I will try to make this review as comprehensive, accurate, and objective as possible, so that anyone considering UCLA's MFE program will have a clear idea of what to expect.
About me: pursued MFE right after undergrad, main strength in programming before entering program, graduated December 2019.
Overall description of program:
Courses are very condensed. A combination of math (stochastic calculus & statistics / probability), programming, and finance (equity & fixed income, derivatives, numerical methods, accounting & corporate finance) with some courses structured to be similar to PhD courses where you go through academic papers (but definitely not nearly as rigorous as PhD courses). Overall, a quantitative program, but not as programming-intensive as computational finance programs such as CMU and Georgia Tech I believe. Definitely much, much more quant than general MS in Finance degrees.
- Faculty is world-class. Peter Rossi, Ivo Welch, Francis Longstaff, they are all very well known within academia. Levon Goukasian is amazing in lectures. UCLA's finance department has an incredible history.
- Courses are well-designed. I find myself continuously referring back to course powerpoint slides, as well as recommended readings, whether during my internship or preparing for full-time interviews.
- Students are diverse, smart, and hardworking. I really enjoyed getting to know everyone. Also, many of my peers already had full-time work experience in finance, so I learned from them as well.
- I’ve been able to meet MFE alumni who were very willing to help, and very nice. However, I may be biased, as the ones I am able to meet are obviously ones who are willing to help, so keep that in mind.
- Los Angeles is a great place to be, enough said.
- MFE office is very disappointing. Executive director does not care about the program at all. I’m inclined to believe she cared before, but not anymore. It is hard to get in touch with her or ask for her help. Also, when the MFE office makes mistakes, she does not have accountability. She sent us a very unprofessional email regarding our behavior during a trip, even though she was not on her best behavior either. I can go on and on about her, but I don’t want to make it personal. The main takeaway is that there is a lack of strong and effective leadership in the MFE office, and sometimes we feel like it is them against us, when we really should be on the same team.
- Career services is lackluster at best. Not all the blame is on the career office, executive director should be more helpful too. There is a dedicated career services group, and we get weekly lists of job / internship positions to apply for. However, career services have made mistakes here and there. A clear contrast is the career services group for the MSBA program at UCLA Anderson, were their career services group is much more aggressive and effective. I don’t think MFE’s career services is bad, they try to help you and are there for you, but I expected much better, especially given the fact UCLA’s MFE program has been established for a decade, whilst the MSBA program only existed until recently.
- Most of the faculty are from academia, with no or limited industry experience. It would be great to have lecturers who might not be PhDs or full professors, but very established practitioners.
- Most courses are taught in R, with one taught in MATLAB. I hope they can shift to Python, not because it is better (that is arguable for different applications), but because most workplaces are asking for Python fluency.
If we are only talking about the educational experience and rewards, I believe UCLA’s MFE program is competitive with the best MFE programs out there. Our professors are seriously impressive, the coursework is comprehensive and rigorous, and the students are competent. If not for the mediocre MFE office, I would give this program a much higher rating.
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
Positive Quantnet reviews from the previous years greatly affected my decision to choose this program back in 2016. A year later after graduation, I can confirm I made the right decision.
The curriculum is intense and rigorous. The program adapts its curriculum reflecting current market situations and practices. The AFP projects are carefully selected and reviewed by industry participants and professors. The projects certainly help one to stay on top current expectations and practices of current financial market. Although the stress of class schedule and home works is overwhelming, perseverance certainly pays off.
You are mostly on your own in terms of career search. But the program usually provides necessary counselling. It also arranges networking events and career trips in major financial cities. For many of those who don’t have enough experience in their resume, a great internship experience is vital. For many, securing an internship is very tough. But the Executive Director of the program will very frequently check on your internship search, motivate you not to give up and will continuously push you to the right direction. In my opinion, this was very helpful for my own career search.
Lastly, I loved every aspect of LA. At least for me, the events , the surroundings and the people always affect my wellbeing. Only a few miles away from the beach, I couldn’t ask for a better location.
Overall, my experience was great!
I am a recent graduate from this program (Dec 2017). I highly recommend this program to serious students of Quantitative Finance and Financial Engineering.
The program picked us up from a very basic level of knowledge - basic regression & portfolio theory and over back breaking homework and quizzes brought us to the level of cutting edge research in the field.
