I recently completed the QuantNet Advanced C++ course and shared my testimonial here. I have several members expressing interest in how I apply specific modern techniques to my job. I hope this will spur more interest in the course and explain things that you can do to generate savings in latency, and running costs which in turn result in huge cost savings.
I work for a large advertising business on the auction side. We received a series of bids from the advertisers and have to show ads to help advertisers and creators while not being overly annoying to the users.
The business has giant scales with hundreds of billions of ad queries daily. The latency requirement is not quite as crazy as HFT, but ads still have to be served within 1...
This article will be updated frequently. If you are a student of the programs below, please feel free to contribute to the course name, link to the course as well as the programming used.
To apply to MFE programs, you have to demonstrate a programming proficiency. Some programs are very specific on what would meet the requirement Others are more lenient.
Below is a look at how different languages are used or taught in various courses at different MFE programs. Starting with the most famous C++, followed by the up and coming Python, and the rest.
Baruch MFE (admitted students required to take Adv C++): MTH 9821 Numerical Methods for Finance
Princeton: Computational Finance in C++
Chicago: Computing for Finance in C++, Advanced...
Whether you're looking for your very first job, switching carers, or re-entering the job market after an extended absence, finding a job requires two main tasks: understanding yourself and understanding the job market. I received several emails asking me for advice regarding quant jobs and various companies that are hiring and what they are looking for specifically. I usually pass on the questions to someone I know and then reply back to them. Over the last month I have got an increased number of such emails. I decided to compile these questions and made some of my own and decided to ask some people who would be better suited to answer these questions.
Over the course of my blog I have had the pleasure to build some really good...
As the title says, as prospective students should be making their decisions, I would like to use this platform to interact with students who might be interested in the career path.
Who Am I: I’m a senior quantitative researcher working in systematic equities. I’m what some might call a “full-stack” quant leading a team on the entire pipeline from data exploration to generating the trades that we want to do (not the actual execution though). I have been lurking on Quantnet for a few years. I did not pursue an MFE, but I did a related master’s degree and my choice for the school was informed by the rankings here. For anonymity reasons, this is not my main account.
About My Company: we are a billion$+ quantitative hedge fund...
If you're toying with the idea of learning C++ for a job in financial services, drawn by the promise of huge pay but put off by the awareness that it's really not an easy language to earn - particularly compared to Python, Rainer Grimm has a message for you: do it. C++ is deeply embedded in the financial services industry, and that's not going to change anytime soon.
"When I first started studying mathematics in 1994, my professor said to me that it wasn't worth learning FORTRAN," says Grimm. "He said FORTRAN wouldn't be used much in the future, but there's still plenty of FORTRAN around now. He said much the same about C++, but when a programming language is used as much as C++ is, it will be used for the next 50-100 years."
What are the most selective MFE programs? There is no single metric that will definitely answer this question. Undergraduate GPAs, GRE scores are important indicators. But for many, the following are popular metrics of admission selectivity: acceptance rates, yield rate and applicants per available classroom seat. When it comes to acceptance rates, here are the top 10 most selective quant programs in the U.S.
Applications per Seat
Princeton University (Master in Finance)
Baruch College (Financial Engineering)
Massachusetts Institute of Technology (Master of Finance)
We are pleased to announce the publication of the QuantNet 2023 Rankings of Financial Engineering programs.
The full 2023 QuantNet MFE ranking is here. For comparison, the 2022 QuantNet MFE ranking is here.
New in 2023 QuantNet MFE ranking
New programs added: Oklahoma State University (Quantitative Finance) and Rutgers University (Financial Statistics and Risk Management)
Employment rate 3 months after Graduation (US only): Percentage of graduates seeking employment who were employed in the US 3 months after graduation.
Average starting salary plus sign-on bonus (US only). These data points are helpful for prospective students who are interested in jobs in the US.
We added students reviews to the ranking in an effort to encourage...
