023 cohort of full-time students
Program​
Acceptance Rate​
Yield​
Applications per Seat​
Applications​
Admits​
Enrolled​
Princeton University (Master in Finance)
4.8%
83%​
25​
625​
30​
25​
Baruch College (Financial Engineering)
6.7%
92%​
16.4​
360​
24​
22​
Massachusetts Institute of Technology (Master of Finance)
9.3%
75%​
15.6​
1913​
177​
133​
Columbia University (Financial Engineering)
11.1%
69%​
13.1​
1242​
138​
95​
North Carolina State University (Financial Mathematics)
16.9%
70%​
8.4​
278​
47​
33​
Columbia University (Mathematics of Finance)
18.6%
50%​
10.7​
1105​
206​
103​
University of California, Berkeley (Financial Engineering)
19.3%
68%​
7.6​
590​
114​
78​
New York University (Mathematics in Finance)
21.9%
40%​
11.5​
529​
116​
46​
Cornell University (FE concentration)
22.1%
32%​
14.2​
811​
179​
57​
Carnegie Mellon University (Computational Finance)
22.1%
52%​
8.8​
842​
186​
96​
* All data is for the entering 2022 cohort of full-time students

Acceptance rate: The acceptance rate is the percentage of applicants who are admitted to the program. Generally, a lower acceptance rate indicates a more selective program.
Yield: The yield rate is the percentage of the admitted applicants who eventually enrolled in the program. Generally, a higher yield rate is more desirable for programs. It indicates the ability of a program to attract and retain a high percentage of admitted applicants.

What do you think makes a program selective? Let us know in the comments section below.
"Great article! It's fascinating to see how selective these top MFE programs are. The acceptance rates and yield percentages highlight the competitive nature of the field. A few questions:
How have these metrics changed over the past few years?
What factors contribute most to a program's selectivity?
Are there any significant differences in the curricula that might influence these acceptance rates?
Thanks for compiling and sharing this!"
 
Hey @Agrawal_Harsh
You can see historical trend of acceptance rate, application numbers, cohort size on our Programs section. Each program has a page and these data can be found on the Admissions tab. Here are a few examples.

A desired class size determines how a program handles their admission each year. It varies every year as you can see from the historical data above.
 
Could it be because of self selection? Berkley's pre-requisites seem quite demanding compared to other programs. Beyond the standard courses, they also expect
1. Advanced Machine Learning with Python
2. Partial Differential Equations
3. Numerical Analysis
4. TWO Finance courses

Although none of these courses are hard by themselves, I believe this would require special planning since a standard single major degree would probably not include ALL of these courses at the same time.
 
Princeton on it's website has said they received 1064 applications: Record Breaking Applications for Master in Finance Program - Bendheim Center for Finance
How is it 574 here?

edit:
my bad, just realised the data is for 2023
Yeap, it was discussed in January.
 
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