Below is my expanded rating of the various aspects of this amazing program:
1. Curriculum - 4.5/5 Great depth offered in the area of equity and derivatives, but only 1-2 courses in Fixed income and credit
2. Duration - 5/5 My program was 13 months long - ideal for someone wanting to get back to work quickly
3. Faculty - 5/5 It is an honor to be taught by Prof. Schwartz, Prof. Longstaff, Prof. Lochstoer, Prof. Panageas and Prof. Kraft.
4. Workload - 5/5 Almost kills you, but ends up making you much much stronger.
5. Industry exposure 4.5/5 - The program director and admin staff go to great lengths to invite professionals to share their insights with us and organize visits to various financial centers to interact with professionals. These interactions greatly helped determine what I wanted to do as my career.
I am currently a student graduating in December 2018. The program recently got expanded to 15 months, I am just one quarter in the program. I am going to give you all of the honest reviews, what I like and what I don't like - trust me there's no lying on Christmas.
Things I like:
1. The education quality is absolutely great. I probably learned more material than my entire 4 years of undergrad. Professors love their subjects, treating every moment of teaching you with great enthusiasm. Class are competitive - you really have to work hard to get an A if that's your standard.
2. The career office, they are trying hard to help you. Yes, I am still looking for an internship, but I don't think spoonfeeding you an internship position is part of the responsibilities of any program. When you see those negative reviews about the career offices, they are probably dreaming of landing an internship without going through interviews- Nah too unrealistic. We have interview workshops regularly, networking events, open houses regularly. Rest is on you.
3. A lot of support - I can talk to program executive director anytime I want. She will work around her schedule to meet me one-on-one. The career advising associate director lent me her office for my phone interview once. Tell me how many programs do that!
Things I don't like that much:
1. Not that much flexibility in course selection. More electives would be great. I really enjoy data analytics, I really hope I can take more machine learning courses. But anyway, I am learning it online by myself, it is all good.
2. Possibly locations, maybe we are at a little disadvantage of locations compare to programs in New York, but it's not a killer. We just have to have a little more phone interviews than those people in New York.
3. We could have the program start a bit earlier. Big banks/tech companies recruit early in September, but our program starts in late September. I have to walk into Morgan Stanley test without learning stochastic calculus - not a fun experience.
Ok, what I am trying to say is, this program way exceeded what I was hoping for. I did not have a great experience during undergrad, this program is all I could hope for. Now it's up to me to make the most out of it.
About me: graduated recently from 2016 batch. will start my job in Jan in complex securities valuation.
My colleagues have already given a comprehensive outline of the program. I am going to add what I think makes UCLA MFE Program special and what needs to be improved.
What’s special about the program:
1- The admission process is one of the best: smooth, professional and friendly. Depending on your background, there will be one or two rounds of interview.
2- It’s a business school! Having access to such a rich network is extremely invaluable and goes a long way for job placement. (As a rule of thumb, programs offered by business schools usually require GMAT rather than GRE) Networking is an essential part of job placement.
3- It’s Los Angeles! If there is a heaven on earth, LA is it! Great Weather, Friendly people, lots of space, delicious foods, diverse culture. these will smooth your transition into a new country and improve your quality of life while studying.
4- Considering the variety of jobs looking for MFEs and extreme competition to get those, it is really beneficial to know what type of job you are looking for upon entering such program and to create your own brand from the very first day. UCLA MFE prepares students best for quantitative asset management, valuation and advisory, data analytics, risk management and statistical arbitrage roles (which mostly have python/R/Matlab as core programming language.) If you are specifically looking for jobs requiring C++ such as High-Frequency Trading, then it may not be a good option.
5- Faculty is definitely an advantage. Even mentioning that you have worked on your applied finance project with well-known names in academic and industry such as Professor Longstaff makes you stand out among other applicants in an interview. Professors such as Daniel Andrei, Levon Goukasian are so dedicated that you can reach them anytime with your questions (even after graduation).
6- It’s 13 months! (it can be an advantage or disadvantage!!) a trade-off between higher program intensity and lower cost of living and opportunity cost.
7- This program helps you to build on top of what you already have: if you do not know anything about derivatives, it will teach you the essentials. If you know the basics, you can get an in-depth knowledge of derivatives. And if you are already an advanced user of derivatives, you will have a chance to work on various models, understand their dynamics and hone your coding skills. So COME AS PREPARED AS YOU CAN!