QuantNet is the premier site for keeping abreast of the latest developments in Mathematical Finance. It provides articles from industry experts that can help you get a job and be successful in your career. I endeavor to live up to the quality Andy expects of all his contributors.
Businesses hire people to solve problems. Their main focus is not on the tools you use to do that, it is your job to learn available tools and advise them on their best application. Don’t fall into the trap of advocating a tool just because you figured out how to use it. Keep learning new tools so you are in a position to give the company you work for the most appropriate solution.
A friend of mine rides herd over the Python libraries used at Bank of America...
“Always protect your downside, upside will take care of itself”
Protecting your downside is what I like to do as a profession, it’s the essence of working as a risk manager, it’s something that continues to excite and challenge me!
Growing up as a child, I was always fascinated my numbers and mathematics, somehow I was grasping mathematical concepts very easily . This fascination led me to pursue my undergrad in Mathematics and Statistics at Indian Institute of Technology Kanpur (IITK). Post that, I worked in actuarial science within the insurance/reinsurance industry applying simulation models to understand our insurance portfolio losses. In 2015, after deciding to pursue a career in finance instead, I came to study Master in...
This article appears in QuantNet 2013-2014 International Guide to Programs in Financial Engineering.
When applying to a master’s program, it is not possible to specify the exact requirements necessary to be accepted, because there is flexibility in the process. An application that is weaker in one area might be accepted because of strengths in other areas.
For the most part, the standard of the applicants is very high; however, in some cases, it is apparent that a capable applicant would have fared better with more careful preparation. There are things that candidates could do to improve their chances of admission, especially if they give some thought to this well before the application submission. The purpose of this article is to...
Two of the best things about writing a book are the people you meet and the things you learn when you send drafts around for comments. My new book, Red-Blooded Risk: The Secret History of Wall Street, was no exception. I expected to get the most controversy over the historical material about how Wall Street quantified in the 1980s, as there were a lot of strong personalities involved and credit for virtually every innovation has multiple claimants. However other than some minor corrections, everyone liked this part. While some of that no doubt results from passions cooling after a quarter century, my impression is it has more to do with having the complete story in one place.
No one cared who was the first person to think of a CMO, or...
In this article, one of Quantnet’s Wall Street Senior Executives describes a typical day in his life as a Managing Director in Market Risk at a bulge bracket investment bank.
06:05 - Wake up, shower, dress
06:10 - Briefly question career choice, think about sleeping in and applying for job at Wal-Mart
06:11 - Recall the great staff and intellectual stimulation job provides, recommit self to career
06:30 - Drive to train station
06:43 - Get on train to NYC
07:30 - Arrive NYC, cab to office
07:40 - Address staffing issue involving zealous junior employee irking bosses, leave message for HR
07:50 - Login, check email, get 1st double short cappucino @ Starbucks, grab two risk quants on the way down to catch up on SCAP
08:00 - Attend...
The author of this article works as a prop trader for a securities firm in an emerging market. With a Bachelor in Engineering, he started out as a financial engineer whose job was to develop VBA applications to back test trading strategies for a senior trader. Three months into the job, the trader left and the author was promoted to run his own trading book. He has been trading over a year since. Here is a day in his life. SHARE YOUR STORY
6.15 - Clock alarm sounds. Immediately press snooze button
6.30 - Hear the alarm again and get up. An extra 15 minutes of sleep has been gained.
7.00 - Leave the house for office downtown
8.00 - Have a breakfast at a small diner next to my office building
8.20 - Arrive at the office
8.30 - Check...
In this article, one of QuantNet members describes a typical day as a market risk analyst in a big financial institution. The author holds an MFE degree.
6:45 am – Alarm clock goes off. The good side is that it’s a Friday and I have a weekend to rest. So I quickly get up, take a quick shower, have breakfast and pull myself together. Then pick up FT from the door, quickly skim through the headlines and head to the train for the daily commute.
7:30 am – After reading FT, look over the news on Bloomberg on my cell before I get in the tunnel and get ready for the day ahead.
