University of Chicago - Master of Science in Financial Mathematics

I graduated from the program in December 2022 and will be joining a mid/large size prop trading shop in Chicago as a quant trader. Looking back to the 15-month journey in Chicago, I found UChicago did a tremendous job in helping me build my career path and explore job opportunities in quant finance industry. Here are some highlights:

Onboarding
Students in the program come from various background. The onboarding process and started 2 months prior to the official start date in order to get everyone to the same page.
This experience helps the most for those who have less experience or knowledge about the industry to get ready early for the short and competitive recruiting season.

Career Office
The career office is the strongest support for students’ recruiting. It’s very impressive when you realize there are only 3-5 people supporting over 100 students with their job search, organizing various career events, always replying to everyone’s email promptly while thoroughly, providing personal counseling any time one needs and continuously updating individualized recruiting strategy.
The support and resources I received from this group of people is invaluable.

Project lab
For those who had limited work experience, this is your best chance to get industry experience on your resume. For those who have had experience, this is a good chance for you to work on some solid projects that industry values or even an official offer.
Like everyone else on this review section, project lab added a lot to my experience. To make it simple, comparing the numbers of interview I received before and after I have a project lab experience, it is obvious to see its value.

LOCATION
In addition to the program itself, location is what I considered the best factor for choosing your school, but the decision criterion might differ for everyone.
Chicago being the biggest hub for prop trading firms in the world has the natural competitive advantage for you to break into the industry. As someone who aimed to get into prop at the beginning of the program, this is absolutely helpful. Not only for job search, but also after you join the industry, you’ll be surprised about how many UChicago alumni you will meet during work from your company, your counter parties, and your brokers.
Crime rate, weather etc. being the negative factors for the location do not bother me the most. I do envy the nice sunshine on a winter day on the west coast, but I guess that’s why have breaks and vacations.

Hope this can help you make the right choice.

I recently graduated from The University of Chicago's Financial Mathematics Program in December 2022. I will work as a quantitative analyst of a top custodian bank in US.

My Background
Previously I worked six years as an economist and strategist for a leading financial institution in Asia. My motivation ,target and goal is to learn most top-notch quantitative skills from math to programming to utilize extensive datasets and to provide more convincing investment ideas.

Career Development Office(CDO)
Emily is the most professional, committed, compassionate, enthusiastic, kind, nice, sweetest and the most responsive and the most supportive and the most helpful professional in this program. She CARES student and knows all the answer to the career questions that graduates had. Without her help and support, I would never be able to secure the job offer.

During the interview process, Emily followed up with my job hunting and provided professional and instant response. What Emily offered is the industry standard. Emily provides insightful guidance and customized advice based on different personal background. Regarding to career path choices, there is a lot to consider. Emily will discuss with you all the opportunities and let you know the possible outcome. Emily is there for me when I had to make life-changing decisions.

Career Development Office provides world-class career service and helps with resume writing, LinkedIn updating, Technical Interview Seminar and Mock Behavioral interview Lab.

Student Service
Meredith is always there for students to talk to and share everything from visa consultation, course selection, course registration process, to accommodation for exams. She is extremely helpful with any concern or question that I had.

Meredith organized our events and classes from architectural boat tour to painting class. She is extremely involved with our cohort. The University of Chicago's Financial Mathematics Program seemed more intimate because our cohort felt more like a community.

Course recommendations
There is more to come. You will have the flexibility to choose fixed income and time series courses from the Booth and math & stat courses from both department.

Roger Lee : Mathematical Foundations of Option Pricing/Numerical methods
Professor Roger is not only smart but he also makes sure every student understand the materials. Roger had a magic and a great way of getting everyone understand the hard Math concepts.
What Roger teaches is not only the theory and but also the real world application of it. Roger will go over brain teasers and interview questions that students have seen during interviews at top firms.

Mark Hendricks : Portfolio Theory and Risk Management I
Professor Mark CARES students and is extremely dedicated to his course. Mark designed the homework rigorously and guided students to figure out the thought process. Mark combines python programming applications of portfolio theory using Harvard Business Case study approach in homework and for discussions. That really helps students to understand the real-life applications and essence of quant portfolio theory.

Professor Mark will also prepare statistical interview questions from time series, regression to financial markets analysis like fixed income. Based on my interview experience with banks and funds, most of the questions had been discussed thoroughly in the class and in the seminar/workshop.

Gregory Lawler : Stochastic Calculus
Professor Lawler is the best and the most respected mathematician contemporarily and the pioneer in the stochastic field such as probability and random processes. His lecture is easy to understand and his course is fun and interesting.

