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"If I am an undergraduate student, I have determined that I am interested in quantitative finance and have accumulated a lot of project experience. Do I need to get a PhD in mathematics or computer science in order to get into quantitative finance?" 
Once upon a time, I had the same problem and hesitated to pursue a Ph.D. in statistics. But then, after reading more and more of my predecessors' experience, I decided to go straight for a master's degree in financial engineering. What influenced my decision was the following article. The original text is in Chinese, posted on Zhihu and other platforms, the author nicknamed "flower street lying scientist ". I will translate the original into English and share it with you, hope it can help you.
"
Structure of the Article:
What kind of person does a quant job require? What qualities are valuable for quant-related work?
Why can both Ph.D. graduates and top MFE graduates work as quants?
If aiming for a quant job, why is pursuing a Ph.D. not recommended?
If one cannot get into a top MFE program, should they resort to a Ph.D. as an entry tool by trading time for space?
Core Argument of the Article:
Pursuing a Ph.D. to become a Quant is putting the cart before the horse.
There is a statistical correlation between STEM Ph.D.s and top Quants, but no causation.
In this article, we define "Quant" narrowly as Quant Research roles, specifically on the buy-side. We exclude other quant positions like risk quants or quant developers, as the emphasis on a Ph.D. is less for those roles. Buy-side Quant Research generally has the highest demand for "independent research" capabilities, a key skill developed in Ph.D. programs. For other quant roles, a Ph.D. holds less significance. Hence, this article only discusses the preference for MFE or Ph.D. in buy-side Quant Research.
A researcher must thoroughly understand the data and exhaustively explore different variables and combinations (or come up with a genius idea derived from inspiration). When facing failure, they must persist even when the results seem meaningless in the early stages. This type of work is closely aligned with the nature of Ph.D. research, which explains why top quant shops are inclined to hire Ph.D.s. Moreover, Ph.D. candidates typically have very strong mathematical fundamentals, honed over years of research, which is also beneficial for Quant Research roles.
In summary, Quants need the following qualities:
In fact, a fair comparison would be between an MFE graduate with 3 years of buy-side Quant Research experience and a fresh Ph.D. graduate with no work experience. Who would be more competitive?
I believe the former has the advantage, as they have 3-4 years of direct "finance data" research experience, while the latter has 3-4 years of unrelated research experience (though indirectly proving their suitability for Quant roles). This comparison makes the difference clear.
Another important consideration is that Ph.D. students are often inherently more suited to Quant roles due to their nature, personality, and talent, rather than because Ph.D. training made them suitable. In other words, it's their ability to endure solitude, their research prowess, and their mathematical talent that allows them to obtain a Ph.D. Such people could easily enter the Quant field through an MFE program as well.
Key takeaway:
More importantly, consider the following: if you graduate from an MFE program and work for two years, only to realize that you are not suited for Quant, you can still switch careers within finance at the age of 27. However, if a Ph.D. graduate finds out after two years that they are not suited for Quant, switching careers at 31 would come with significant opportunity costs. Moreover, if you can't get into a top MFE program, I highly doubt a decent Ph.D. program would admit you. If you attend a low-ranked Ph.D. program, top funds won’t want you. At best, you might end up at places like Fidelity or BlackRock (which are large asset management firms but not top Quant funds). The pay at these firms isn't exceptionally high, and given the time investment and your talent limitations, I’d suggest that such candidates may be better off pursuing a different career (e.g., recruiting or intermediary roles).
Key takeaway:
A STEM Ph.D. program certifies your fit for Quant roles, but this certification comes at a significant time cost. On the other hand, those who are truly suited for Quant roles don’t need this certification and can easily enter the field through a top MFE program. For those who can't get into a top MFE program, I would advise against aiming for top buy-side Quant roles. Instead, focus on finding a solid mid-level quant role at an investment bank.
If you’ve already enrolled in a Ph.D. program and suddenly realize that you are both highly interested in and suited for Quant roles, you can still make a mid-career switch and be very successful. In fact, the core characteristics that make someone suitable for Quant work—intelligence, patience, independent research ability—are not something that a Ph.D. or MFE program can cultivate. These are traits that you inherently possess. There's no need to force yourself into a career that doesn't suit your nature. There are plenty of other career paths out there that may be a better fit for your strengths and preferences.
"
Once upon a time, I had the same problem and hesitated to pursue a Ph.D. in statistics. But then, after reading more and more of my predecessors' experience, I decided to go straight for a master's degree in financial engineering. What influenced my decision was the following article. The original text is in Chinese, posted on Zhihu and other platforms, the author nicknamed "flower street lying scientist ". I will translate the original into English and share it with you, hope it can help you.
"
Structure of the Article:
What kind of person does a quant job require? What qualities are valuable for quant-related work?
Why can both Ph.D. graduates and top MFE graduates work as quants?
If aiming for a quant job, why is pursuing a Ph.D. not recommended?
If one cannot get into a top MFE program, should they resort to a Ph.D. as an entry tool by trading time for space?
Core Argument of the Article:
Pursuing a Ph.D. to become a Quant is putting the cart before the horse.
There is a statistical correlation between STEM Ph.D.s and top Quants, but no causation.