7:50 am – Get to my desk and check email for any requests either from risk managers or my manager for the CRO . Some days can get extremely hectic and need to be on...
New York’s Baruch College offers a no-frills financial engineering course that’s feeding some of the world’s most elite global trading firms.
Princeton has its Gothic spires, MIT its Great Dome. But for a no-frills lesson in 21st-century finance, head to a lackluster high-rise on Manhattan’s East 25th Street — AKA, Bernard Baruch Way.
Nine flights up, along scuffed linoleum hallways, a handful of math-loving graduate students consider equations that would make most people’s heads hurt. On the syllabus recently: three-dimensional volatility surface structures for options pricing models.
If you have to ask what those are, you probably don’t belong at the elite financial engineering program at Baruch College, part of New York City’s...
We are proud to present an interview with Dr. Kreitzman (UCB MFE) and Dr. Stefanica (Baruch MFE) who have been executive directors of their respective programs since inception. The interview was joined by several alumni of the programs (Cindy Liu/Nikos Rachmanis of Baruch MFE and Trivedi Himani/Yang Guo of UCB MFE) who shared their experiences during their study as well as memorable milestones in their careers.
The interview celebrates the long tenure of Dr. Kreitzman who moved into the private sector at the end of 2021, after two decades plus time as executive director of the UC Berkeley MFE program. For many prospective students and alumni, she is the face and voice of the UCB MFE program.
We'd like to thank all participants who...
In the last ten years, the number of graduate programs in quant finance has exploded, as has the number of MFE grads with an eye on top jobs at big-name firms. A decade ago there were seven graduate level quant programs in the United States; today there are close to a hundred – each cranking out anywhere from twenty to a hundred graduates a year. Just as their students see a MFE degree as a surefire ticket to wealth, universities are trying to cash in on the bonanza of eager (if somewhat naïeve) future quants by offering multiple programs in the field. It’s a great moneymaker for the schools, but are the expectations fueled by these degree factories realistic? Can the finance industry absorb the coming glut of MFEs?
From Amsterdam to Zurich you can attend financial engineering masters programs in all the financial centers in the world, or places off the financial beaten path such as Bethlehem, Coimbra, Potchefstroom or Stillwater. You can be taught by some of the great names in academic quantitative finance—such as Carol Alexander, Marco Avellaneda, Emanuel Derman, Darrell Duffie, John Hull, Robert Jarrow, Mark Rubinstein, Philipp Schönbucher and Steven Shreve (leaving out many just as distinguished)—or by professors who may be as competent, but whose names will not resonate with as many potential employers. You can pay $20,000 to $80,000, and no doubt more or less, and spend one to two years or, in some cases, attend part-time.
Start early. Submitting a grad school application takes time. Rome wasn’t built in a day, and neither will it take a day to complete your application. Plan accordingly.
Know your 'why'. Why you want to get an MFE degree –
Going to grad school is a big decision. It’s expensive and if you’re already working, it can be hard to go back to school when you’re making money.
Applying to grad school because you’re not sure what to do next (so might as well just go to Grad School) often leads to unmotivated applications and subsequently poor results.
More often than not, there comes a time in your career when you realize you’re missing a certain skill set or feel like you need a push for that next step. That moment you realize WHY you want to...
As banks everywhere look to build up their systematic trading teams as a matter of strategic urgency in the face of competition from electronic market makers like Jane Street and Citadel Securities, a new wave of demand for C++ developers has been unleashed.
Justifiably known as one of the most difficult coding languages to master, banks need engineers proficient in C++ to work on the low latency trading systems that are key to winning business from quantitative hedge funds.
Earlier this month, Goldman Sachs' CEO Stephen Scherr said the bank had boosted its entire equities franchise by building a "tech stack" that was "aimed at the systematic clients in prime." Now, Goldman is hiring C++ coders to work on systematic market making...
The C++ certificates have helped thousands of students learn in a practical way advanced C++ skills they used at work and in their future education.