What can be improved:
1- Career services: Considering the number of students, career services department is understaffed. The program deserves an image and footage at least as good as the program itself. Career services team needs both HR and technical members to introduce the program and its students’ qualification. A well-structured program without a proper marketing and presentation.
2- The program should have started earlier in October (which is starting now with the current batch) to equip candidates with requisite math, statistics, programming and finance essentials in the first quarter. We needed more time to digest all the materials in the econometrics course in our first quarter.
3- More flexibility on electives.
Going back, I would definitely choose UCLA MFE in my top three. If I could bet on school future rankings, I would go long this program as I believe it to be greatly undervalued in quantnet ranking.
Graduate from 2016 batch with work experience in Banking and Risk Management. Currently working in Financial Services/Accounting.
Personally, I found the UCLA MFE experience satisfying and enriching. Having considerable experience in the field of banking, I was expecting to gain skill-sets for asset management and other industries such as consulting, Fin-tech. MFE courses and projects gave me the flavor of most of the career paths available for a financial engineer.
Some Plus points:
UCLA MFE faculty is world class. It was amazing and very exciting to learn from professors such as Prof. Rossi, Prof. Schwartz, Prof. Longstaff, Prof. Goukasian and others. Classes such as Fixed Income, Computational Finance, statistical arbitrage taught me practical application and issues with theoretical finance concepts.
The program schedule is very hectic and definitely not for the weak-hearted. The program is supplemented with weekly finance seminars and group activities that helped us widen our knowledge base and perspective. Courses such as Computational Finance, Fixed Income, Quant Asset management provided a lot of hands-on experience for financial model building, model validation/calibration, valuation, and backtesting, which was immensely helpful in our internships. The majority of courses required coding in R/Matlab or Python.
UCLA MFE has the dedicated career service. I felt that career service is understaffed considering the total number of students and the vast variety of career paths. Career services regularly provided us with openings/opportunities with frequent workshops on skill enhancements and guest lectures from successful finance professionals. This year most of the openings were in Risk, valuation and Fin-Tech. There were opportunities for networking with LA-based firms in the form of guest lectures/seminars/events. But it definitely takes effort from student side as well to get a job/internship. In my batch, Students with good tech skills (programming) found it easy to secure an internships/jobs in an early phase. Most of the top banking internships get finalized by Jan/early Feb, so it might be hard to target these internships as most of the relevant courses are taught in 2nd and 3rd quarter.
There is no place like LA. More I traveled to other places, more I loved LA. Amazing weather, amazing neighborhood (Beverly/Hollywood) and a great campus.
Some things which can be improved:
Career services team is bit understaffed and sometimes it is too much work to handle full-time jobs and internships of 2 batches simultaneously.
Less exposure to Python which is now used almost in every quant role.
There is less flexibility with electives and program structure.
UCLA MFE is definitely an amazing program and greatly undervalued in Quantnet rankings. The program is very receptive to feedback and some of the changes that we suggested are already being incorporated. I am pretty sure that with a growing alumni network and proactive changes, UCLA MFE will be one of the top programs in next few years.
Graduate from 2014 batch working in asset management.
About the program:
Faculty is great and world class.
Unique value proposition in the Job markets in So Cal area. Most of the students in my batch got into risk management, valuation and asset management business. On the target lists for most buy side mutual funds as UCLA Anderson ranked top in asset management. Sell side (wall st.) recognition becomes stronger in recent years through alumni connections but still hard to compete with other ”Ivy League” schools. So if you are targeting BB banks, not the program for you unless you are recent wall st job leaver or PhDs!
Relative easy class as comparing to PhD level classes but with a lot of hands on experience. Small group projects every quarter. A lot of finance papers to read. I personally found it great and this helps me a lot in my current job reading some sell side research papers and develop trading strategies.
Sun, beach, palm trees and chill only if you got an offer right after the summer intern (Joking). 15 mins drive from Santa Monica beach! 5 mins drive from Beverly Hills! And no winter!
To sum up:
Great program and definitely undervalued in recent Quantnet ranking.
I am a graduate from the 2015 batch, who came in to the program after considerable work-experience in financial sector, to support my career transition from corporate finance to quantitative finance.
