Latest reviews

This program is perfectly suited for students that want to start their quant career without necessarily having lots of experience.
Compared to other MFEs I heard about (Columbia MFE, MIT MFinance, …), the career service has an impressive number of companies that directly reach out if they are interested in Interns / Full Time graduate students. This makes this MFE so special, - even if there had been some problems recently with the director leaving during the year - most of MFE students across the country have to apply by themselves and hence struggle more to get resume screenings.
Concerning classes, the quantity of the courses is heavy, so students that are tired of enjoying the sunny weather in California shouldn’t worry.

I graduated with a Master's in Financial Engineering from Stevens Institute of Technology, and it has been instrumental in shaping my career in the finance industry. The program's curriculum is exceptionally well-designed, integrating theoretical knowledge with practical applications. Core courses like Stochastic Calculus for Financial Engineers (FE 610), Pricing and Hedging (FE 620), and Portfolio Theory and Applications (FE 630) provided a robust foundation in quantitative finance and risk management, crucial for my role as a Credit Risk Analyst and Quantitative Analyst.

The professors at Stevens go above and beyond to support their students, combining academic rigor with real-world industry experience. Their mentorship has been invaluable, offering personalized guidance that helped me navigate the complexities of the finance sector. Courses like Advanced Derivatives (FE 680) and the Project in Financial Engineering (FE 800), which often involve industry collaborations, were particularly beneficial in applying classroom concepts to real-world scenarios.

Stevens Institute of Technology is renowned for its strong connections to the finance industry, especially given its proximity to New York City. This location advantage, combined with excellent career services, facilitated numerous networking opportunities, internships, and job placements with top-tier firms. The university's reputation as a leading institution for financial engineering is well-deserved, providing a platform that effectively bridges academic learning with industry practice.

I would like to extend a special thanks to Professor Emmanuel Hatzakis, Industry Professor and Director of Finance & Financial Engineering at Stevens. His dedication to his students is truly remarkable. Professor Hatzakis consistently went above and beyond, offering invaluable support and guidance tailored to each student’s individual needs. His commitment to fostering a nurturing and challenging learning environment has made a profound impact on my educational journey and professional development. I am incredibly grateful for his mentorship and unwavering support.

Though I already knew how to code in Python before, this course taught me to code Pythonic!

The MSc in Mathematical Finance at York is a fantastic pick for anyone looking to crush it as a quantitative researcher or dive deep into tough financial maths, even if it’s not as famous as some London schools for quant stuff.

From the beginning, you might be hit with measure-theoretic probability, quickly realising that the material here is no joke—this is far from playing in a sandbox.

When you dive into stochastic calculus, you might find the proof of Ito's Lemma in one-dimensional settings is tough, but this is just the start.

If you're willing to grind through the dissertation stage, you'll find that proving Ito's Lemma is only the beginning, as you might tackle finding some kind of viscosity solutions to your SDE for real quant trading problems.

However, the dissertation stage is based on your own hustle—it's up to you whether you struggle with these advanced topics or just chill on stochastic volatility models.

Don’t expect the UoY maths department to land you a seven-figure salary straight out of the gate. But if you put in the effort all year and learn the key points how to break into the industry, you might likely find your place even before you finish the degree.

The Financial Engineering Master’s program at Stevens Institute of Technology is founded on academic excellence and personal growth. From the very beginning, my admissions process was incredibly personal and attentive with the dedicated efforts from Dr. Emmanuel Hatzakis. His guidance and support made my admission into this program seamless and welcoming!

The curriculum provided an in-depth exploration of subjects including advanced derivatives, algorithmic trading, and stochastic calculus. These core subjects were taught with a level of detail and clarity that not only enhanced my understanding but also sparked a passion for the intricacies of quantitative finance. The program's focus on these advanced topics ensured that I gained a comprehensive understanding of the financial markets and the quantitative techniques used within them.

Moreover, the hands-on learning experiences and real-world applications of theoretical knowledge significantly helped prepare me for the professional world. The program's emphasis on cutting-edge financial engineering practices equipped me with the tools and confidence needed to excel in the fast-paced and ever-evolving field of quantitative finance.

The Master of Science program in Financial Engineering at Stevens is an academic endeavor that paves the way for a successful and fulfilling career. Overall, the combination of having a personal admissions process, exceptional teaching, and practical experience sets graduates up for professional success as leaders in the industry.