Chanaka Liyanaarachchi : High Performance Computing
HPC is the most useful programming course that I took in The University of Chicago's Financial Mathematics Program. Professor Chanaka will dive into various applications from OpenMP to CUDA. We will have the opportunities to have exposure to modern technologies.

Jon Frye : Portfolio Credit Risk: Modeling and Estimation
Professor Jon is the economist and risk specialist from Chicago FED. The lecture that Professor Jon taught in class is industry standard from PD/LGD to vasicek credit risk model. The homework that Professor Jon gave is to ensure students understand the risk management inside and out.

Project Lab
The project lab that I did with my cohort did help me secure the job. We will be able to be in touch with the current developments in finance through their relationships with practitioners.

Cohort
I had true friendship for life when I was in the University of Chicago. I would say that they were my family. Most students are very friendly and willing to help.

The University of Chicago's Financial Mathematics Program
The program has a great team of dedicated professors, career and academic counselors, classmates and students. Its reputation in the quantitative finance industry will open doors for you and you will realize how much you have learned and grown during the 16 months. I would describe this program as the most challenging and most rewarding academic endeavor of my life, and would recommend it to anyone with a passion for learning more about the quant side of finance.

Summary
Two roads diverged in a wood, and I took the one less traveled by, and that has made all the difference.

The University of Chicago's Financial Mathematics Program changed my life. This is one of the best decisions I have ever made in my life.

Graduated in December 2022, working as desk strat at a major bank.

CDO: really on top and provides great connections with employers and alumni.

Curriculum: provides almost all aspect of quant finance knowledge from pricing, computing to economics. Also the teaching staffs are a gold mine. Once you reach out they offer bottomless help.

The program really is a buffet. You can get what you want and all you need to do is to show up and grab a plate.

I graduated from UChicago MSFM last December, and I am set to work as a quantitative researcher at a bank in NY. Overall I am extremely satisfied with the program.

Background:
Hard science undergrad. Several years of experience in finance in Asia. Hope my review is particularly helpful for prospective students who are already experienced in some way, as this was my case.

Why I chose this program?
I was admitted to several programs mentioned in quantnet. I reviewed the course lists of each program. UChicago MSFM had a good mix of theory and domain-knowledge courses, and the course choice was flexible. I knew what courses I wanted to take and not, so this was a big plus. If you were in my shoes, you probably would want to take courses that you need instead of a course in which you're going to get an A. So I encourage you to review the course lists. Also, the program allowed students to take courses from other departments, mainly statistics and Booth. I highly benefitted from this flexibility.
Of the programs I was admitted to, MSFM was the only program that offered project lab each quarter. I participated in the project lab in nearly all quarters and was able to gain insight and connection. It was a big differentiator for me because when I graduate, I'd need to work full-time to get a taste of a business I'm interested in (which is a big commitment).

Course reviews:
Roger Lee: taught option theory and pricing methods. Anything Roger teaches, I highly recommend you take because he is amazing. He can explain complicated concepts in a crystal clear way. Initially, I was not enthusiastic about his options class because I thought I was already familiar with the materials. But I did not regret taking his course. He cleared out all of my bogus mathematics and replaced my complicated solutions with simple solutions. I glimpsed at some of his research papers. Even though I cannot produce this quality research, I could still appreciate his amazing ideas (if you are interested in the topic, you don't need to for exams). What some financial mathematics professors prove with long long lines of hard algebra, Roger, with his brilliant ideas, can prove in much fewer lines.

Mark Hendricks: taught portfolio theory and credit. Mark is a very good teacher and a nice pleasant person. He really cares about students and would go out of his way when you have something to discuss. He emphasizes explaining in words our understanding, which is what you need to do in interviews.

Seb Donadio: taught Python and C++. Seb is probably going to be your memorable professor. One of the most intense courses for me. Even though I was familiar with the languages, I spent a lot of time on assignments and projects. Instructions need some work because they can be vague and confusing, but I encourage people to take his courses to get the full experience of MSFM. The strength of his courses is the domain knowledge he shares. He is a highly experienced professional and doesn't mind sharing what he knows. I appreciate that I learned not only more about the languages but also how they are used in the financial industry. I found his courses very helpful in interviews.

Gregory Lawler: taught stochastic calculus. He is a distinguished scholar and a very good teacher - a must-take for quant finance wannabes.

