As it has been mentioned before, the faculty is top notch. Profs Longstaff, Ivo Welch, Lars Lochstoer, Peter Rossi are world class professors.
It's a very packed degree, with a lot of things to digest in very little time + a summer internship. In my opinion, it's easier to absorb all the knowledge with previous experience either in finance, math or coding. Probably 2 out of the 3 would be enough to have a strong experience in the program.
There is a good infrastructure around you. Industry professionals are invited to speak every week or so, you get mock interview sessions, resume preparation sessions, quantitative interview preparation sessions, networking events and so on. I've stayed in touch with the MFE Office and always received all the support I've needed.
For some of the students (me included), learning to connect and network takes some time, and it's hard to do this while staying afloat in your coursework. It's a very demanding 15 months but it's an experience I would definitely recommend!
The professors and faculty are world class. From Peter Rossi, to Francis Longstaff, to Ivo Welch, I've never had the privilege of learning from a more accomplished and well-respected group of people. The level of care they put into each of their lectures was abundantly clear and was leagues above what I experienced at my undergraduate university. They were easy to chat with, always accommodated time after class for additional questions, and, in my opinion, the main reason someone should attend UCLA's MFE program.
The coursework was expansive and quite rigorous. However, there is simply too much information to try and squeeze into a 15 month program. As a result of this squeeze, you feel like you're trying to drink from a fire hose. The flip side of this is that you get excellent exposure to a bunch of different subject areas in quantitative finance and, if you didn't truly have enough time to learn it the first time, you have the tools/materials/means to review it later.
A lot of the posts here are being hard on the MFE's career services, in my opinion. While it took me a nerve-wracking amount of time to obtain my summer internship (got my offer in late March), this wasn't because of a lack of opportunity. I must have had six or seven opportunities before winter break and I simply didn't perform in my interviews. While these were very competitive positions (Morgan Stanley, JP Morgan, etc), it's not the career services' fault that I fell short. I suppose I could say that I wasn't properly prepared to interview but that falls more on myself than the MFE program. A counselor can only take you so far before you have to take responsibility for your own career.
MFE Office / Administration:
I can't thank the lovely ladies in the MFE office enough. Leanna and Elisa were always there to listen to my grievances, help me with petty (and major) problems, and guide me through the program. The amount of students, current and prospective, they have to manage is astounding and they each deserve a raise for all the work they put in.
- Class of 2019 -
Having completed an year in the program, I believe that I am now in a position to give an objective feedback. I will address each of the quarters in the program separately.
Undergraduate form one of the top engineering institutions in India, and with cumulative work experiences of three years in a BB and asset management.
Quarter 1: This quarter has "four building blocks" of our program: Financial Accounting, Econometrics, Stochastic Calculus, Investments.
Financial Accounting: This focuses on the fundamentals of reading (just reading) the financial statements of companies. The course did not, at any moment ,focus on the relevance of each of the concepts in valuation. I finished this course with the hope that the "Financial Decision making"(Corporate finance named fancily) would cover these. More on this later.
Investments: This course is taught by Prof. Chernov and the concepts covered key concepts involving valuation of financial market products, and the theory of asset allocation. The subject was taught well and the assignments were well designed to facilitate learning.
Stochastic Calculus: The course is taught by Prof Panageas, who teaches so well that a person with no background in advanced calculus or probability can get it. The assignments in this course were well designed to reinforce concepts dealt with in class. This course is however introductory only.
Econometrics: Professor Rossi is an excellent teacher and is an expert in this subject. However, I personally felt that this curriculum was similar to that of a STAT 101 course and more content can be included in the curriculum. Devoting 6 lectures (18 hours) to linear regression is definitely overkill.
Empirical Methods in Finance: This course builds upon our fundamental Econometrics course, and a large chunk of it was modelling of time series. This course was a good refresher for me, and professor Lars did an excellent job teaching it.
