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Renaissance Technologies co-founder reveals secrets to quant and VC career success

Ceiling fresco in Palazzo Barberini, Rome, Italy

When you hear the name Howard Morgan, it should make you think of Jim Simons, founder of quant hedge fund giant Renaissance Technologies. In the 1980s, Morgan – who has a PhD in operations research from Cornell – moved out of the upper echelons of academia to co-found the buy-side firm. He ended up breaking off on his own and cementing his legacy as a legendary venture capitalist and angel investor. He admits that alternative investment career paths – and the buy side in general – today are much different from when he got his start.

The author of many books, Morgan became a tenured professor at the University of Pennsylvania, where he taught decision sciences, as well as computer science and how to apply it to business, at the Wharton School and the Moore School of Electrical Engineering.

“I was consulting for industry and helping them understand how to use computers, and I did a little bit of investing of my own,” Morgan says. “I did work with Jim Simons, and he and I started Renaissance Technologies in 1982.”

Simons, who has a PhD in mathematics from the University of California, Berkeley, and a net worth of approximately $18bn, headed up the quantitative hedge fund side of the firm, which he still does to this day alongside co-CEO Robert Mercer, while Morgan served as president and led the VC business when that industry was still nascent.

“Quant trading was in its infancy, and the techniques being developed at Renaissance were on the bleeding edge of everything that was happening in the ’80s,” Morgan says. “At the time, the firm was about half venture and half trading – we thought we could make an interesting fund using technology to create trading models.

“Quant trading was doing well, but at that time the VC operations did far better than the trading, whereas, by the end of the ’80s, the VC unit achieved a 25% compound annual return, while the trading operations were in the 30s,” he says. “Trading in public instruments, you could shut down and three days later distribute it, whereas in the VC business it could take five, six or seven years [to achieve a liquidity event] – it wasn’t until 1996 when our last VC instrument went public.”

In 1989, as Renaissance’s hedge funds ballooned in size, Morgan left the firm to start consulting and venture-capital firm Arca Group. In 2004, he co-founded a seed-stage VC firm, First Round Capital, with Josh Kopelman, co-founder of Infonautics and the founder and president of Half.com, which he sold to eBay in 2000 for $374m.

“Quantitative trading became so dominant and did so well that Renaissance didn’t want to continue venture investing, so I went off on my own,” Morgan says. “In the late ’90s, it still took at least $200m to start a successful company, but by the time Josh and I started First Round Capital, you could start firms much more cheaply, be there at the beginning – the first investment round – and then scale up with that.

“Now with the cloud, you can start companies for tens of thousands of dollars and scale up from there, and there is lots of capital available to entrepreneurs,” he says. “Our focus was on companies that used the internet to reach their consumers or do business by using technology, lean and mean startups able to scale quickly using the internet and modern tools without creating massive infrastructure.”

First Round Capital seeded Bazaarvoice, OnDeck, StumbleUpon (which eBay bought in 2007 for $75m), Warby Parker, Blue Apron, HotelTonight, Mint and Uber. It has since turned its attention to startups focused on AI, machine learning, robotics and the rise of blockchain and related cryptocurrencies.

Morgan is still a special adviser at First Round Capital and recently joined the board of advisers at TIGER 21 (short for The Investment Group for Enhanced Results in the 21st Century), a peer-to-peer learning network for high-net-worth investors, investment managers, entrepreneurs and senior executives.

Quant hedge fund and VC career paths

In the ’70s and early ’80s when Morgan was in academia, the VC space was much smaller. Now there are exponentially more VC firms, but that doesn’t mean it’s easy to break in and establish yourself in the sector.

“My advice [for aspiring VC professionals] is first work in a startup so you understand what they’re all about, then do small investments on your own, at least five of them, and use that track record to talk to venture firms,” Morgan says.

Quantitative trading is undergoing a revolution thanks to AI, deep learning and data science, which is opening up new career paths on the sell side and the buy side, both at established firms and growing upstarts.

“If you’re going into quant trading, you have to really understand AI, math and statistics, because hedge funds prioritize having publicly available legal data that other people don’t see as useful,” Morgan says. “Learn AI and data science tools and have a deep understanding of stats.

“In the quant world in 2017, the tools are so much cheaper and more available, so a lot more people are trying them, but if they’re all using the same data sets, there’s no edge,” he says. “If you look at Renaissance, they don’t want people to have experience with trading; they want people who have math, stats, physics, biochemistry or computer science backgrounds and can apply their expertise to predicting price movements.

The bottom line: A deep understanding of science and math is the most important factor for most hiring managers looking for quantitative traders and researchers, data scientists and AI experts.

“The big bulge-bracket firms do want you to understand the trading side of things, because you’ll obviously run into the reality of making trades in the market, but to master the deeper algorithmic trading parts of the business, get a PhD and get very into the math, science and computer science aspects of what you’re doing,” Morgan says.

First Round Capital’s 2013 holiday video, featuring Morgan himself swinging on a wrecking ball:

Photo credit: pixone/GettyImages

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