These are the courses nearly everyone takes, and you can choose the rest of the courses from both the Financial Mathematics department and other departments. You don't want to stack up too much in the Fall quarter due to recruiting. Other quarters can be as hard as you want them. Generally, I am happy with nearly all the courses I've taken.

CDO:
One of my favorites in the program. Emily Backe was a world-class career consultant (no longer part of CDO anymore, promoted for the better good of the program - but she is still here). She is extremely caring and knowledgeable. The CDO had ample industry knowledge that helped me navigate my way. They did not provide just generic career advice.

Summary:
I am extremely happy with the knowledge I gained in the program and the career outcome. I'll stay in touch with people I met in the program. Not really understanding why UChicago's ranking is so low on the quantnet ranking table, though I cannot speak of other programs I didn't attend. But in my personal opinion, the ranking is irrelevant to individual success (as a potential quant finance wannabe, you shouldn't take information as is anyway). I hope the prospective students find a program that suits them most. Wish you success.

I graduated from UChicago FinMath in December 2022 and will be joining as a quant strategist at a Chicago prop shop.

Career Development Office
As mentioned in the previous reviews, Emily is an amazing career advisor. Not only does she give excellent interview and career advice, she also provides the moral support that is needed during the recruitment process.

Course reviews:
There are some courses in the program that I believe are worth taking:
- Portfolio Theory and Risk Management I
- Options theory/Numerical Methods
- Stochastic Calculus
- Regression Analysis and Quantitative Trading Strategies. This course does have mixed reviews but I personally enjoyed it. It gives you an insight on how to manipulate data and simulate simple trading strategies.

For Seb's programming courses, I believe that they are good if you do not have a CS background. If you do, this course is should be more of a review and grinding Leetcode/Hackerrank will be more helpful (which is pretty much the homeworks anyways).

The program also gives you the opportunity to take courses from other departments. Students should leverage this and take courses such as probability and statistics and machine learning courses from other faculties. I also highly recommend that you take a course from Chicago Booth; some of the courses there are very well taught.

Project Lab
Project lab is a nice touch to the program. It allows students to work with industry employers on a quant project. This experience can be used as a resume boost and be talked about during interviews. Students can also get internships and full time roles from this as well.

Conclusion
Overall, I had an amazing time in the program and will really cherish my 15 months there. I would take the Quantnet 2023 rankings with a grain of salt and do your own research into all the Master's programs. At the end of the day, making it to any of the top programs is impressive and finding a full time job will be much more dependent on individual skills and efforts. Hope this review helps!

The cohort consists of a healthy mix of young graduates and more mature students with experience in the industry. This diversity is reflected throughout my experience at the program. Students have prior background in financial mathematics are also allowed to take a certain number of electives from other departments (e.g. the renowned economics program or business school). The new track system allows students to build a more tailored curriculum and focus on areas that they're most interested.

The program is very well-structured, not only in course arrangement, but also in career center's assistance. I find my classmates all have strong undergraduate background so it is a little bit pressure here, but pressure makes progress!

Enrolling in UChicago's Financial Math Program was a game-changer for me. The blend of theory and real-world application, coupled with passionate faculty and hands-on experiences, has made my academic journey truly transformative. The supportive community and commitment to staying ahead in the finance world set this program apart. It's not just an education; it's a personal and professional growth journey. Five stars without a doubt!

Cheers!

My experience at the UChicago Finmath program is definitely life changing for me. The most helpful resources are the networking opportunities with financial industry and plenty of brilliant alumni who are always willing to help me. These factors help a lot in boosting my career. In addition, the courses provide the basic knowledge we will need to handle quant interview, which helped me a lot during my interviews.

Status:
Graduated from UChicago MSFM in December 2023. Will begin working as a Quantitative Strategist in February 2024 in NYC.

Highlights:
- Comprehensive and rigorous curriculum with 4 concentrations available (Financial Computing, Financial Data Science, Options and Derivatives, Trading and Risk) that makes it an extremely focused and goal-oriented program.
- Good interview preparation provided both by CDO (mock interviews, technical interview workshops, company info sessions with a chance to speak with recruiters) as well as through coursework (August review and September Launch which occur before classes start, classes taken in the first quarter prepare you for internship interview questions as well).
- Project Labs offered with reputed companies spanning a variety of project topics. I received two interview requests for a full time role with the company I did a Project Lab with.
- Strong alumni network that participates in panels to help with interview preparation, course recommendations, and general career advice.
- Location advantage with career treks offered to trading companies based in Chicago. NYC based companies also heavily recruit from FinMath.
- Special shoutout to Meredith and Emily who will help you in any way possible and will always give you a shoulder to lean on :)

Course Recommendations:
Any class taught by Mark / Seb / Roger, Quantitative Trading Strategies, Credit Markets, Project Lab.