The MSc is a good programme if you’re looking for a study to break into quant research. There are more than enough courses which give a good overview of the state of the art research currently being used in the industry. As with all programmes, in general teaching is of a good level, with some positive and negative outliers. However, overall, I would say the MSc is a good programme, especially if you are looking for a solid Mathematical foundation to break into the industry. With that, the good reputation of Imperial also helps, as in general, the programme is well-known to be of a good level by practitioners.

As a recent graduate of the UC Berkeley Master of Financial Engineering program, I feel compelled to share my experience for those considering this path. While the program offers a rigorous curriculum and access to a network of professionals, there are aspects that could be improved.

Curriculum and Instruction: The academic rigor is undeniable, but the practical application of the coursework sometimes falls short. Theoretical knowledge is abundant, yet opportunities to apply these concepts in real-world scenarios were less frequent than I expected.

Career Services and Placement: The career support services were not as robust as I had hoped. A significant turnover in the placement team during my tenure led to a disorganized job search process, leaving many of my peers and myself feeling unsupported in our career aspirations.

Cost and Value: The financial investment in the MFE program is substantial. While I understand the prestige attached to the Haas School of Business, the return on investment is a crucial factor that seems to be glossed over during the admissions process. Prospective students should carefully consider the cost-benefit ratio of this program.

Overall Experience: While I value the knowledge gained and the connections made, the program's execution did not fully meet my expectations. Future improvements in career support, practical application of skills, and a more inclusive culture could enhance the experience for upcoming cohorts.

Pros:
- the whole Oxford experience, i.e. collegiate system, formal dinners, networks, meeting people from various background
- course introduces you to the main concepts in mathematical finance and related mathematical backgrounds (although given that the course is only 9 months long, it is often not that rigorous)
- the Oxford name for applications

Teaching: In general, the teaching quality is average to good. However, it varies significantly between different lectures (i.e. there are some with rather poor quality for Oxford standards). In contrast to undergrad teaching, there are no tutorials with 1-3 students but classes with -20 students taught by (mostly) DPhil students (hence of varying quality). Many professors tend to use slides (which I personally do not like for lectures focusing on mostly mathematical concepts, proofs, etc.)

Assessment: Exams/Take-Home Exams/Online Exams happen at the beginning and end of the Christmas and Easter break (i.e. December, January, March, April), so most of the time in the break has to be used for studying. Deep Learning and Statistics are 48h hour take-home exams/projects which can be quite exhausting. Moreover, in the written exams multiple lectures are assessed in one sitting (e.g. Stochastic Calculus and Financial Derivatives, or Fixed Income, Stochastic Control and Risk Management).

Dissertation: In the last term (i.e. Trinity) there are no lectures/classes, only the dissertation. Nevertheless, due to the short timeframe (-10 weeks) it can still be stressful. The Maths Institute provides a list with possible dissertation topics. Alternatively, the dissertation can be done as part of an internship. The quality of supervision is also very dependent on your supervisor (and/or industry supervisor if you are doing an internship)

As someone who want to break into the quant finance industry but had no experience in C++, I took this course to gain programming knowledge and hopefully improve my competitiveness in master’s program and future job applications. The TAs are very responsive and previous threads on the forum are also very helpful. This is not an easy course and I committed a lot of time to finish it with distinction. Feel proud of what I’ve achieved!

I’m a student just graduated from the class of 2024. I would say that this program is not worth it after Linda leaves. The new executive director quitted halfway and the former associate was promoted. But she has no idea about the quant industry and limited career connection. The whole career office provides limited support and service with the current students because their lack of industry experience and understanding towards the knowledge required in the financial markets. Everything becomes even worse when the job market performs bad in recent years. The only thing that the new director is doing is to seek jobs via LinkedIn and Handshake then email the students to apply for such positions. I would say anyone that holds a high school degree can do this job. When students approached her regarding the employment data she just bullshits. I really hope Linda to be back and save this program.

The Advanced C++ course helped me push to the next level of my C++ learning journey. I was able to utilize everything I learned almost immediately.

Took the course to prepare for interviews, fantastic program!

As with any program there are dipshits, but I think the time our program director has invested into getting good candidates into the MSFE has yielded great results, especially in terms of scholarships. The friends I've made here are definitely for life and we have supported each other a lot.

The program director does a lot to get people jobs by getting us into various corporate sponsored projects. For others this has helped them especially in the interview stage.

