Trading in quantitative hedge funds (for earning to give)
Summary
For someone with strong quantitative skills, we think this represents one of the best career opportunities available. The pay is exceptionally good enabling earning to give, you can develop technical skills valued in academia or technology, and the work is satisfying. We’ve seen numerous cases of mathematicians taking this path and being highly satisfied. The main caveat is that the industry faces many risks – these activities could become unprofitable due to regulation or competition – so it’s important to make sure you also build strong career capital.
Pros
- Exceptionally high pay
- Engaging work
- Build skills in statistics, programming and modelling, as well as general skills like team work and decision making under pressure.
Cons
- Only possible to enter with very strong mathematical skills.
- Industry faces numerous risks.
Key facts on fit
Strong mathematical skillsWhat is this career path?
Hedge funds trade money on the markets on behalf of wealthy investors, in exchange for fees and a share of the profits. Quantitative hedge funds use strategies based on algorithms to make money. Jobs in this path involve using statistics, mathematical modelling and programming to devise, implement and manage these strategies.
Immediate impact
Direct impact
We think the social value of quantitative trading is neutral or weakly positive, with some chance of it being harmful. For more, see the articles on Marginal Revolution and Noahpinion and, within the academic literature, this review by Greenwood and Sharfstein, followed by this discussion by Cochrane.
Earnings potential
This is likely to be one of the highest earning paths available. Compensation starts at $100,000-$500,000 and grows rapidly in the first 5-10 years. Based on current salary levels and ignoring the chance of firm failure, we estimate the median lifetime earnings for a new entrant are $250,000-$750,000 per year, with a mean over $1 million per year. This ignores prospective salary growth or contraction. Overall, we recommend using an expectation value somewhat below these figures.
This path can also offer the chance to reinvest your earnings at above market rates, further boosting lifetime income.
Advocacy potential
This path is not particularly good for building connections and doesn’t give you a public platform, although you will have wealthy, intelligent colleagues, so there may be some opportunities to promote effective philanthropy or financial reform.
Building your long-run potential
Career capital
You’ll have opportunities to develop strong technical knowledge and skills, such as machine learning, programming and statistics. You’ll also develop most of the major transferable skills.
On the other hand, this career is not particularly useful for developing a broad network, and the firms may offer less prestige than alternatives in academia or technology. The only common exit option is into academia.
How difficult is it to enter?
If you’re capable of finishing in the top third of your class in mathematics at an Ivy League university, then you have a shot at entering this path. Slightly weaker mathematical ability can be compensated for with strong programming ability and rationality (for instance, skill at poker). You’ll generally need qualifications in mathematics, physics, computer science and so on to be considered, though not always. Many jobs require a PhD, though some can be entered directly from undergraduate. Applying to internships is one of the best ways to test yourself out.
For someone with the necessary mathematical skills, our impression is that this option offers unusually good pay and job satisfaction relative to its difficulty.
Job satisfaction
Many people find the work interesting and engaging. The culture often seems more supportive than finance in general (though it depends on the firm). Your colleagues will be very smart, but the pace is faster than academia. You’re expected to work 50-60 hours per week – considerably better than investment banking or tech startups.
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