Dr. Daniel Duffy, the creator of the two certificates, will be on the virtual call, along with Mr. Avi Palley, the teaching assistant coordinator for the seminars. Also on the call will be Dr. Dan Stefanica on behalf of the Baruch MFE Program and Andy Nguyen on behalf of Quantnet.
Please join us to learn more about how the course content is tailored to practical needs, how personal teaching assistants support the learning process, the importance of C++ in finance and financial engineering education. This is the first time such an information session is offered and you will have the...
Alysa Turkowitz has over 20 years of experience working at top universities supporting top-ranked graduate programs in the areas of admissions, career services and curricular affairs. While at Columbia, she worked at Columbia Business School, Mailman School of Public Health, and the Graduate School of Arts & Sciences, Statistics Department. Additionally, she provided leadership coaching to Executive and full-time MBAs, served as a Columbia Alumni career coach, and taught as an Adjunct Faculty member at Teachers College, Columbia University. As of 2020, she is the Executive Director for the Master of Financial Engineering program at UCLA Anderson School of Management. Alysa received her BA in Psychology from Vassar College, her MA in...
By Linda Kreitzman, Executive Director of the Master of Financial Engineering Program at Berkeley
Master of Financial Engineering programs’ students have, in my view, a very wide array of job opportunities in front of them, and not just in traditional quantitative finance with roles as strats at an I-bank, or researchers/portfolio managers at a hedge fund, derivatives traders, or in high frequency trading, etc. Financial disintermediation from Fintech firms brought opportunities in areas such as digital payments, robo-advising, peer-to-peer lending, digital insurance (InsurTech), healthcare, etc. We can safely say that domains of all financial intermediation have been impacted by digital finance and that they created data science roles...
The practice of quantitative finance used to be the prerogative of global trading hubs such as New York or London. When major investment banks, hedge funds, or proprietary trading firms were expanding to Asia, they tended to send senior executives from New York or London to selected Asian cities to head quant teams, and staff the team with local junior hires—traditionally smart graduates fresh from college. The quant teams in Asia would look to deploy mathematical models developed and implemented in the U.S. or Europe to the Asian market. In other words, the Western world was the center of innovation in quantitative finance and finance in general, while Asia was passively adopting the products and models developed in the West.
The decision to pursue a degree in financial engineering is an important step in advancing your career. Congratulations! Whether you are seeking to switch careers or advance within the financial services industry, the skills you will acquire are vital to mastering the strategic and analytical demands of the industry.
Applying to graduate school is a big decision—as well as a significant investment of time and resources—and the emotional and rational aspects can influence candidates’ applications and interviews. Those students who prepared in advance have the advantage of conveying a clear and compelling idea of what is motivating their application . . . which is not only important for admission counselors but a worthy exercise for...
Technology has always been a driver in finance. That was true when Nathan Rothschild (the eponymous founder of Rothschild Bank) used carrier pigeons to relay the news of Napoleon’s defeat at Waterloo to London in 1815, something that was obviously going to move the London markets, and an innovation that, at the time, shortened the transmission of the outcome of the battle from days to hours. Technology as a driver in finance is also true today, perhaps even more so. And what’s really driving finance today, from a technology perspective, is Big Data (and Big Compute and Machine Learning and Data Mining and the Cloud, as these oftentimes go hand-in-hand with Big Data).
Which raises the question: What should a modern day quant know about...
"Engineering is not merely knowing and being knowledgeable, like a walking encyclopedia; engineering is not merely analysis; engineering is not merely the possession of the capacity to get elegant solutions to nonexistent engineering problems; engineering is practicing the art of the organized forcing of technological change. Engineers operate at the interface between science and society." - Gordon Brown
The function of finance is to connect providers of capital with users of capital. This can be a simple process. For example, a venture capitalist might find wealthy individuals to fund start-up companies. This venture capitalist might make use of tools such as a spreadsheet and quantitative theory such as discounted cash flow...