This program will challenge you in the best way possible and will not only empower you with academic knowledge but also a preparedness for job interviews and professional competence. With a staff that goes above and beyond to help and an alumni network that is so involved, the FinMath program is indeed an exceptional one!

The admission process was quite smooth. There were a couple of self introductory and motivational videos required. Also prior knowledge of mathematics, coding and finance was beneficial.

I loved the Fixed Income courses by Mark Hendricks and used the concepts learned during internships. The Credit Markets course by Alex Popovichi is another fantastic addition to the fixed income enthusiasts.

The career team is quite focused on helping students rather than advertising to prospective new cohort unlike some other schools on this forum. I really like their approach of "Apply Apply Apply" and helping you with connections to other alumni in the same industry and company to get insights that google or LinkedIn just wont provide.

Love the vicinity to so many options and futures companies as well as asset management firms. A wholesome community.

My stay at the UChicago Fin-Math program has been exciting and spectacular.

The courses are very structured and useful. From Options pricing and Fixed Income to Python and Reinforcement Learning, it equipped me with all the necessary knowledge for the practical world. I love Roger, Mark, and Lauler the most, they're the kind of professors who can explain many obscure concepts in very straightforward ways. The more fascinating part is that you can choose various courses from different departments so that you get a chance to learn what you want to learn.

The CDO(Career Development Office) is very supportive, they keep posting kinds of internship or full-time opportunities via email and organize many technical and behavioral workshops to help us better prepare for the real interview.

All these resources help me better land a job in such a difficult job market.

If you're hesitating whether to apply for the program, just go and apply for it right now!

In general, I love the Financial Mathematics program. The students there are smart and eager to learn.

For courses, the required ones are very helpful and highly recommend. They are math and programming focused, but also useful in financial industry. For example, Option Pricing, Portfolio Theory and Risk Management, Stochastic Processes, and Python. Other courses are optional, so it's very flexible for students to develop their path and interest. Some courses are more theoretical, others are more applicable. Students can found courses that they're interested in and make a balance between the academics and interview preparation.

Many students landed a job before graduation. Some students landed a job after graduate. I think the program did well and I'm very satisfied.

Not bad and sounds like things have been improved

What do you think is unique about this program?
Hard to say because I only have second hand info about other programs, but I will try:

I felt like the pace was really fast. When courses drag on too long, it's easy to lose interest and motivation.

Also, there were some really good professors: Paulsen was an excellent lecturer and was very helpful in understanding the material. Lee did real well at explaining and teaching some pretty complex and deep material (for me). Hanson did a great job making stochastic calculus accessible to someone with an engineering background. Even though Fefferman only did a few days of intro on measure theory, he was also excellent at making very theoretical and deep material accesible. There is no shortage of teaching talent, but not every professor is awesome.

What are the weakest points about this program?
The year I went (2009-2010), there were way too many students admitted (~150, which means around 250 people in lecture, including part-timers from previous years). About half seemed legit and about half seemed like undergrads who couldn't get jobs and whose parents had the money to send them. Essentially spoiled brats with no manners. They made it difficult for the instructors because they don't shutup for lecture and they were always suspect of cheating, so the instructors had to be jackasses during exams and during lecture a lot of times. Some of these kids were really bright and some, well, were just kids with no professional experience and no clue how to conduct themselves. Of course, I believe this has changed and the year I went was definitely a transitional period for the program.

This is a minor complaint, but I think there could have been a little more flexibility in the curriculum. For instance, I would've liked to take some computer science classes like machine learning or AI. and perhaps some accounting or more pragmatic finance courses in the business school. It would have rounded things out well if I could've done that.

Career services
I tend to think, "You make your own breaks," for stuff like this. There were quite a few companies recruiting and there were opportunities, just not as many as a b-school student would have. But then, b-school grads get hired into a more broad spectrum of industries and job functions. The school had a decent career website and recruiting process.

The career services I thought were done fairly well, but not outstanding. Tim Weithers did a great job, as did the others.

I and many others found pretty good jobs. A combination of the right fit for a position, a little luck and networking really does a lot.

Of course, that doesn't mean everybody had the same experience I did. I also know some people who had trouble finding a job and either had to revert back to their original job function or had to look for an extended period of time. I'm not sure that's the school's or the program's fault. A bad job market and perhaps lack of planning could've contributed.