I am sure anyone reading this review, by now must have developed a good sense about Financial Engineering programs, in general. They all comprise mainly 3 components: (1) Finance, (2) Financial Computing, and (3) Maths/Stats, with varying degree of each depending on how a particular program is structured.
When I started narrowing down on a program that would be a right fit for me, I had the following criteria in my mind:
>> I wanted the program to be Fast-paced, to help minimize my opportunity cost; but rigorous enough to make me competitive for the job market afterwards
>> Program to be more ‘Finance-heavy’, since I didn’t want to go into roles where I’d be competing with CS majors or Maths PhDs. Plus, this way I could leverage and develop on my existing knowledge and experience of finance
>> It should have sufficiently strong emphasis on Financial Computing and Financial Maths, to help me get the necessary theoretical background along with required hands-on skills, to allow me to hit the ground running
>> Offer a diverse peer group (in terms of academic background, age group, and ethnicity)
>> Program should be from a well-recognized university, and of course have an impeccable placement record
Overall experience with the program:
Having been through the program, I am happy that UCLA Anderson’s MFE program checked all the items on my list!! Here is how…
>> The program in its current avatar is quite compact at ~13 months, including a 3 month internship
>> The program is housed/owned/driven/directed by the Finance department at Anderson. Which is awesome!! As you must have gathered from other reviews, Anderson’s finance department has historically been one of the strongest in the country and continues to be so. And the faculty loves teaching the MFE program, since the curriculum is more advanced (then say an MBA program), allowing them to share more of what they know.
The curriculum comprises courses with strong theoretical emphasis, such as fixed income markets by the man himself, derivatives, credit modelling, empirical methods, risk management etc. Don’t get me wrong, when I say they have a relatively stronger ‘theoretical’ bent, because they are still enough hands-on programming assignments (fitting short-rate models, forward-rate models, 2 factor/ multi factor, MBS modelling, calibrating cox-process, time-series modelling etc. etc.), which give ample talking points in an interview
>> While financial computing, in a way, gets covered throughout the course by way of in-class examples and coding assignments, there is a dedicated course taken by Prof. Levon, who comes with a strong background in mathematics and finance, and makes certain that you are very comfortable working in MATLAB by the end of his course.
>> Anderson is a strong brand, on account of its MBA program, with a large and strong alumni base, including industry leaders, such as Larry Fink (Blackrock) and Bill Gross (ex-PIMCO)
Along the way, there were also a couple of pleasant surprises in the program:
>> Course work by Prof. Jason Hsu, where he not only covered the literature on well-known equity anomalies (making sure you know the language of the industry in case you walk into an Asset Management role), but has designed the course to be so hands-on that by the end of it I was comfortable working with equities data and replicating results from any academic paper. The skills learnt in this course were directly applicable during my internship.
>> Course work by Prof. Olivier Ledoit, who is this super smart guy, teaches a course on how to beat markets by way of statistical arbitrage – again a highly hands-on course, by the end of which, you have a working stat-arb model. (There is a reference to him in the book ‘The physics of wall street’, in case you’ve read it)
>> MFE students are allowed to attend finance seminars, where academic researchers and PhD job-market candidates from programs across the country, present on their research. It is a great way to learn about current research areas.
What this program is not
Now one thing that this program is NOT, is it is not a PhD program. So even though, the course-work is rigorous, the program simply does not afford the luxury of time to teach or study these topics in as much detail as a PhD would. Mind you, almost every subject which is taught can be made into a research career in its own right. So, if you are looking for that level of depth, any financial engineering program simply won’t make the cut!! Which is why some students go on to do a PhD. However, it does provide you with enough of a foundation to learn and explore further on your own.
Career services/ Job prospects
No review can be complete without a comment on career services. I think the stats published on the program website speak for themselves. All I’d like to add is, the program enables you to explore careers across spectrum – asset management/ hedge fund/ sell side strats/ risk/ fintech/ consulting/ third-party providers of tools/ regulator/ exchange (and others I cannot immediately recall)
Another thing that many students question when considering this program is – how effective is the program in placing students on east coast? Again, I’d advise any prospective student to look this information up first-hand on LinkedIn. You’d be surprised how many students end up working in NY. While the official stats for my batch are yet to come, I’d imagine around one-third have their clocks set on EST.
