University of California, Los Angeles - Master of Financial Engineering

Graduating soon but I’m going to try to give an in-depth and honest review of the program for the incoming applicants. I am generally happy with my own outcome at UCLA and I emphasize this to point out my review is not an expression of personal frustration. I am appreciative of the program, so my hope is my feedback can be used by both future applicants and admin.

Student Quality:

Probably the worst part of this program. Around a quarter of the class admits to having zero prior programming knowledge and I overheard one student say they’ve never taken any calculus before. Also almost a quarter of the program has only a passing interest in quantitative finance and are immediately turned away when they realize the rigor and breadth of knowledge required, and instead pivot to targeting traditional finance roles. Few come into this program prepared with the baseline knowledge required for the coursework or about the industry.

But what’s the worst is the work ethic and culture. For the mandatory career prep coursework before the MFE started, only ~15% completed it by the deadline. The homework load is designed to be handled by a group of 4-5 randomly assigned, but every group I knew of was filled with freeloaders who did not contribute. Cheating on exams is rampant (hint to admin, nobody needs to go to the bathroom that often) and almost everyone’s assignment submissions are thoughtless ChatGPT copy/paste. Lectures are more than half empty and many TA sessions have zero attendance, yet they will complain about how hard the material is, how bad their grades are, and that the MFE didn’t help them find jobs. The department has an unofficial "no Fs" grading policy, which works in favor of many who would otherwise be flunked out.

Despite this, there are many standout individuals who are extremely intelligent and hardworking. The range of quality in this program is shocking, you have professionals with strong international experience somehow in the same cohort as fresh grads who are scared of a matrix and need AI to debug a print statement.

Sadly, behind the scenes the admin has acknowledged that most students here do not have what it takes to work in the quant industry. Admissions should tighten up standards to improve program outcomes, but it’s a chicken and egg problem. Why would good applicants want to join a program with a poor ranking, but the program will continue to have a poor ranking until good applicants join.

Courses/Instructors:

Decent range of electives with generally good quality and depth (the MBA electives are a waste of time and it’s a shame they’re offered, if you want MBA level coursework you shouldn’t be in an MFE) but I’ll focus on the mandatory courses:

Quarter 1:

Investments: The class is a little too basic, spending weeks going over how simple cash flow discounting works, but it picks up faster near the end and gets the job done. Chernov is a knowledgeable and pleasant instructor, but does not come across as very involved. Usually fair assignments and exams.

Financial Accounting: Easily the worst class in the entire curriculum. Accounting being a core class in an MFE is a questionable decision, and while Dill is a pleasant person that responds to feedback, the material is taught poorly and he is also arguably not best suited to teach this course. Individuals from traditional finance backgrounds were getting confused by in this accounting class. This class should be compressed into a 2-week crash course before program starts and replaced with another; dedicating a quarter of the most important semester in the internship search to accounting is a terrible decision. Fair assignments and exams, despite having to pay to do weekly assignments on an online textbook.

Stochastic Calculus: On the opposite side of Accounting, this class is amazing. Panageas is a passionate instructor and this material is challenging but the class is designed for you to pass. His explanations and derivations in class are phenomenal at presenting complicated concepts in simple terms. Challenging assignments but very fair exams.

Econometrics: Another good stand out in the first quarter. Despite Yavorsky coming from a marketing background, he is exceptionally knowledgeable and skilled at presenting econometrics concepts at a technical level. He will not rest until you truly have learned the material, and you will learn a lot of material. Only downside to this class is it is taught in R (including a 1-week R bootcamp before class), let’s let that language die already. Relatively easier assignments but harder yet still fair exams.

Quarter 2:

Derivative Markets: The highlight (or lowlight depending on what kind of student you are) of the entire MFE program. This class is no longer the cake walk described in earlier reviews, it is extremely rigorous and technical and builds on Stochastic Calculus. Reiner is a passionate instructor who knows almost everything there is to know about derivatives, although sometimes he has trouble communicating it to us who are seeing most of this for the first time. It also feels like we are trying to learn too much in too little time or not spending our time on some material wisely. The TA sessions for this class are also a standout in terms of expertise and difficulty, one of the very few TA sessions attended by most students. The assignments are usually very hard and lengthy, as well as the exams. Students perform so poorly, a 0 on his midterm got you a B+ after the curve this year.

Empirical Methods: An extension of Econometrics which is taught by Lochstoer who again is very knowledgeable and pleasant individual. Useful material, but the class doesn’t stand out either positively or negatively. Maybe a little bit too much time spent on old topics like Fama-Macbeth but otherwise a good class. The assignments and exams are of medium difficulty.

