Renaissance Technologies is the most successful hedge fund in history, averaging nearly 40% annual net returns over the last 30 years. The book The Man Who Solved the Market discusses the fund and its founder Jim Simons in depth.

This is part 2 on a series discussing the book. Part 1 discussed the Renaissance’s data pipeline. This part will discuss Renaissance’s unusual practice of hiring almost exclusively from academia.

Academia

Simons was a successful mathematician prior to starting Renaissance at the age of 40. He joined The Institute for Defense Analyses (IDA) as a code breaker at the age of 26 and eventually went on to lead the math department of Stony Brook University at the age of 30. Simons made his greatest academic contribution to mathematics in his mid 30s when he published a paper coining the Chern-Simons theory.

At the age of 40, Simons abruptly left academia to start a hedge fund, shocking many of his colleagues. Simons had dabbled in trading before, viewing market prices as a puzzle to be solved.

He first focused on commodities, currencies and bond futures. At first he tried a traditional approach of reading news stories, looking at historical trends and trying to predict what will happen next. This approach yielded poor results and Simons quickly lost faith:

“Sometimes I look at this and feel I’m just some guy who doesn’t really know what he’s doing,” Simons said.

But it was short lasting:

Until then, Simons and Baum had relied on crude trading models, as well as their own instincts, an approach that had left Simons in crisis. He sat down with Howard Morgan, a technology expert he’d hired to invest in stocks, and shared a new goal: building a sophisticated trading system fully dependent on preset algorithms that might even be automated.

“I don’t want to have to worry about the market every minute. I want models that will make money while I sleep,” Simons said. “A pure system without humans interfering.”

Simons had no connections to investing or Wall Street and in the late 1970s hedge funds didn’t exist in their modern form. This worked in Simons favor since he had to chart his own path. Simons tapped his existing network of colleagues from his time at building out Stony Brook’s math department and work at IDA. He knew how to get academics aboard:

“You’re at Stony Brook?” he asked Penavic, who nodded. “What have you done?”

Unsure who the guy with all the questions was, Penavic, who stood six-foot-six, began describing his undergraduate work in applied mathematics. Simons was unimpressed.

“That’s trivial stuff,” he sniffed. It was the most devastating put-down a mathematician could deliver.

Undeterred, Penavic told Simons about another paper he’d written focused on an unsolved algebraic problem.

“That problem is not trivial,” Penavic insisted.

“That’s still trivial,” Simons said with a wave of his hand, cigarette fumes wafting past Penavic’s face.

As the young recruit burned, Simons started grinning, as if he had been playing a practical joke on Penavic.

“I like you, though,” Simons said.

A bit later, Penavic was hired”

Interviews usually consisted of candidates presenting their work and discussing an academic problem presented to them. Renaissance looked to hire the smartest people in the hard sciences.

They needed to be supersmart, of course, with identifiable accomplishments, such as academic papers or awards, ideally in fields lending themselves to the work Renaissance was doing. Patterson steered clear of Wall Street types. He didn’t have anything against them, per se; he just was convinced he could find more impressive talent elsewhere.

“We can teach you about money,” Patterson explains. “We can’t teach you about smart.”

Simons also knew what motivated academics. Although he was very secretive to outsiders, Simons fostered an open culture within the firm

Researchers couldn’t discuss their work with those outside the organization. Internally, however, the division was structured to breed an unusual degree of openness and collegiality. Most of the twenty-five or so employees — all mathematicians and engineers — were given the same title: technical staff member. The team routinely shared credit and met for champagne toasts after discovering solutions to particularly thorny problems. Most days, researchers wandered into one another’s offices to offer assistance or lend an ear. When staffers met each day for afternoon tea, they discussed the news, played chess, worked on puzzles, or competed at Go, the complicated Chinese board game.”

Simons located his fund in a sleepy town on the north shore of Long Island, unheard of among finance firms. He also granted profit sharing fairly early on and many staff member became wealthy, making millions in both salary and personal investments in the fund.

Simons began sharing equity, handing a 10 percent stake in the firm to Laufer and, later, giving sizable slices to Brown, Mercer, and Mark Silber, who now was the firm’s chief financial officer, and others, steps that reduced Simons’s ownership to just over 50 percent. Other top-performing employees could buy shares, which represented equity in the firm. Staffers also could invest in Medallion, perhaps the biggest perk of them all.

Simons was embracing immense risk. Hotshot researchers and others were liable to become frustrated working in a flat organization that spread its largesse around and made it harder to stand out.

Another benefit of hiring academics and working outside of finance was that employees were less likely to leave to rivals.

Full access to the system’s code enabled staffers to walk out the door, join a rival, and tap Renaissance’s secrets. But, since so many of them were PhDs from the world of academia with limited familiarity with Wall Street, Simons believed the chance of defection was relatively small. Unusually onerous lifetime nondisclosure agreements, as well as noncompete contracts, also reduced the danger.

Even as the fund became profitable and many employees became incredibly wealthy, the culture proved somewhat sticky:

Other than a few old-school traders who completed transactions, many at Renaissance didn’t seem to prioritize wealth. When celebrated computer scientist Peter Weinberger interviewed for a job in 1996, he stood in the parking lot, sizing up the researchers he was about to meet. He couldn’t help chuckling.

“It was a lot of old, crappy cars,” he recalls. “Saturns, Corollas, and Camrys.”

That’s not to say academics were immune to petty squabbling.

By 2002, Kononenko — who was thin, clean-shaven, and good-looking, with hair that showed signs of gray at the temples — was pocketing well over $40 million a year, colleagues estimated, about half from his pay and half from investing in Medallion. He used some of his winnings to build an impressive art collection.

Despite their mounting wealth, Kononenko and some of his newer colleagues grew unhappy. They complained that there were too many “deadwood” employees who weren’t pulling their weight and were being paid way too much.

“What do they even contribute?” a newcomer was overheard asking about some of Renaissance’s senior executives.

Despite this, Simons was able to effectively manage and retain the brightest people in academia and help foster a culture of excellence.

Why Hasn’t It Been Replicated?

Finance firms are certainly leaning a lot more on technical staff in recent years, but the culture of most banks is that there is a separation between technology and strategy. Technology is a cost while real value generation is driven by MBA types.

Banks have a long and storied history and culture is hard to change. Many are entrenched players and face little outside risk to disruption. Increased regulations and the 2008 crisis all but enshrined them as wards of the state, immune to any shakeup that could append their model. New regulations also limited what they are able to do in regards to proprietary trading. The attention on large banks also makes them conservative as to their business model.

Buy-side firms like hedge funds are different. They have more freedom to experiment and try new models but most of those firms are founded and funded by people from within the large bank culture. Investors have strong biases. Asking investors to drive out to northern Long Island to meet some socially awkward academics requires spectacular returns. Managing and motivating academics is also difficult. The people with the resources to start and fund investment vehicles have no experience in this and they are not willing to empower someone who does.

Simons is a once in a generational force that combined academic excellence with strong managerial experience. He could rally a team of geniuses and build out a money printing machine.

But of course other quant funds exist, and their roster is similarly filled with brilliant people. But these funds are chasing a different set of incentives. This will be the topic of my next post.