Anderson’s MFE program is one of the best programs with its unique areas of strength. Housed under the Anderson business school and driven by finance department, it has been designed to be compact, rigorous and yet well-rounded. Plus, it happens to be in one of the coolest cities to not just study, but also work in.
I graduated from class 2015 and here is my review:
1. The program is in business school. Compared with many other MFE programs, it looks decent at least.
2. Really famous faculties in finance area. Some of them even provide personal connections to help students find summer internships and full-time jobs
3. Comprehensive curriculums.
4. Weather and view.
5. Safe. It's in Westwood, close to stone canyon and beverly hills.
Not that good:
1. Need more serious programming training since most candidates didn't graduate from computer science program. Algorithm, Data Structure, Database and Machine Learning are essential for job hunting. As for the programming skill set, we have enough training on Matlab, R and SAS. However, we lack training on python and C++(or Java) which are even more important.
2. If the program could be longer, that would be better. Having 4 classes in one quarter, it's a bit too much. Students need more time to prepare interviews and improve skill sets which are missed in the curriculums.
All in all, it is a very good program. The job placement is very good. The rate of summer internship return offer is pretty high. The ranking of 2015 in Quantnet didn't reflect the true value of UCLA MFE.
I am a 2014 grad from UCLA's MFE program. Like a lot of people who have provided their reviews prior to me, I will also share the things that I liked and did not like so much about this program.
Pros: Personally, the faculty of any program is its backbone. UCLA's finance faculty is one of the best in the world. Every interaction with these hallowed professors is awe inspiring, besides being extremely enlightening. Well structured assignments and project work based on class lectures then prepare the students to deal with the challenges in the real world. This program is very research oriented, so reading academic papers and working on projects based on these is at its core. Learning from great professors, who have built seminal models in various domains of finance and are very well cited in the academia, is surely a huge plus for this program.
The other good things are the great support you get from the career services and the admin teams, the interactions with a talented peer group, and the access to industry leaders through several fora organized by the school.
Cons: I wish the program were longer in duration so that one can go deeper into one's area of interest. Being just a 13 month course, it is super intense and can crush anybody without a strong sense of commitment to one's goals. So if you are looking for a program where you wish to do a great deal in a certain field then a PhD program would be better suited for you.
To sum up, every program has its core; for some it is programming, derivative pricing, etc., for the UCLA MFE program it's finance. To do well in this program and later, you don't need to have a background in finance (although it helps), for you will be made to swim in this ocean. The only question is, do you have the stamina.
I liked the program very much and agree with the recent comments.
A key differentiator of this program is for international students. After the program, students can work on OPT for 12 months and extend it for another 17 months. That's 29 months of work without sponsorship and that's like any other MFE program BUT because graduation takes place in December, students will be able to apply THREE times for the H1b cap gap. For (almost) all other programs it will only be TWO times. And with the enormous ever-increasing number of H1b applications, the odds improve in your favor and are very much needed!
I'm an MFE graduate class of 2014. First of all, I would recommend taking the older reviews with a grain of salt -- the program improves every year and the faculty and staff is very receptive of student feedback.
Course Material: Things taught are very up to date. My favorite class is Jason Hsu's Quantitative Asset Management and Hanno Lustig's Empirical Methods (lots of time series stuff). Both are difficult classes, but it's worth learning as much as possible because contrary to what some reviews said, you can't possibly learn this stuff elsewhere just by googling or watch a YouTube video. I was struggling with a class and tried to hire a Cal Tech Math / Stats Ph.D. to tutor me some material and even he cannot fully explain it in the context of finance. Having a solid understanding of time series / cross sectional regression is very important even if you decide not to stay finance. I am still applying lots of stuff I learned from these classes today for my job. I can also tell you that there are at least two strategies I learned from the program that I am still using for my own portfolio today with much success. There are just so much to learn in this program and it’s up to you to pick which subject you want to master. The career-related seminars and industry panels are all designed to help you understand your career options.