Student body
Even though the network was smaller, I met and keep in touch with quite a few people from the program. I have many fond memories of U of C and the program and did a lot of learning there. No amount of disparaging remarks about the program, the professors or the students will change that.

I mentioned the class size above, which made it harder to meet more good people. Again, I believe this has changed and thank God for that.

I recently graduated from the FinMath program in Dec 2019.
Overall Experience:
I was very satisfied with the teaching, career services, and professional opportunities provided. The program is majorly taught in Python, and a few classes are in C++.

Things that can be improved: The program can improve on adding more electives, and improve some of the existing ones (namely Machine Learning). Maybe we can have some more advanced classes being offered as electives outside FINM.

Courses: Stand out courses are Option Pricing, Portfolio theory, Quant Strategies. Another advantage is some of the electives offered are cross-listed with the Business school, or Statistics departments, so you can fine tune the course to your requirement.

Project Lab: One of the best experiences to work with companies (HF,AM,Banks) on real problem that they want explore and solve.

Career Services: We had plenty of networking events, company events and alumni dinners to network. I believe the career office is doing a fairly good job.

I graduated from the UChicago Fin-Math program in 2022 Dec and I am starting my full-time quant trading role at a market-making firm in Chicago in 2023 Feb.

My background:

Undergrad -- Finance & Data Science major with a math minor
Full-time experience -- one year at a wealth management firm

What I liked about the program:

1. Location
- I finished my 4-year undergrad program in NYC and figured that NYC was not for me. I wanted a better blend of a big city but also having some nature / peace and quiet. Since I wanted to become a quant trader, Chicago seemed like the ideal choice being the trading / market-making industry hub, but also having the peace and quiet that I wanted. Its proximity to job opportunities also allows easy networking / coffee chatting.
- The city's architecture is also very nice. There are also a lot of museums that are definitely worth going to.
- The city's rent is much lower than other major cities. (Almost half of NYC's.)
2. UChicago's positive academic reputation
- The school overall is known for its academic rigor, reputable professors, and beautiful campus. With the Fin-Math program, you get access to not just the top-tier Fin-Math courses and professors, but also resources from other programs such as the Booth Business school, the stats program, UChicago Law School, etc..
- Some Fin-Math professors (namely Roger Lee, Mark Hendricks, Seb, and Greg Lawler) are amazing lecturers and have classes that have an amazing blend of theory + practicality.
- There are also out-of-Fin-Math professors (namely Mei Wang in the Stats department) who also teach very good classes.
- There are tons of research opportunities
- There are some times free / discounted social activities (show tickets, Michelin restaurant meals, skiing, etc.) that are posted by the school that's kinda neat.
3. The Fin-Math program's resources
I categorize this program's resources by its (1) courses, (2) career development, (3) other general / life resouces.
(1) courses:
- All of the classes taught by the professors listed above are highly recommended, plus the other recommended classes in other reviews.
- You also get access to non-Fin-Math classes like those in Booth, the stats department, and even the law school for Fin-Math credits.
***But since class schedules / professors may change every quarter, it's better to ask Meredith & alumni what classes to take (or avoid..) when the time comes.
(2) career development:
- Emily Backe in Fin-Math's career development office (CDO) is extremely resourceful, kind, and responsible. She can not only give you the perfect interview prep but also lead you to just the right people you need to speak to for your job search, interview prep, etc..
- Other professors (Roger, Mark, and Seb) will also help you with technical interviews. Their interview prep sessions are extremely useful.
- There are also industry professionals (called IPO) helping you with further interview prep.
- The program is designed in a way such that you get to meet students from a class above you during your first quarter at the program. This makes sure you have students to talk to who can tell you about their school + work experiences, and
(3) other general / life resources
- Meredith is the go-to for all your questions. She is fun, resourceful, and knows EVERYTHING about the program and its people. She will give you her most honest opinion (and all the intel she gathered from all the profs & students) on what classes to take or avoid. She will also lead you to any help you may need since she knows everyone... quite literally.
- The class size is fairly large (~100 people per class), which mean there's a larger variety of students from different background, etc. Students are all very nice here -- you can definitly make life-time friends from the program. Also, many students are very knowledgeable and have many years of work experience -- you can always learn a lot from your classmates.

