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UCLA Financial Engineering program

UCLA MFE is a 15 month full-time program under UCLA Anderson School of Management

    $60,756 (Class of 2017)
    Application deadline:
    Jan 10, Mar 10, May 31
    Los Angeles, CA
    The Master of Financial Engineering (MFE) Program at UCLA Anderson School of Management merges mathematical and statistical tools with finance theory to equip our students for highly rewarding careers in quantitative Finance. Graduates of the UCLA Anderson MFE Program apply these concepts to build models, solve problems and evaluate opportunities in areas such as risk management, asset management, derivatives trading, corporate finance and data analytics.

    As a fully-integrated part of the UCLA Anderson School of Management, the MFE Program is based on the business school paradigm of merging theory and principle with up-to the-minute business practice. The UCLA Anderson finance faculty is among the best in the world. Consistently top-rated, they are leaders in cutting edge financial engineering research, as well as the practical implementation of current theory.

    In 2017 UCLA Anderson revised and expanded the MFE curriculum. The full-time program will now begin in September and last for 15 months (up from 13 months in the previous year), with graduation in December of the following year. The newly revised and expanded curriculum integrates mathematical, statistical, and computer science tools with finance theory as applied in industry settings. The curriculum consists of 10 core courses, 4 electives (chosen out of 7 offerings), a corporate sponsored Applied Finance Project and a summer internship.

    Curriculum 2017.jpg

    MFE students have comparable levels of quantitative skills but varying professional and academic backgrounds. To see detailed class profiles, please click HERE.

    Class Stats Quantnet.jpg

    Applications are available online, and the application period is divided into three rounds/deadlines. The application cycle begins in October. To learn more about the admission requirements, please visit Admissions Page.

    Career Services
    The UCLA Anderson MFE Program has career services staff solely dedicated to assisting MFE students with career placement, communication skills and resume development, as well as interviewing and negotiating skills.

    Through “Weekly Conversations on Finance”, on campus networking events, various workshops/seminars/panels, and a networking trip to Wall Street, San Francisco and Chicago with the Career Services team, MFE students have an opportunity to foster relationships with professionals in the field.

    The MFE Program has been very successful in placing its graduates in summer internships and full-time positions with prominent financial services firms. The Class of 2014 (43 students) was fully placed 5 months after graduation

    Historically, base salary ranges from $50,000 to $120,000, averaging $90,000. 100% of the MFE students participate in a summer internship.

    Full Time Placement

    Placement Info.jpg


    The UCLA Anderson network is one of the world’s largest and most renowned alumni networks with members in all 50 states and more than 100 countries. MFEs will become members of this network and have access to the alumni database. UCLA Anderson MFE alumni actively participate in academic seminars, speaker events, and host field study projects at their respective organizations. The MFE Program also has regional alumni chapters, through which graduates can expand personal and professional networks, meet with visiting faculty and connect with local business leaders.

    Contact Information
    Click HERE to download the UCLA Anderson MFE Program brochure
    For more details, visit the UCLA Anderson MFE website at www.anderson.ucla.edu/mfe. For general inquiries, contact the MFE office via e-mail atmfe@anderson.ucla.edu or on the phone at (310) 825-3103.

Recent Reviews

  1. Bowen C
    Bowen C
    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.
  2. siavash
    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.
  3. pranavpatwardhan
    About me:
    Graduate from 2016 batch with work experience in Banking and Risk Management. Currently working in Financial Services/Accounting.

    Program Experience:
    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.

    Program Structure:
    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.

    Career Services:
    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.

    Los Angeles:
    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.

    Final Verdict:
    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.
  4. MoneyQ
    About me:
    Graduate from 2014 batch working in asset management.

    About the program:
    Faculty is great and world class.
    Job Markets:
    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.
  5. Udit Gupta
    Udit Gupta
    About me:
    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.

    Bottom line
    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.
  6. Anonymous
    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.
  7. Anonymous
    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.
  8. MFEAlumnus
    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!
  9. rhuang
    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.
  10. GGGG
    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.