Recommendation: The materials are difficult and require you to get out of your comfort zone and really spend time to learn it. What I mean by this is this program is NOT kindergarten -- you cannot expect to listen to each lecture and be able to ace every homework. You'll need to speak to your class mates, the TA, and the professor if you don't understand something. If you have poor social skills, well, it's time for you to develop it! If you are shy about asking questions, you will not be successful because there's no way you can expect to magically understand everything and work out everything on your own. The old saying goes “no good being the jack of everything but master of none”. So find the career path you want to take and master the material related to the career path of your choice.
Programming: Computational methods really teaches you how to code. Again, like I said, you need to work with your classmates and seek help from the TAs. However, I do feel this class is a bit unfair. The homework solutions are NOT published so you will never know what went wrong. I feel the student who lacks programming background are at a disadvantage here because they would not be able to learn as much as those who already have solid programming skills. The stuff is NOT easy and often the TAs couldn't even figure it out.
Recommendation: You need to be comfortable programming in AT LEAST one language. Whether it’s R, SAS, Matlab, C++ or Python doesn't matter. However, giving my current working experience plus the internship I did, I can tell you that free software always wins. Yes, the company I worked for does use SAS and Matlab, but unless you are of great value to them, they will not spend another $10K a year for you on software. So chances are you have to prove yourself worthy first by writing good algorithms in Python or R. There's a package called Octave in Python that is much like Matlab -- learn that if you have spare time.
Career Service: It's ok. If you need advice you will likely receive great suggestions. It's not like an MBA and it possibly will not be any time soon because on Campus recruiting is just too costly for the companies for a program this size. However, like the faculties said, no one is stopping you from going to the MBA career event. It's true that links are sent to the students and we have to apply on our own, but don't forget that the resume book gets sent to a lot of companies and the school continues to expand its network. I find that very helpful. Occasionally companies will ask for resumes through faculties and this is the MOST helpful since it is likely you will be directly presented to the hiring manager. I can tell you I have several co-workers here from other schools with a similar tuition but received no support at all.
Other thoughts and comments: The students are a bit young and sometimes immature, but not everyone is like that. Often you'll hear the younger crowd complaining about things not handed to them on a silver plate; yet it's them who ditches all the non-graded career activities and cheating on their homework and sometimes exams. The program needs to seriously beef up its standards by severely punishing cheating or code sharing with a zero tolerance. I feel some students found cheating or code sharing did not receive proper disciplinary action.
Advice to applicants: Pass the CFA level 1! I can’t emphasize this enough – if you aren't even willing to do this, then I recommend you reconsider getting into Finance. The material in CFA level 1 will give you a significant head start.
I’m a recent graduate from the UCLA Anderson MFE program. I enjoyed it very much and think it is an excellent program because of these reasons:
Courses/Subjects: The curriculum is broad and covers diverse aspects of finance (risk management, derivatives, quant asset management, risk management, etc.). I felt submerged in many aspects of finance and was able to build a deep understanding of the diverse quant models. All professors are outstanding and really teach the ins and outs of finance. They are specialists in their fields and many of them have helped shape the world of finance! Ideally, I would have liked to see even more programming intensive courses to prepare me even better for the job search afterwards.
Career Services: It was great to have a team dedicated to help you find internships and full-time employment. I got advice on cover letters, my resume, interviews, where to steer my career and much more. The school is well connected to the industry and is always expanding its connections through its alumni network and I was able to leverage upon that. I was able to get a foot in the door with several finance companies across the US through the Anderson alumni network to find a job/internship. But remember, it was always up to me, the candidate, to find a job and be as prepared and qualified as possible. It took a lot of hard work. Going the extra mile in my area of interest was what made me stand out and helped me secure a job.
Advice to applicants: the job market in quant finance is highly competitive. It is good to know what you want before the program starts so that you can really focus on that field and become an expert. CFA and FRM certifications help you prepare for the program but programming skills in Matlab, R, Python, C++, etc. are more important to have before the program starts. It’s a real challenge to learn programming skills from scratch during this intense program.
I would highly recommend this program if you are profoundly interested in quantitative finance.
The reason why I am writing this review is because the UCLA MFE has been underplayed by most applicants as a weak/fledgling program and to increase awareness amongst new applicants about the UCLA MFE and my experience. As a current student in the UCLA MFE 2014 batch, I can say my experience has been absolutely fantastic. Having an undergrad in engineering and an MBA in finance coupled with experience as a programmer, prop trader and a research analyst, I joined the program with a thirst to learn advanced Math & Stats, build and implement models in Finance and move into the buy-side of the financial industry. The information and knowledge imparted in the course was much more than what I had expected and am very satisfied.