A financial engineering graduate degree is primarily a way to start or advance, a career in quantitative finance. It is useful in many ways: not only academically, but practically, by learning about career paths and deciding which suits your interests and background best, and by creating opportunities to compete for the right openings at the right time.
Based on a long experience fostering careers of both young and mid-career students and alumni, I will briefly share pointers on how to put a master of financial engineering (MFE) graduate degree in the larger perspective of a successful career in quantitative finance, from how to decide whether such to pursue an MFE, to thinking about shaping your career path once you graduate.
Dear prospective students,
I recently signed a contract with a top Investment Bank for an Associate C++ Developer position in the Securities Technology Division in New York. Three years ago I had very little programming and math knowledge, and non-relevant work experience. I was just another business admin graduate with ambition to make it in Wall Street one day. Sounds familiar?
Here's what happened:
I came across the C++ Programming certificate in one of my searches for MFE programs in New York, and decided to enroll.
The intro certificate covers a lot of useful stuff, like implementing important data structures such as vectors (dynamic arrays) and stacks (adaptor containers), Object-Oriented hierarchies for polymorphic behavior...
Since writing for this blog in January about the HFT/algo job market, I’ve received many inquiries from students asking about the “requirements” for quant jobs on Wall Street. “Do I need a PhD?” is a frequent question. Each time I receive one of these inquiries, I struggle with the answer. My instinct is no. But when I look at who is working in these jobs, I do see a predominance of PhD’s in the top positions. PhD’s in mathematics, physics, operations research, EE, etc. are common in the quant community. So it’s tempting to tell students that a PhD is helpful, but it feels like the wrong answer. In my gut I know that the people getting these jobs are not getting offers because they have extra letters after their name. The people...
Questions about job-hunting, your career path, workplace issues, interview and review preparation, salary and benefits negotiation? Ask Ellen Reeves, one of the contributors to QuantNet 2012-2013 International Guide to Programs in Financial Engineering.
Career and workplace advisor Ellen Gordon Reeves is the author of Can I Wear My Nose Ring to the Interview? A Crash Course in Finding, Landing, and Keeping Your First Real Job, featured in media including CNN, CBS, EXTRA, Fox, ABC, @katiecouric, NPR. She consults to programs including the financial engineering/risk management programs at Baruch College and The University of Washington, preparing students for the job market.
Reeves is the creator of Extreme Professional Makeover: Boot...
Preparing for a Career in the Field
When preparing for a career in Financial Engineering, it’s helpful to know what you need to know in order to be considered a good candidate for a job, as well as how to be successful in that role once you are hired.
First, you should know that the general utilization of an MFE degree tends to be oriented toward quantitative roles on the desk (i.e., working on the trading desk and delivering the models, risk calculators, etc., directly to the traders who utilize their products), or in risk management, model validation, and library control, CVA, or quantitative development and programming.
I’ve been a recruiter for more than 14 years, and have worked exclusively in quantitative finance for the last 12...
A recent NYT article sheds light on how the trading landscape has been changing on Wall Street, due to technological advances as well as regulatory reforms such as the Dodd-Frank financial legislation.
The article makes clear that technology has been and will play a HUGE part in the industry as an increasing volume of trading occurs over automated exchanges as required by laws or other factors.
"The increased use of automated platforms means that more programmers are needed, but fewer employees over all."
The trading desks at Credit Suisse are demonstrations of how changes have transformed the type of trading and traders needed for the job.
"The traders here are mostly educated in math or physics, often outside the United States...
After conducting an exhaustive job-search campaign, you finally received an offer –congratulations! There are many factors to consider when examining this new offer. Evaluating a job offer is very subjective, but people often focus on the salary and disregard other key areas. Here is a five-step process that I developed to help my clients fully evaluate new job opportunities and determine if this is the right fit for them.
Evaluate the Position: The actual position is the most important part of the offer. In this new economy, where jobs tend to have a shorter tenure, each position becomes the stepping-stone to the next position. So if you have a career path in mind, each job positions you for the next step in your career. Is this...
