Investment

More investors, including family offices, getting closer to achieving Medallion Fund-like returns

Advances in technology have led to hopes that a new generation of investors can emulate Renaissance Technologies (RenTech) whose Medallion Fund has produced net returns of roughly 40% a year since 1988. 

Sovereign wealth funds in Singapore, Abu Dhabi and British Columbia are backing expertise in AI, along with large family offices. New hedge funds and quant systems are continually springing up. 

These days, Medallion is run like a co-operative on steroids for the benefit of its employees

Securing access to an avalanche of data and machine learning to generate returns from algorithms has become a top priority for investors, according to JP Morgan. 

Sarah Heffron, co-head of electronic client solutions and program trading says: “The trader of the future isn’t a person who’s pressing buttons to trade. It’s somebody who understands more of a macro view through the use of data and technology.”

This all-embracing approach has been pioneered since 1988 by RenTech, a $130 billion manager, led by Jim Simons.

Its Medallion Fund saw average gross returns of 66% – or 39.1% after fees – between 1988 and 2018, according to The Man Who Solved The Market by Gregory Zuckerman. During the pandemic of 2020, its returns were 76%, according to Institutional Investor.

Medallion tends to perform well during a crisis because it has neutral exposure to the market, plus volatility to turn to its advantage. RenTech also does well because it uses short-term signals which adapt to changing circumstances.

Legendary traders like Louis Bacon, John Tudor Jones and Bruce Kovner – old favourites for many family offices – have shot out the lights in certain years. But their record for consistency has been less appealing partly because their systems were less advanced than RenTech. 

If anything, RenTech’s returns have improved over the years, as machine learning has become better at its job, unlike human traders who can get bored or run out of puff.

Traditional investors have performed even less well. Berkshire Hathaway’s Warren Buffett managed to achieve 20.5% a year between 1965 and 2018 but this return was largely thanks to his early years.

These days, Medallion is run like a co-operative on steroids for the benefit of its employees. Jim Simons, originally a mathematician and former codebreaker, has put his share of the profits at the disposal of a family office, Euclidean Capital, a big investor in biotech, as well as his family foundation.

The big question for would-be imitators is how easily, and whether, RenTech’s performance can be emulated. After all, it took Simons years of trial and error to develop his approach, driven by the hiring of uniquely talented hires. Simon’s personality, and experience, facilitated their retention. And he readily admits: “We’ve had a lot of luck.”

According to Zuckerman, he knew the importance of data from the outset, buying and scrounging access to a wealth of price movements over decades – including tick data to cover each trading day. With a struggle, his managed futures team found ways to make sense of price movements for sectors like currencies and commodities to provide signals on future performance.

Fundamental analysis does not figure in this process. Simons once said he didn’t know why planets orbited the sun but that didn’t mean he couldn’t predict their movements. 

It took RenTech longer to crack the equities market but it did through a statistical arbitrage strategy developed by Robert Mercer – latterly a donor to Donald Trump’s election campaign – and Peter Brown. They both previously worked on IBM’s language translation initiative whose complex workings informed their investment theory.

Their results encouraged RenTech to trust the use of machine learning to take advantage of fleeting arbitrage opportunities without human input although Simons struggled with this approach.

Their systems saw patterns of price behaviour that took advantage of the relative performance of prices which pounced on trading errors produced by the behaviour flaws of traditional investors using less data. RenTech’s technology takes an exhaustive approach to analysing relative trades, but the system does not pick stocks. Instead, it can take 4,000 long positions and 4,000 shorts at any one time.

But RenTech does use baskets of swaps offered by the banks to hide its trading tracks and apply leverage. It hires from various disciplines, including astrophysics, to help its algorithms seek out patterns. Medallion was only rewarded with profits from just over 50% of its positions, but that was enough. That said, the more the merrier.

RenTech has also avoided the classic quant trap of getting caught out in a crisis by using data that is backwards-looking, rather than adaptive. 

RenTech’s near-contemporaries include DE Shaw, whose quant funds have a strong record for avoiding losses. Its founder David Shaw has moved into molecular physics, where he has been involved in groundbreaking research.

Another quant peer is Ken Griffin’s Citadel, which has run a successful hedge fund business for years and now supplies technology to services that provide market access to retail traders using platforms like Robinhood. 

Former RenTech executive Robert Frey runs FQS Capital, which uses cutting-edge techniques to invest in hedge fund strategies. 

More traditional systematic funds run by the likes of Man Group and AQR have increasingly turned to machine learning to improve their returns.

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