Derivatives: The course is extremely basic and is not a MFE level course at all. The curriculum is best suited for MBAs, and not suitable for someone who looks to trade/price these securities. Out of the 10 lectures, NONE of them was new to me, or to anyone who has attended the first quarter.
Fixed Income markets: This course is taught by professor Longstaff and is the best course of the lot. The course builds a good understanding the fixed income products and their pricing. Professor Longstaff has tremendous experience and does an excellent job in giving the right intuition. The homeworks are realistic and extremely well structured.
Corporate finance: This course was taught with a lot of animation and the classes were indeed a good break. The course however, like accounting, was poorly structured to meet the needs of an MFE.
Financial Risk Management: This course was taught very well by Prof. Haddad and the homework assignments were interesting and exciting too.
Quantitative Asset Management: This is the worst course in the curriculum and a complete misnomer. The course, like derivatives just repeats content and the homework assignments were even more pointless (at least that wasn't the case in derivatives). The outcome of this course is just frustration and not a solid understanding of portfolio management.
Data Analytics/Machine learning: Taught by professor Lars. Although the course is taught well, and there is zero redundancy, it speaks little on application of machine learning techniques to solve real problems and is just unfortunately just involves using basic R packages to "small data".
Computational Methods in Finance: Focuses on implementation of Monte carlo and other numerical techniques to derivative pricing. It is just a repeat, that develops little understanding of the techniques. The homework assignments were redundant and just served to induce boredom.
Other important aspects:
Co-students: A large chunk of students in the class have absolutely no quantiative background, to the extent that they haven't even heard of "Matrices", get intimidated by seeing the "integral" symbol, do not understand conditional probability even after completing two quarters, and have poor programming skills. Most of them are straight out of undergrad. Although the program offers a paltry introductory math course, I believe this course doesn't serve to improve their understanding.
The review below that strongly advocates for using "Accounting" and "Fama Macbeth regressions" to build trading strategies only serves to demonstrate that people are just unaware of the difference between: expectation and average & attribution and trading. I admire your confidence in betting and LOLing people.
Homeworks: While the majority of assignments are good, some are simply redundant and repetitive. In my opinion, these homeworks should be scrapped. Also, there must be a strong restriction placed on using libraries in homeworks (which defeats the purpose).
Exams: They are just too easy and I actually experience that my undergraduate exams were way harder. The program should acknowledge that correct grading, and a necessary spread in scores are important to enhance the credibility of your grades.
I’m proud to be the UCLA Anderson MFE alumni.
I would not trade my MFE experience @ UCLA for anything else, and let me tell you why:
(1)well structured classes. From basics to extremely complex concepts - everything will be covered. You’ll have plenty of opportunities to test your knowledge working on various problem-sets. It’s laughable to read complaints about Fama-MacBeth and Accounting below. I’d bet those folks just never built a single trading strategy.
(2)team work. Significant part of home assignments are done in small groups. This allows exchange thoughts with peers, improve understanding of material (incl. Fama-MacBeth;) ), and strengthen soft skills that most quants are missing.
(3)ability to provide constructive feedback and be heard. If something is not right, just let administration know. They are there for you to help and make things right. Never hesitate to schedule a meeting with the program’s Executive Director or Career Advisor to discuss suggestions, go through your resume, practice answering interview questions or get advice on job/internship search process.
I’m thankful for help and endless support of members of faculty and administration.
It’s a true honor for me to be part of strong and successful UCLA Anderson MFE family!
I am a UCLA Anderson Alumni from the MFE program class of 2016. Overall the program was stellar. Excellent professors and great guidance for our careers. We had industry professionals come give talks on a weekly basis. The staff was great as well. Elisa Dunn — the Executive Director of the MFE Program — was extremely helpful in assisting me to learn about various industries, develop my career and get a feel for the quant industry as a whole. Leanna Cortez — the Associate Director of the MFE Program — was also excellent in guiding the program and coursework. All the staff were professional and there to help. The professors were phenomenal. A lot of them have invented the knowledge they were teaching and were super clear and concise. In terms of landing a job, some people think that the career services should hand them a job. But that's not how it works. They were there to give the students opportunities and it was always up to the student to take advantage of those opportunities. I do agree with other posts with respect to Python over R and I think this is one of the parts in the MFE program that they definitely need to change. When I graduated companies only wanted Python and not R. It really helped to understand the theory and having gained the ability to program helped too. There is no way I could have gotten to where I am today without having this experience on my resume and learning the skills that were taught during the program. Highly recommend this program to advance your career and get into the company of your dreams.