About the program:
Since the program spans for only 14 months, it can be extremely demanding, but the knowledge gained in those 14 months is enormous. Students gain a high level of proficiency in subjects like Econometrics, Stochastic Calculus and Computational methods in Finance along with enhanced programming skills in MATLAB, R and SAS.
The career management cell does an excellent job reaching out to companies and everyone has been very successful in securing an internship in my batch. I can't speak about full time jobs, since I am yet to graduate. But looking at the previous batch, I am quite confident that our batch will be well placed. You should also keep in mind that the career management can get you an interview, not a job! It is up to the candidate to impress and convince potential employers of his/her skills and knowledge.
Pros & Cons:
Although, UCLA covers all areas in quantitative finance, the course material caters more towards careers in Asset Management and Hedge funds. If you are looking for an HFT or intense C++ programming or a pure Math finance course then this is not for you. The UCLA MFE is a fine balance achieved by combining the necessary applied Math, Stat and Programming to the field of Finance.
Best taught subjects:
1) Econometrics by Prof. Hanno Lustig: Almost parallel to the PhD level 1 class taught by Prof. Cochrane at Chicago Booth.
2) Fixed Income by Prof. Francis Longstaff: Taught by the man himself. Co-inventor of the LSM method used to price path dependent options which is used by most option pricing models and many more path-breaking achievements.
3) Quantitative Assent Management by Prof. Jason Hsu: CIO of Research Affiliates, which manages more than $169 Billion. What works and what does not from the practical standpoint.
4) Computational Methods in Finance by Prof. Levon Goukasian: Specialist in Portfolio Optimization. After this class you can price almost any derivative security by solving or implementing SDEs and PDEs
My advice to new applicants:
1) Know what you want: It is very important to understand why you want the MFE and what career track you wish to pursue after the MFE. If its Investment Banking associate or corporate finance or general jobs in finance, get an MBA!
2) Be open minded:- A trader at an I-bank is no longer the ideal job! Even if you believe it is, not everyone can get it. Look at other job profiles, the industry is booming with quant jobs in Risk Management and Analytics.
3) Get a CFA level 1 if you don't have experience in finance. The exam will help you answer the most important question, are you really passionate about finance?
I won't be surprised if you see the UCLA MFE ranked amongst the top 5 in the next few years.
Excellent program for those who are serious about either making a transition into finance or are looking to enhance their quantitative finance knowledge. Being housed in the business school and having an ideal mix of industry practitioners and academicians in the faculty helps not to diverge too much from practicality of the quant finance discipline.
One of the very few programs that can help develop an outlook beyond I-banks and into the asset management and hedge fund industry due to its West Coast presence. This is a particularly applicable now as the sell-side is more and more constrained by regulations and people looking to buy-side to come up with innovative solutions.
The program is rigorous, challenging and provides a good balance of the breadth and depth in finance. Lastly, UCLA Anderson has a very strong reputation in the industry and is definitely one that is worth having in one's resume.
What do you think is unique about this program?
World-class faculty. Most courses are hands-on. You learned many techniques that could be actually applied in your future job.
What are the weakest points about this program?
The program is a one-year program, and is very intense. You need to work very hard. But on the other hand, you can get your MFE degree in just one year.
Career service: Career office does a very good job to provide opportunities, workshops, guidance and networking to help students find internships and full time jobs. Getting interviews are not problems. Btw, most job opportunities are in California. If you want to work in California in future, this is a great choice.
Most classes are great, while the bad ones are really bad. Good program to lead you to the door, but you have to finish the score by yourself. Career service need improvement to worth the B-school price tag.
What do you think is unique about this program?
UCLA Anderson has great faculty in finance, we have classes from UCLA Anderson faculties as well as non Anderson or even non UCLA members.
Most classes taught by Anderson Faculty is generally of high quality, some of them have industry experience and very accessible and willing to speak frankly. Class taught by former CS stat arb trader may be one of a kind in MFE program and that is the one I enjoyed most, along with Jason Hsu's Quant Asset Management class.