Fixed Income Markets: Picks up where Investments finishes off. While it starts again quite slow, it goes into great technical depth of fixed income pricing. Longstaff is an expert, and his strength comes in explaining these hard concepts in layman’s terms during the lecture, then having us go on to implement these ideas in more technical ways during assignments. His assignments vary from easy to hard (but always fair) and his exams were on the harder side.

Trading, Market Frictions, and FinTech: This is an MBA level course that doesn’t go beyond the surface level of a variety of topics and was considered a running joke amongst the entire cohort. Zhang is again friendly and approachable, but her demeanor doesn’t compensate for bad material. I understand the intention behind a class like this, but it needs to be revamped and increased in depth to bring it to the level of quantitative finance. Extremely easy assignments and exams, just forget this class exists.

Quarter 3:

Risk Management: A useful course taught by Haddad. Haddad has an important quality of being able to explain why this material matters and will schedule extra time out of his day to help the class succeed. The main criticism is that it feels like the whole class is just spent talking about different variations of VaR which gets quite repetitive. Medium difficulty assignments and exams.

Data Analytics & ML: A continuation of Empirical Methods taught again by Lochstoer. More interesting but still relatively foundational topics discussed such as non-linear models, otherwise runs exactly like Empirical Methods. This was recently made a mandatory course, which I believe is a positive step for the program. Same difficulty as Empirical Methods.

Quarter 4:

Applied Finance Project (AFP): AFP can be hit or miss depending on the firm you are anonymously selected by and the work group you have formed. This isn’t a class in the traditional sense.

Career Services:
Antoine runs the career team with Jeremy assisting on the administrative front. Both are extremely approachable for help or advice, and Antoine’s strengths lie in creating and rebuilding the alumni networks (alongside Leanna in the admin). There is an annual NY career trip that has been moved to October, to be more in line with recruiting timelines. They also have a resume book and occasionally invite industry speakers, but the career impact of these efforts is not very strong.

Unfortunately, that’s where the positives of the career team end. Nobody has any first-hand experience with quantitative finance, and at times their efforts may even be detrimental. This cohort was forced to attend 9 hours of mandatory MBA coaching on “how to build a story in your interview”, something that would probably get you laughed out of a quant interview if you couldn’t pass the technicals. They do organize technical sessions (QIPS) but these are infrequent, loosely structured, and don’t fulfill the technical preparation needs. Targeted technical preparation is the key to passing quant interviews, and there isn’t anywhere near enough emphasis put on it.

The people in the career team are amazing individuals, but they need a hands-on expert who knows what they’re doing in this industry. Don’t rely on the them to be anything other than a supportive shoulder to cry on. Career outcomes are weak and have been getting worse over time, most graduates don’t go on to work in quantitative finance at all.

Overall:

UCLA’s MFE ranking is deflated by the poor admit quality and career outcomes, but the program instruction is still relatively competitive (top 10 QN peer score, actually above MIT and NYU Tandon). Admin is composed of great people, acknowledges most of its weaknesses, and are attempting to make some changes, but it’s not enough. It also seems like they’re hampered a lot by the department, maybe this is the business school (dis)advantage they always advertise. At the end of the day, this is just another cash cow program targeting internationals just like almost every other MFE out there. Potential applicants, keep in mind what’s hidden in these rankings is there is a selection bias; having met individuals in all MFE programs, it’s not as if Baruch or Berkeley will transform you into expert quants after a year of coursework, they simply tend to admit only those that have the highest probability to succeed in the industry in the first place.

If you are an international applicant, are passionate about breaking into the US quant finance industry, are willing to put in a lot of work inside and outside the classroom, and are able to pay one of the highest tuition fees (and worst scholarships) amongst MFE programs, UCLA’s MFE will get your foot through the door. If you do not tick all these boxes, do not go here.

This last piece of advice applies not just to UCLA MFE applicants but all MFE applicants, perhaps consider a technical non-MFE graduate degree instead (CS, Stats, OR, etc.); something you won’t be told a lot is that all MFE programs are blacklisted at many top quant firms.

Although we had great professors and excellent classmates, there was no 6-month AFP (Graduate Project) and no help from summer interns. We only had one week of AFP, which was the week before graduation. Employment is extremely bad as you might see from the official website. As long as you are accepted by the school from the east coast, do not consider UCLA MFE.