Unlike most fields, modern financial risk management can be traced back to a specific time and place, and a relatively small group of people. Some quants in New York City, between 1987 and 1993, codified knowledge from a variety of fields, thrashed out disagreements and created the basic foundations of risk management which remain valid to this day. Of course, much of the intellectual heavy lifting had been done before 1987, but it was not organized systematically nor known to any one person. And there has been much progress since 1993, but no shift in fundamental principles.
What’s in a name?
During the years of development, we discussed what to call the field. We wanted to distinguish it from fields like portfolio management and...
The author of this article works as an associate for an investment bank in NYC trading exotic derivatives. The author holds a master degree.
5:30 am: Alarm goes off. Told myself last night that I'd go to the gym downstairs in my building for a quick workout before work today. Not happening. Back to sleep. I really do go through this process most days. I probably should stop even bothering to set my alarm for this time.
6:00 am: OK now I'm up. Shower, get dressed, get on subway to work. You'd be surprised how few people are out on the street at this time.
6:40 am: I'm at the desk now in lower Manhattan. I log in to my PC, start up all my applications. I have a pricer, risk management system, Reuters, Bloomberg, chats, broker screens...
5:45am - Alarm goes off, time to get up and get ready
6:30am - Head to bus stop
6:40am - Bus to train station.
6:55am - Arrive at train station, purchase coffee.
7:15am - Find seat on train
7:30 (ish) - Train heads off to London - usually read a book or the Economist or similar.
8:30ish - Arrive at London Bridge train station
8:35 - Head to tube stop to grab the tube over to Canary Wharf
9ish - Arrive at desk at bank (sometimes with Krispy Kream in hand)
9-noon - Work on software and meetings with stakeholders
12ish - Head down to canteen and grab some lunch - if it's a Friday go for the Pie, mushy eas and chips.
12:15 - Eat at desk whilst working.
12:30 - Work on code, meetings etc.
Fridays: 5 - head home.
Very good day - 5:30/6 head...
In this article, one of Quantnet members describes a typical day in his former life as an Interest Rates Developer at a Major Investment Bank (MIB), FO and MO spreadsheets support. He is now employed at another MIB.
4:50 AM - I do not want to wake up, can someone please break this evil clock alarm!!!
5:15 AM - I’m on the train and going to job
6:30 AM - Finally I’m here and first thing I check if all publishing systems are up. Looks like couple of indicator on my alarm monitor that I wrote in C# are red so I’m going in and investigate, looks like couple of Reuters’ spreadsheets which publishing data closed overnight and did not reopen, so I help them and we are good here. Time to drinkk some coffee (1st cup)
7:00 AM - First call from...
In his new book, Scott Patterson argues that quantitative risk managers nearly destroyed Wall Street in a series of disasters going back to 1987. But that is far from the whole truth.
The quant revolution in academic finance began about 60 years ago, and it came to Wall Street in force about 30 years ago. It has been blamed for every disaster since, which is not entirely unfair.
Most of the innovations during this period have been quant-linked, and in many cases were pure quant. That means quant models affected all Wall Street events, including disasters. More positively, quants have increased the size, speed and power of finance, which is an enormous net benefit, but it does make disasters more significant for the economy as a whole...
Remember in Hamlet when King Claudius discovers Laertes has been buying naked CDS protection on Danish government bonds? Polonius, the royal treasurer, fears it will increase funding costs and bring on a fiscal crisis. The king laughs off the threat with the famous line, “There's such divinity doth hedge a king, that treason can but peep to what it would, acts little of his will.”
Few modern CEOs or heads of state have demonstrated the same wisdom and courage. Instead we are likely to hear less poetic line, “It’s like buying fire insurance on your neighbor’s house!”
To suffer the slings and arrows
Actually it’s not like buying insurance. The distinction between hedging (including buying covered CDS protection) and insurance is...