Holger Kraft's credit class is tough but one can learn a lot from that rigidity (I wish he also told us the class Stochastic Calculus early in the first quarter in replace of current teacher who give a very short-changed SC class that is not enough get us through the job interveiws. If we were told by him, the placement could be much better IMO.)
Accounting and Corp class in the frist quarter have limited value in finding quant positions IMO but they are very good class taught by great Anderson Faculties. It is better to be elective rather than required for MFE student. Plus MFE student could also have class with MBA or even PhD students with no additional cost and there are some really interesting ones.
Faculty from math department seems to be less genuine in the interest to teach finance student. Teaching assistant hired from math grad program lacks interest of helping "money oriented" student, but TAs from Finance and Econ do great job.
The risk management course is absolutely the worst (Previous reviewer mentioned the teacher even does not bother to give grades in time, course and homework were at best poorly designed. ) But the faculty is not from UCLA,(by no means fits Anderson quality), and I do not expect her teaching for future classes given the unpopularity she had this year.
More works can be done in the quality control in terms of the class offered.
The program has good connection with buy side recruiters on the west coast, and CA is a better place to live IMO.
What are the weakest points about this program?
Career service lady made fair amount of effort to advertise the student body, but the effect is quite limited. We had chances to get in touch with IBs like Citigroup, Morgan Stanley and JPMorgan, but majority of the student body are not well prepared at the time of exposure.
The placement result into such positions could be better, if the interview workshops took place in time.
Some information about recruiting process is misrepresented by the career lady which lead to general decline in the confidence of her knowledge and ability. (The career lady had zero experience in financial firms recruiting.)
C++ programing has next to zero training in this program. (Good if you do not like programming, but lack of such important selling skill of quant makes student harder to place in the market)
We have some connections to east coast BB banks, but placement number are limited, partly because of the timing and preparation at the time BB recruits. Many intern positions in rating agencies and local buy side firms. Some international students utilized their own connection to find intern/full time jobs.
UCLA MBA has a good channel of connections to the industry, however such channel is not well utilized by this MFE program, reducing the value of a "Business School Housing" MFE program.
Career lady seems approaching in a more general college level career service manner, not effective enough for specific MFE student. Not good enough for a B-school price tag.
This program is getting better in its visibility to recruiters, but placement number should speak for itself.
Chinese and Indian majority, US minority.
Male majority, female minority.
(well, BB quant recruits has that similar demographics too, pretty common for quant finance career.)
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.
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.
Mostly international (who will pay $54k for a degree with such a little market value).
What do you think is unique about this program?
The faculty at UCLA Anderson is truly great. Most of the courses are very hands-on, you learned a lot of techniques and skills in solving real-world problems. Many professors come with an industry background, so it's interesting to hear them talk about how what we learned in the class could be applied to real world. I especially enjoyed the Fixed Income class given by Professor Francis Longstaff. His class got me interested in the world of fixed income, and the class material proves to be pretty practical and useful when it comes to my current job in short term interest rate trading.
The Quantitative Asset Management class given by Professor Jason Hsu provides the most up to date material in the asset management industry, including the research method they employed and the latest trend in the industry, as the professor himself works as CIO at an asset management firm. The Computation Finance class is a good combination of learning the derivatives pricing theory and the techniques of pricing those options and mortgage backed securities, which is the critical part to financial engineering. All in all, I was really satisfied with the organization of classes and the quality of the faculty.
The fact that UCLA MFE program is housed under Anderson school is one of the reasons why I chose this program against others, because being in business school gives you more resources in terms of job search, networking with alum and learning finance from a more business world point of view. The guest speaker sessions arranged by school, conversation on finance, and the NY Wall Street orientation street are all very good resources in helping you understand more about the finance industry, and that's something you can only find at a business school.
In terms of career service, we have a dedicated career director at UCLA MFE. The program works really hard in helping placing every student for summer internship and full time. Given that the program is still pretty young, not many bulge-bracket investment banks would come all the way to LA to set up an on campus recruit for our MFE students, but we have very good connection with local buy-side firms in LA, and the network and reputation is starting to build up.
But no matter how strong the school's brand name is, in the end, job search still comes down to whether you have a solid enough resume to catch hiring manager's attention. As far as I know, we had many classmates who got interviewed by investment banks and big asset management shops, so getting interviews is not a concern. The harder part falls on whether you are well prepared for interviews, and that's something that can only be done by you.