After almost a year of studies, I finally feel ready to submit a review. Currently, I feel incredibly grateful to my undergrad professors, who taught me everything which was needed to get a summer internship. Meanwhile, throughout the school year at UCLA Anderson, the amount of new material was close to none. And don't get me wrong, I came straight from the economics undergrad, not from another master's or even a full-time job. This program is a perfect place for a person who has never heard about the regression and has never learned a single programming language. I will try to explain everything in greater detail below.

Math/Statistics/Econometrics - I don't even know what to start with. Everything is taught at an elementary level. The entire time-series course was dedicated to ARMA(1,1) modeling and especially to the Fama-MacBeth regression. Almost no statistical tests, no theory explanation - nothing. The same can be said about the econometrics class, which felt like stats 101. On the other hand, the stochastic calculus class has a well-rounded curriculum, and Professor Panageas is a fantastic lecturer. And that's all: three "true math" classes on the Financial Engineering program.

Programming - *sigh*. I will start by citing my classmate: "Our program never penalizes people for inefficient implementation, which they should. I've literally seen people writing four nested "for" loops." Everything is implemented in R, and only Professor Goukasian tries to motivate people to use C++. To be honest, programming is simply not taught. Some people are still using Excel for regressions and optimization because the program does not care.

Finance part - it is not as relevant for the MFE, but I feel obliged to mention it. The program's mandatory accounting class (!!!) was taught so badly that people without the prior accounting experience almost did not get it. Fama-MacBeth model has been in so many courses, that it has become an inside joke, but still has never been adequately explained. In the Derivatives class, Professor Eisfeldt did not know the material in her own slides. For example, she barely answered any questions and was not able to explain the math formulas. It turns out that there can be a derivative of the constant, which is non-zero. Many of the classes also repeat each other a lot, which reduces the amount of new material even more. On the other hand, professor Longstaff is an amazing lecturer, and the fixed income class was one of the best at the program.

Faculty - I don't want to say any more bad things. Professors Longstaff, Goukasian, and Panageas are well-qualified and passionate about their subjects. That's what I expected from the MFE, and it is a pleasure to attend their lectures. I believe that if the curriculum had been better, the teaching would have been better, too. Currently, it feels that most of the people simply don't care.

Career Services - I've never seen decent career services. They exist here, and they do something, not like the alumni network. Very often, if you write to alumni, they would simply ignore you. Moreover, as you have probably already understood, it is an MFE degree from the business school, the MS Finance with more numbers. Therefore, be ready to work in asset management or data science if you're lucky. No quant research, no trading, no big-name firms. One more thing to mention, the school claims a productive mix of MFE and MBA - DO NOT TRUST THIS INFO. Yes, in all caps. You are excluded from the community, you do not get any perks, you can't join the clubs, and you are technically not even allowed into the student lounge.

I was extremely excited to be admitted here a year ago, and now I am thinking about a Ph.D. because I would have learned more from spending the huge tuition in the bar.

To sum up, if you have another offer or you do not need a visa - think twice before going here. Twice as two stars, which I give to the program.

I also want to finish with the two quotes I've heard recently:

The only good thing is that "Weed is legal, but that shouldn't be a concern." -- classmate

"You should have not expected anything more from the Master's program. It just serves as a paid accreditation mechanism for the job market later" -- my undergrad professor

Disappointing

What do you think is unique about this program?
Class & Anderson Faculty, lots of practical hands-on projects, possibility to do one rigorous applied finance research project with a topic I'm truly interested in, some networking opportunity.

What are the weakest points about this program?
Disappointing standard of integrity, career service, have never seen any good effort to link students with employers. internships somehow work out but full-time placement is really disappointing. Also they offer $5k as tuition remerbursement to some unpaid internships to make them 'paid'. Absolute zero contact with big banks/wall street firms. Classes are good but not all of them. No variation, everyone takes same classes. Some faculty have absolute no interest in teaching (one even submitted final grade one month after the deadline in the final quarter, yes after commencement & everything was over). Do not market your truly great faculty & their life long research for MFE program/brochure rather try to market your students/placements.

Career services
Whats career service? one comes to b-school to make direct contact with the recruiter & pays high fees. Our career director send out online links for us to apply which many of us consider as spam.If online application works, then no point to come to a good school. Most of option pricing/ interest rate calibration/models including codes are available online why pay $54k for that? career director needs to understand what computational finance is & where potential opportunity lies. Above all, she creates major confusion. 50% of the class secures paid internships (mostly in LA/SF area), rest not worth of mentioning. Full time placement is even worse. There are some big shots in the industry body but what they do regarding career placement is highly questionable.
So before you spend that huge money for tuition, think twice about your other options.

Student body
Mostly international (who will pay $54k for a degree with such a little market value).

This review was submitted anonymously