What I didn't like about the program:

1. City's infrastructure & weather
- Many parts of the city, including but not limited to public transportation, road design, how people don't know how to drive, bad DMV systems, etc. are designed poorly and are extremely inefficient (and sometimes have bad service)
- Too cold.. brrr
- High crime rate (esp around school, aka the Hyde Park area)... However, you do have to be careful everywhere (plus most American major cities do have issues with high crime rates, although not necessarily as bad as Chicago's hyde park area..) Just be vigilant and try not to walk around alone in dangerous neighborhoods, especially when it's dark.
2. Career development office's flaw(?)
- For a while during my time in the program, Emily Backe was gone and the program's CDO was near non-existent with very insufficient support. It's awesome that Emily came back but the program's CDO is very Emily-dependent. Hope CDO hires more reliable staff soon so Emily doesn't need to be overworked...
3. Some classes were poorly taught and were a waste of money & time
- These classes are
4. Minor things that don't necessarily concern others
- Fin-Math's graduation for my year was meh ... The merchandise we got included a bag that has very low quality (had 2 holes already after using it once)
- The winter can be depressing with the school almost empty (most students take online classes in the winter). But it get's better in the spring & fall.

Overall:

- I wanted to give 3.5/5 but QuantNet doesn't let me. Since Emily's back, I'll round it up to a 4/5.
- I didn't give it a 5/5 mainly because of (1) the bad courses that the program offers and (2) the inconveniences caused by the city's bad design / insfrastructure. However, I still gave it a score higher than 3/5 because you still can get what you want from the program.

Background
Master's degree in computer science. Worked for a bank as a risk analyst and currently working as an energy trading strategist for a major energy company. I am located in Singapore and report to boss in UK.
I studied part-time in the Chicago MSMF Singapore program since Sept 2009

Did you get admitted to other programs?
No

Why did you choose this program (over others, if applicable)?
I only applied for UChicago MSFM Singapore as it seems the best choice in Singapore or even Asia in terms of reputation.

Application process
The website was and is outdated. Most of the information regarding this program was found in online discussions. They responded my emails selectively.

Courses selection
1. Course selection is not flexible. I like Statistical Risk Management, Mathematical Foundation Option Pricing and Fixed Income so far.
2. Singapore students can study in Chicago for 1 or 2 quarters our of 3 quarters. a lot of us chose to go to Chicago in Spring quarter Apr - Jun
3. We can choose one course from Chicago Booth, which is only available in Chicago campus

Quality of teaching
1. Practitioners teaching Fixed Income are good. because the course is reduced for some reason they insist offering additional seminar which is not counted in grading.

2. the class is like a video-conference bringing people from Chicago, Singapore and Stamford together. the video quality is good. we can ask questions using a microphone. all classes are recorded and can be played back later.

3. Teachers for each course normally come to teach in Singapore for 2 weeks, giving lectures and office hours.

4. Singapore program has local TAs for every course, mostly previous graduates. They are very helpful. Without TA's help it's not possible to figure out homework. In terms of homework, TAs are much more useful than lecturers.

Materials used in the program
Notes are enough

Programming component of the program
Matlab is dominant. There's C# class but i haven't taken. For me not much programming except the Matlab programming in statistical risk management and regression analysis.

Projects
so far i haven't done any project, expecting one for Regression Analysis.

Career service
1. We visited a couple of banks in Singapore
2. Our resumes are compiled and sent to banks
3. Other than campus recruitment, quite a few immediate openings have been sourced by local career service.
4. nothing specific to intern

Student body
Ethnics are quite diversified and balanced. we are also invited to Chicago Booth alumni gathering in Singapore.

What do you like about the program?
I am much more confident about my math now. previously i picked up some models on my own, which can't compare to what I learn in the program in terms of both coverage and depth.

What DON'T you like about the program?
1. the most important course Stochastic Calculus should be taught much better.
2. the management doesn't care much about publicity. i think for a professional program this is very important. the more people appreciate the program the more value that the current students and previous graduates get.

Suggestions for the program to make it better
I would hire a public relationship manager to advertise the program better.

What are your current job status? What are you looking for?
as a quant strategist in energy trading. i want to expand my skill set further and look for more challenging opportunities, e.g. trading, portfolio manager, deal originator, etc

Background:
- Computer Science undergrad with a few years of work experience as a software engineer.
- Started working as a Trader after graduation in December 2022

Other Admits:
- UCLA and UC Berkley MFE
- Chose UChicago MSFM due to close proximity to many trading firms as well as lower overall cost.

Overall I believe the program has a mixed bag of experiences that bring my rating of the program to a 3.5/5. There are some truly exceptional portions to the program as well as a few downright terrible classes/professors that make you question if you're wasting your time and money.