The administration/directors of the program are decent at responding to issues. For example, there recently was an issue with international students having to pay extra for OPT that was resolved. I have my old review regarding this issue for posterity on my profile.

One issue, however, is lack of teachers in the business department. This has led to two big issues. One is classes being overlapped with undergraduates. Normally, this wouldn't be the biggest issue, but the derivatives course is going to be at an undergraduate level and not going to get to Black-Scholes, rendering it useless for graduate students. The professor has been great and will try to adjust the course just for graduate students but he shouldn't be forced to do that. Two, the program has professors who have influence on the curriculum and keep their outdated courses in it

I am from the 2024 graduating batch and hence, my opinion will be biased by the way that year was:

Good:
1. Good and diverse peer group - engineers, statisticians etc. 1 had a PhD as well - for many it was their 2nd masters
2. Faculty knowledge - faculty is great, Lettau, Walden, Wallace are GOATs in their fields
3. Great Californian weather
4. Courses are very hands on - if you do all the assignments yourself, you're leaving this program as a very well equipped quant
5. Linda is the queen - she will help you in every way possible - it is very unfortunate that she is no longer leading the program

Bad:
1. Very unprofessional placement team: the director left in the middle of the program, when more than half the batch was unplaced. he did not even wait till a replacement was hired and as a result the placement season was very bad. I thought these actions were very unprofessional. They just got a new director - 7 months after- and she was the old directors deputy. If you're not in her good books, she is not very helpful and can prove to be counter-helpful too
2. 1 year is simply too compressed - each term is 8 weeks and it is simply not feasible to learn graduate level coursework in a good manner in such a short period
3. Grade deflation - the median/mean GPA at Haas MFE is 3.4 which is substantially lower as compared to other MFE prpograms. This is a problem while interviewing with firms that focus on GPA

I found the course through recommendation by one of my senior classmates. He got a satisfying offer and this certificate helped a lot. Also as I know C++ is playing a more and more important role in Financial Engineering so I think it is essential to enrich my background in C++

What truly sets this program apart is Professor Sheng's (also the Program Director) exceptional connections within the finance industry. When I expressed my interest in a niche asset class, she connected me with people who had started a prominent fund trading in that area. Her network facilitated internship opportunities at hedge funds for my friend and me. Additionally, she frequently invites industry leaders to speak and network at the school, such as the CEO of Tower Research, Hedge Fund CIOs, Senior Quant Researchers from big hedge funds, inventors of exotic financial derivatives, and countless others. It feels like she knows everyone in finance, echoing her sentiment that "finance is a small circle." Fordham is extremely fortunate to have her. She genuinely supports promising students. This is evidenced by her helping me secure a sell-side quant role in Europe through her connections. Truly incredible.

As I am part of the first class with Sheng as the program director, it's understandable that the program's ranking hasn't yet reflected her impact. However, it's clear to me that the program is criminally underrated.

While Fordham may not have the broad recognition of some other institutions, its skills, expertise, and network ultimately matter more than the school's name. Compared to schools like Columbia, where students often feel anonymous, Fordham offers a more personalized and supportive environment. I believe Fordham holds its own against even the most prestigious institutions because of Professor Sheng.

Currently, Fordham can be considered a tier 2 school. Fordham offers an incredible value proposition for those who didn't make it to a tier 1 school.

Besides the network potential, there is also the location advantage: if you want to work in finance, would you prefer to be in New York or Georgia? New York or Minnesota? New York or California? The answer is clear.

Found the course searching in Google. Main reasons for choosing it:
I needed to get a proper refresh on C++ but I didn't want Coursera-type courses. Given the author and the TA I thought this course was worth the money. To make it even more worthy I study each topic in other resources so at the end it became pretty heavy. I wanted a proper base on C++ because it's probably the language with which I can better learn Data Structure and complexity basics and it gives a structure in coding in other languages, e.g. Python, which is (probably) easier and gives you a lot of freedom. Freedom without knowing what you are doing can be a bad thing.

Berkeley MFE is a perfect program for students who are going to pursue a job in the financial engineering industry. The curriculum design, the career support, and the reputation of this top MFE program are quite impressive.

First of all, it's not my first experience with coding, so it may make me feel easier to do some of the tasks than others. I heard c++ long ago and knew why it is important in the financial area. Then this program became my first choice since my university does not provide related courses. For the content, all the exercises are interesting, levels are separated in a really reasonable order, I feel so great with APalley and Professor Duffy for giving me useful comments and lectures.