Jason C. Mercurio
As a recent graduate of the UCLA MFE program, I came across the previous review and thought the need to chime into the discussion.
The executive director and career service can help you only as much as you want to help yourself. You have to work hard to be ready for interviews to get the job. Of course it doesn't help if the executive director doesn't put her head into the game, that shouldn't be the reason you like or don't like the program.
UCLA Anderson is a prestigious school, the professors here are the best in this country. I truly appreciate the time here in Anderson and I have learnt a lot from the professors, especially professor Lars who guided our Final Year Project.
For those who have learnt quantitative finance/math/stats, you would probably feel this program is too easy, but I have definitely picked up new knowledge and skill set. I would highly recommend the program to those who want a change of career into finance.
There are a lot of things you need to learn outside the curriculum to be able to get a job, thats just the reality unfortunately. So you shouldn't expect to be able to find a job very easily upon entering the program, especially when the career service is not helping much.
Long story short, great place to learn, but you are very much on your own when you are on job hunting, which I would say that it is not a completely bad experience, because you can probably find better job opportunity than the career service can find it for you.
Just my 2 cents
I graduated from the UCLA Anderson MFE Program in December of 2018, and enrolled in Fall of 2017 directly following my undergraduate studies. It was a challenging program for me, because I did not have an extensive programming background and my mathematical abilities were not the strongest. However, I had other strengths in my application that the admissions committee considered, and by their faith and trust in me I was admitted.
Not surprisingly, the program was a challenge for me. After the first quarter, I was automatically placed on academic probation as I did not meet the GPA requirements in order to stay enrolled in the program. Once this happened, the Executive Director, Elisa Dunn, immediately reached out to me in order to help me work through this challenge. We spoke together extensively and we devised a plan that I would execute in order to improve my grades. With the help of Elisa and through hard work and determination, I was able to improve my grades and get off academic probation.
Later in the academic year, I encountered a different challenge. This time, the issue was related to the UCLA administration (unrelated to the MFE program) and this threatened to jeopardize my ability to stay enrolled in the program and graduate. I reached out to Elisa again for help, because I had few other people who could help me in my complicated situation. Again, Elisa worked tirelessly to help me resolve this situation and did everything in her power to advocate on my behalf to the university. With her backing, I successfully overcame this obstacle too.
In addition to Elisa, the rest of the staff, including the head of admissions, Leanna Cortez, and the director of career services, Sheila Benko, are incredibly helpful in supporting and advocating for their students. They are truly on your side and want more than anything to see you succeed. Your performance, good or bad, reflects profoundly on them. As a result, there is a true alignment of interests in the program. I was taken aback by the depth and breadth of the lengths to which the entire Anderson MFE staff will go to help you.
Aside from the incredible staff, I want to make particular note of my incredible experience with the Anderson alumni. What is special about the Anderson experience is that you are exposed to a business school legacy that goes back over 80 years. As a result of this legacy, I was able to meet with Anderson alumni (MBA and MFE) in various cities around the world, including New York, San Francisco, and Sydney (yes, Australia!). I found that upon emailing alumni using the Anderson alumni database, almost all were willing to meet with me at a moments notice and eager to help. It is this common bond among all Anderson alumni that is perhaps my most favorite aspect of the school.
It goes without saying that the faculty, courses, and students at UCLA Anderson are world class. That is why I have focused my review on the people in the administration and alumni community who truly made an impact on me.
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.