Calc-based probability is sufficient for the undergrad equity level positions I am aware of. Measure-theoretic probability is usually considered more of a grad level course.
Doing well on IMO/IOI is a recognized marker for high ability in math/CS that helps in getting an interview, but they are not the only recognized markers. Other recognized markers are getting to USAMO or higher or taking “well-known” classes such as Harvard’s Math 55, or the corresponding equivalent at several other colleges, or a number of grad courses like measure-theoretic probability mentioned above. Not really familiar with the impact of iPhO or others.
Remember, all you are trying to do is get the first interview, and once you get to that point, it’s really a matter of how you do.
What’s the difference between a “prop shop” and a hedge fund? Is the former a special type of the latter, and if so, what makes the different from others?
Is there any value for a recent graduate in obtaining the Certificate in Quantitative Finance (CQF)?
It states “ Founded by Dr. Paul Wilmott, the part-time, online CQF program is designed to help established and aspiring professionals advance their quant finance careers. The master’s-level program teaches the theory and practical implementation of the latest quant finance and machine learning techniques used in industry today. ”
Piggybacking on the above question, are there any certifications that could make sense for someone with a bachelor’s degree who wants to move in quant finance or trading?
Here are some other certifications, are any of these worthwhile?
The fundamental difference is that a prop shop trades or invests using its own money, whereas a hedge fund invests using other people’s money.
Prop shops are almost always trading firms. All the profits are theirs, and all the losses are theirs as well. They buy and hold stocks for a short period of time with the anticipation of selling it within a short time for a profit. They are “market makers” in the sense that they are readily willing buyers for any security they cover if the price is right. The play an important purpose in providing liquidity in the markets because they hold inventory ready for sale to longer term investors, such as hedge funds but also traditional long-only investors.
In contrast, hedge funds are investing other people’s money with the goal of increasing it, and they take a cut of these profits.
It’s possible it has value, but I personally never knew anyone with that certificate.
None of those certifications are useful for initial hires into the most competitive quant firms, which look for evidence of raw talent and don’t care if the applicant has zero financial knowledge when hired.
However, as I said earlier, there are plenty of successful quant firms that are less competitive (a good example is Acadian Asset Management) , and that want to hire people with an understanding of the financial markets. Of the programs listed, I would give the most credence to the MFE programs listed (NYU, Columbia, and Berkeley).
Another good alternative that’s superior to anything else listed besides the MFE is the CFA program. There is a well known Boston quant shop that used to (and might still) display the CFA diplomas of their key employees in the reception area.
@hebegebe Can you educate us a bit more about some of the lesser known hedge funds and prop trading firms. Companies such as Optiver, SIG, JS, Citadel etc are well known and there are plenty of info about these.
what about more obscure or less well known ones like Dipsea Capital, Walleye Quantic, Headlands, QRT etc? Are they deliberately secretive despite being successful or is there a long tail of mediocre firms in quant?
I don’t know any of the companies you mentioned. But doesn’t mean small quant companies can’t have a successful strategy. For example, there are strategies that work for a smaller pool of money but don’t work well for 10x that amount.
Things to learn about these companies include background of the founders, track record over the last three years, Sharpe ratio, number of clients, number of different strategies being run, and the amount of capital invested in each. And importantly, what will allow them to continue succeeding when the well known companies have a lot of talent, and a huge budget for data and computing equipment.
Interesting. I know of these companies mainly based off of recruiting outreach and frankly I was a bit shocked at some of the info I heard second hand. For instance, apparently one of the key guys from Headlands often comes to lecture at Berkeley and apparently they outpay JS and HRT for their new grad hires. (~500k).
Similarly, Walleye has basically zero web presence outside their website but apparently manages $11B.
I guess some of the things you are talking about are proprietary in nature (Sharpe, # clients etc.) so would you say variables like new grad comp and AUM are correlated to firm quality.
New grad comp is certainly correlated with firm quality, but not a guarantee. A firm might have a few good years and overpay relative to its long term prospects, or it might be on its way to becoming the next Citadel.
Re AUM, that’s comparable only across hedge funds. You cannot a compare a hedge fund with $11B of client money to a prop trader with much less capital. The prop trader can be just as profitable because it has a much higher volume of trades where it can make money.
Another thing to seriously consider is work environment. One of the reasons Jane Street is so coveted is because the work environment is quite relaxed, with most employees working less than 50 hours per week, and attrition being very low. Conversely, Citadel is much more sink or swim.
Forgive me if this has been addressed before. What about physics majors/phds in these roles? S24 is thinking now of getting a phd in physics before deciding on a career path. Is this a reasonable step for someone interested I. Quant?
@hebegebe, could you shed more light on software engineering roles at these types of firms?
Do CS graduates interested in SWE roles need a strong math background? What other qualities (aside from being a CS major) are valued?
Do aspiring software engineers also need to come from the same elite schools targeted by these firms for trading and quant roles, or do graduates from other strong CS programs (even if the university as a whole is not considered top-tier) also have a shot?
@hebegebe would know more but my perception after being around a kid purusing Quant Dev roles - there are 2 types of SWE roles: Quant Dev vs. Core Engineering. Essentially the difference between developers helping with alpha generation vs. developers scaffolding and managing the trading infrastructure and related tooling.
Both these roles require FAANG-like CS skills - data structures, OS etc. with a healthy dose of ML and low latency data engineering. From what I understand the recruiting is mainly Leetcode Medium-to-Hard level problem solving and system design rather than probability games or trader math that QR/QT roles might demand.
Regardless, SWE and QD roles all look for top notch CS pedigree whether its through school ranking, prior internships, or through competitive programming pedigree.
The big four for quant software engineering hires are: Berkeley, CMU, MIT and Stanford.
And while top students from those colleges certainly have a big advantage, students from other strong CS programs can and regularly do get hired into quant software engineering roles.
For example, here are some colleges that do well with quant software engineering, but not nearly as well with quant trading roles: Berkeley, CMU, Cornell, Georgia Tech, Michigan, UIUC, UT-Austin (particuarly Turing).
SWE roles generally don’t require exceptional math skills. For example, Jane Street used to (and might still) explicitly say that they don’t test software engineering candidates on probability.
Instead, it is the quant traders and researchers that need the exceptional math skills, and once they find a winning strategy, they explain this to the software engineers, who are then responsible for using their exceptional CS skills to implement that strategy in a way that’s fast and reliable.
So while the software engineers don’t need the hardcore math skills, they need enough math knowledge to understand the algorithms given to them and implement them in a reliable way.
PhD graduates are primarily looking at research roles, not quant trading or software engineering roles where 22-year olds are readily hired. It’s important to realize that this is a small hiring segment in an already small industry. If I were to guess, I would say that no more than 200 PhDs are hired each year.
The area I know best is stock trading, and for that the most common PhD degrees are either in pure math or statistics. But students with PhD degrees in other heavy math fields like electrical engineering or physics are also considered. To increase your chances, I would recommend research related to financial markets.
He may have more luck in quant firms that work on derivatives (like stock options). Many of the original Wall Street quants were physicists, because the Black-Scholes equation that is the fundamental building block of stock options is very similar to the Heat Equation that every physicist learns. I don’t know much about this part of the quant finance market, but it’s something for your child to investigate.
This is a pretty informative podcast by Max Dama who founded the Traders Club at Berkeley and heads up one of the best quantitative trading firms around.
Lots of good insights for students and parents interested in the field.