The big problem with DIY quants
This year, quants are the new rock stars of finance. Hedge funds, asset managers and investment banks are all rolling out the red carpet for those who can write algorithms that will ensure they get ahead of the competition as Wall Street restructures itself around a brave new world of artificial intelligence, quantum computing and huge reams of structured third-party data to make investment decisions.
As a talent crisis looms, there's also a new generation of firms - such as Quantopian, Numerai, Quantiacs - convinced that there's really not a shortage of quants, they'd just rather create algos at home in their pajamas than within the confines of an investment bank or hedge fund. These funds use the carrot of Darwinian competition with the chance of a monetary prize at the end or, in the case of Numerai, its own currency.
Quantopian hired Jonathan Larkin as its chief investment officer in June last year to lead a 'community' of data scientists, mathematicians and quants, shortly before it announced that hedge fund grandee and Point72 Asset Management founder, Steve Cohen, was investing $250m and that it had plans to manage external capital and launch its own hedge fund based around its best freelance members. Larkin has now departed, with reports suggesting that it was down to disappointing performance within Quantopian's $50m hedge fund, which launched this summer.
There's a bigger issue here. Maybe, the idea of a 'crowdsourced' hedge fund open to any DIY quant willing to work for comparative peanuts isn't a fundamental threat to the highly-paid professionals after all.
"These types of platforms can often be more about quantity over quality," says Alexander Lipton, a PhD who has held senior quant roles at Bank of America Merrill Lynch, Citadel and Credit Suisse. "These days, anyone can take an online course and call themselves a data scientist. Hiring quants for a large financial institution is a rigorous and complicated process - and rightly so."
Lipton was head co-head of the global quantitative group at Bank of America Merrill Lynch, overseeing a team of 200 quants across New York, London, Tokyo, Hong Kong and Sydney and was heavily involved with recruitment. "It was a complicated process. Usually, we required a very strong technical background, preferably a PhD from a top school and then we'd take them through a gruelling interview process to ensure they were up to the job. You have to draw a distinction between the general public who claim to be quants versus the people with the relevant skills and qualifications."
The interview process at investment banks has come under criticism from quants themselves. Gruelling nine-hour modelling tests and up to 10 rounds of interviews are reportedly the norm. Assuming you make it through this, if someone at the top has any doubts, the hire is not signed off. Jamie Walton, the former head of FX quants at Morgan Stanley, told us previously that it received 700 quant applications every year, and hired 10-20 of them. Any new recruit need 100% approval rates from those involved in the process.
Naturally, those running these companies believe in the rigour of their own selection process. Quantopian founder John Fawcett told the FT that "we have conviction in our investment process and expect our refinements will lead to improved results".
Larkin told us previously that the 15 people Quantopian selected from 120,000 members to manage capital underwent a selection process to rival any hedge fund or investment bank. Quantopian vets the algorithms, and makes sure the code can run successfully on its own for six months. Then it goes into an automated screening process and, finally, is monitored by the firm’s own quant team. Anyone who makes it through this is then subjected to a background test and then an interview with the team.
The successful quants were not amateurs, he said, but ranged from quants studying computer science at Cornell, to senior data scientists working for internet companies, to mechanical engineers. “From our vantage point, we see a lot of people with the types of skills that would be welcomed in a lot of industries, particularly finance, but that don’t necessarily want to be tied down to one sector,” said Larkin. “To some extent, it’s reflective of the evolution of work – people want to move around.”
Lipton has since quit large financial institutions and now describes himself as an entrepreneur. He is involved with numerous projects - he's just signed up as a senior adviser to blockchain start-up Zilliqa, as well as OTC derivatives settlement tech firm Clearmatics. He's an adjunct professor at New York Stern University, a technology fellow at MIT and honorary professor of mathematics at Imperial College London.
While he believes that quants are entering a new golden age with the opportunity to work on exciting projects around blockchain, artificial intelligence and data science, financial services is no longer the natural home for the top quants, he says.
"When I started in the 1990s, any quant who was a little entrepreneurial went into an investment bank. It was the ideal place to be - interesting work, at the forefront of financial engineering," he says. "Now, finance is more sedate and there are a lot more opportunities available elsewhere."
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