In this article, we define "Quant" narrowly as Quant Research roles, specifically on the buy-side. We exclude other quant positions like risk quants or quant developers, as the emphasis on a Ph.D. is less for those roles. Buy-side Quant Research generally has the highest demand for "independent research" capabilities, a key skill developed in Ph.D. programs. For other quant roles, a Ph.D. holds less significance. Hence, this article only discusses the preference for MFE or Ph.D. in buy-side Quant Research.
1. What kind of person is suited for a Quant role? What qualities are valuable for Quant jobs?
Buy-side Quant Research usually requires someone who can explore a problem deeply and iteratively to find a simple (human-comprehensible), logical (makes economic sense), and self-explanatory mathematical model to explain fluctuations. This is inherently contradictory: simple models often lack explanatory power due to too few factors, and simple models are also likely to have been fully exploited (if you can think of it, so can others). Thus, the work involves constant back-and-forth, requiring patience and tolerance for solitude.A researcher must thoroughly understand the data and exhaustively explore different variables and combinations (or come up with a genius idea derived from inspiration). When facing failure, they must persist even when the results seem meaningless in the early stages. This type of work is closely aligned with the nature of Ph.D. research, which explains why top quant shops are inclined to hire Ph.D.s. Moreover, Ph.D. candidates typically have very strong mathematical fundamentals, honed over years of research, which is also beneficial for Quant Research roles.
In summary, Quants need the following qualities:
- (a) Intelligence and a strong aptitude for mathematics
- (b) The ability to endure solitude
- (c) Skill in conducting deep, independent research
- (d) Strong mathematical foundations
2. Why can both Ph.D. graduates and top MFE graduates pursue Quant jobs?
- Intelligence: While top-tier Ph.D. students may have a slightly higher mathematical aptitude, I tend to believe that top-tier MFE students are no less intelligent than Ph.D. students from schools ranked around 50th.
- Endurance for solitude: Students who graduate from STEM Ph.D. programs have clearly endured years of solitude. If they were more career-driven, they could have entered FAANG companies earlier and enjoyed a better quality of life in the U.S. So in terms of this criterion, Ph.D. students are superior to MFE graduates.
- Independent research skills: Ph.D.s are clearly better at this than MFE students. Many MFE programs emphasize group work, and students spend significant time on job hunting. The focus is not on cultivating independent research abilities.
- Mathematical fundamentals: Ph.D.s again have an edge here. Ph.D. candidates spend at least 4-5 years honing their mathematical foundations, while MFE students have only 1-2 years, which naturally results in a gap in their foundational skills.
3. If your goal is a Quant job, why is a Ph.D. not recommended?
We’ve overlooked a crucial variable in our calculations: time. MFE graduates are at least 3-4 years younger than Ph.D. graduates.In fact, a fair comparison would be between an MFE graduate with 3 years of buy-side Quant Research experience and a fresh Ph.D. graduate with no work experience. Who would be more competitive?
I believe the former has the advantage, as they have 3-4 years of direct "finance data" research experience, while the latter has 3-4 years of unrelated research experience (though indirectly proving their suitability for Quant roles). This comparison makes the difference clear.
Another important consideration is that Ph.D. students are often inherently more suited to Quant roles due to their nature, personality, and talent, rather than because Ph.D. training made them suitable. In other words, it's their ability to endure solitude, their research prowess, and their mathematical talent that allows them to obtain a Ph.D. Such people could easily enter the Quant field through an MFE program as well.
Key takeaway:
- Those who are well-suited for Quant roles don't need a Ph.D. to prove their fit.
- Three years of work experience is more valuable than a Ph.D. in mathematics education. Therefore, the MFE route is a more efficient path.
4. If you can't get into a top MFE program, should you opt for a Ph.D. as a stepping stone, trading time for opportunity?
Again, time is the most important variable. MFE graduates are 3 years younger, and those 3 years of experience are enough to surpass a fresh Ph.D. graduate.More importantly, consider the following: if you graduate from an MFE program and work for two years, only to realize that you are not suited for Quant, you can still switch careers within finance at the age of 27. However, if a Ph.D. graduate finds out after two years that they are not suited for Quant, switching careers at 31 would come with significant opportunity costs. Moreover, if you can't get into a top MFE program, I highly doubt a decent Ph.D. program would admit you. If you attend a low-ranked Ph.D. program, top funds won’t want you. At best, you might end up at places like Fidelity or BlackRock (which are large asset management firms but not top Quant funds). The pay at these firms isn't exceptionally high, and given the time investment and your talent limitations, I’d suggest that such candidates may be better off pursuing a different career (e.g., recruiting or intermediary roles).
Key takeaway:
A STEM Ph.D. program certifies your fit for Quant roles, but this certification comes at a significant time cost. On the other hand, those who are truly suited for Quant roles don’t need this certification and can easily enter the field through a top MFE program. For those who can't get into a top MFE program, I would advise against aiming for top buy-side Quant roles. Instead, focus on finding a solid mid-level quant role at an investment bank.
If you’ve already enrolled in a Ph.D. program and suddenly realize that you are both highly interested in and suited for Quant roles, you can still make a mid-career switch and be very successful. In fact, the core characteristics that make someone suitable for Quant work—intelligence, patience, independent research ability—are not something that a Ph.D. or MFE program can cultivate. These are traits that you inherently possess. There's no need to force yourself into a career that doesn't suit your nature. There are plenty of other career paths out there that may be a better fit for your strengths and preferences.
"