Pros:
- The program begins 2 months before the official start date. It begins with an August review that brings students to a base level of understanding required in the program. The program attracts students from a wide range of backgrounds and not everyone is fully equipped with the resources to delve into the material. The topics cover a wide range such as regression analysis, probability, programming etc. This time is both useful to brush up on material you may not have experience in as well as prepare you for the level of coursework once classes start.

September launch provides more classes as well as opportunities to meet other students and alumni. There are social gatherings to acquaint incoming students and also workshops and seminars to help you in your job search.

- The first quarter the probably the best part of the program. Roger Lee and Mark Hendricks are both phenomenal professors/lecturers and all three suggested classes (Portfolio Management, Options Pricing and Python) had a lot to teach. This three classes combined with the job search provided a very rewarding first quarter which left me with very high expectations with the rest of the program.

- The support staff are also extraordinary. Meredith and Emily are the two main callouts that come to mind. Meredith is always available for you to talk to, whether it is personal or professional. If there is anything that you need to have done, she is the go to person. Emily is likely the best career advisor I ever worked with/will work with. Saying that she goes above and beyond is honestly an understatement. I genuinely don't know how she was able to make the time to answer everyones questions. She makes sure to understand each student's unique situation and provides insightful guidance even when you yourself may be unsure on what you want/need.

- The program provides flexibility in what electives you want to take. You have the option to take classes from Booth and Stats departments within UChicago.

- All the classes (bar a few where professors forget) are recorded start to finish and uploaded online. This allows you to rewatch to see portions that you may have missed as well as play the video back at 2x speed to review.

- Being located in Chicago it's easier to meet/see many of the trading firms that are located there.

Cons:
- There were a few months where Emily temporarily left the program. This along with a few other changes in the Career Development Office (CDO) were very noticeable. However, now that she's back, maybe things will be back to normal (though she's not in the same role).

- Too many classes that are not worth taking. Further details below.

- Chicago winters and crime

Courses to take: Modern Applied Optimization, Bayesian Stats I and II, Microstructure, Stocalc, Numerical Methods, Portfolio Theory, Option Pricing, Python

Classes to avoid:
- Regression Analysis and Quantitative Trading Strategies with Brian Boonstra: Overall this class taught me very little. It was largely a project class that are focussed on teaching you how to manipulate and display data. The "trading strategies" are incredibly basic and something that you could teach yourself by looking at wikipedia. Grading made no sense as they would often times give you an 80 with the only comment being "Great work". The lack of feedback gives you no opportunity to learn nor the willingness to try on future assignments. This class was likely the biggest disappointment I had in the program as the reviews made it seem like it would be a great class.

- Probability and Stochastic Processes with Jostein Paulsen: The material in this class was actually great, it was just taught very poorly. Partly due to the fact that there was too much material for a 50 credit course, partly due to bad a bad professor. This class could be very valuable if they rework it to be a 100 credit course with more depth.

- Applied Algorithmic Trading with Christopher Gersch: The homeworks were again graded completely arbitrarily with no feedback. The final project also had no feedback and seems to be graded based on entertainment value. It's not a difficult class, but just doesn't provide much educational value.

- Blockchains and Cryptoassets for Finance with Brian Boonstra and Co.: Material was not very informative and some of the homeworks seemed like they were designed for a middle school class.

- There are other classes that I heard bad things about through word of mouth, however since I didn't experience them personally, I won't comment on them.

Tips going in:

- Study the Green Book ("A Practical Guide To Quantitative Finance Interviews”), prior to the program if possible. As Emily and others will tell you, it is never too early to start interviewing.

- Keep track of places you're applying and apply far and wide. Keeping track of your applications during the internship process if very helpful when deciding where to apply come full time.

Can you tell us a bit about your background?
B.S. Engineering Physics (High Honors), University of Illinois at Urbana-Champaign, 2002
B.S. Computer Science (Highest Honors), University of Illinois at Urbana-Champaign, 2002
Five years of IT and software development
I studied full-time in the program from 9/2007-6/2008

Did you get admitted to other programs?
Yes; NYC Courant's Mathematics in Finance and Carnegie Mellon's MS Computational Finance
Why did you choose this program (over others, if applicable)?
Short duration, lower cost of program and of living, reputed heavy mathematical focus.

Tell us about the application process at this program
Online application. Had to submit GRE General test scores. Went smoothly.

Does this program have refresher courses for incoming students? How useful was it?
There were free courses offered to incoming students which were nominally "refresher" courses. In practice, these courses were survey courses in material that students were unlikely to have been exposed to. Several of them were very useful; the measure theory course conducted by Robert Fefferman was outstanding, and the finance introduction by Tim Weithers was well-done.

Tell us about the courses selection in this program. Any special courses you like?
Mathematical Foundations of Option Pricing - excellent
Numerical Methods - excellent
Statistical Risk Management
Stochastic Calculus
Data Analysis And Statistics - disastrously bad
Topics in Economics - well-taught, but questionably relevant
Portfolio Theory and Risk Management - good
Foreign Exchange
Fixed Income Derivatives - wildly mixed quality depending on presenter
Advanced Option Pricing
C# Programming (optional)

Tell us about the quality of teaching
Teaching quality ranged from very competent to insultingly poor.

On the "competent" end, Roger Lee deserves particular commendation for his course preparation and delivery in Mathematical Foundations of Option Pricing and Numerical Methods. The design and delivery of both courses was absolutely meticulous and well thought-out. Other instructors who deserve positive mention include: Paul Staneski and John Zerolis (Portfolio Theory), Lida Doloc (Fixed Income Derivatives), and Jostein Paulsen (Stochastic Calculus, Statistical Risk Management).

Sadly, there were also several instructors who did not appear to feel it necessary to assemble a coherent syllabus or present their material in an understandable fashion to the students in their classes. Chief among these was Per Mykland, who "taught" the Data Analysis and Statistics course (and I believe in most years teaches stochastic calculus as well). His lectures were very rough surveys of material which was inaccessible and unknown to most of the students in the course. Generally, no supplementary reference texts were mentioned to provide comprehensible explanations of the topics covered, and his lecture notes were filled with errors that had clearly gone uncorrected for years. Much of the final section of his notes consisted of text copied directly (save an occasional misspelling) from N.H. Chan's _Time Series_. The material covered by the homeworks was often not addressed by the lectures; in fact, the head teaching assistant informed us in no uncertain terms that he expected most of the class to fail the second homework. The teaching assistants were often unable to help with the homeworks, leading me to believe that they frequently did not understand the material any better than we. Students did so poorly in the class that he announced his intention in the final lecture to simply give all students 'A's in lieu of a final exam (though he was later overruled).

Professor Mykland's disregard for his teaching obligations is legendary; there are discussions on Wilmott Forums of his lack of concern for his audience's comprehension all the way back in 2005 and it seems that little has changed. Unfortunately, data analysis and statistics are fundamental to financial mathematics, and for those of us who did not enter with graduate degrees in statistics, we were left woefully unprepared for the remainder of the courses (particularly stochastic calculus and statistical risk management) as well as job interviews. As a particularly pointed example, I was unclear on what a "standard error" was until I engaged in a program of self-study after his course...in which I got an A-.

Materials used in the program
Primary texts included:
- Hull's _Options, Futures, and Other Derivatives_
- Carmona's _Statistical Analysis of Financial Data in S-Plus_
- Ingersoll's _Theory of Financial Decision Making_
- Bjork's _Arbitrage Theory in Continuous Time_

I also found Baxter and Rennie's _Financial Calculus_ to be an excellent introductory text, though it was not used directly in the courses.

Programming component of the program
Excel, R for statistical analysis, MATLAB for numerical methods, C++ with Quantlib for some interest-rate derivatives work. The introductory programming courses were taught in C# and covered basic ASP.NET. Many of the homework assignments had a programming component.

Projects
There were few "projects" per se, though much of the homework was group work.
Career service
Unknown; I didn't use them.

Can you comment on the social interaction between students of different ethnics, nationalities in the program?
Many of the Chinese students formed a fairly tight social group, I suspect due to shared language. The remainder of the students were very outgoing and mingled and worked together freely.
What do you like about the program?
Excellent instruction in a few topics, a good reading list, U of Chicago name on the diploma, meeting a lot of great people.

What DON’T you like about the program?
The general disregard for the quality of education received by the students.
Suggestions for the program to make it better
- Dismiss Per Mykland.
- Solicit feedback from students to ensure that professors generally are doing a good job, and reward them or remove them accordingly.
- Ensure that professors are aware of how their courses fit into the overall curriculum. Many of them seemed unaware of what students entering their classes would and would not be expected to know.

What are your current job status? What are you looking for?
I am employed by an investment bank as a software developer, and would like to find more quantitative challenges in the near future.

Other comments
If you have a graduate level of statistical experience, are very comfortable with PDEs (and preferably SDEs), and are willing to put up with having to fight to learn in some classes, you could get a lot out of this program. Otherwise, I would suggest going elsewhere.