Investment

Next gen Jim Simons-like investors

Two Sigma is seen by many as the most successful challenger to RenTech. Led by David Siegel and John Overdeck, it manages $58 billion. As well as a successful quant process, it is an innovative firm, recently starting to use data science to time its buying and selling real estate.

WorldQuant has performed by producing a string of performance-seeking algorithms to chase performance. Founder Igor Tulchinsky said in his autobiography The Unrules “Automation vastly expands what traders can do, allowing a leap in scale, scope, complexity and productivity.” He also sees the importance of humans working closely with machines. 

Marcos Lopez de Prado recently became global head of quant research at the Abu Dhabi Investment Authority.

He is also chief investment officer of True Positive Technologies advising clients with assets totalling $1 trillion which were built out of strategies worth $13 billion he first built for Guggenheim Partners. 

Lopez de Prado believes we are only at the start of a data journey, where data sets will upgrade our investment understanding through machine learning. He believes there is scope for others to compete with RenTech, but does not expect the scene to become overcrowded as yet.

He has pioneered the use of machine learning in backtesting, bet sizing and portfolio construction. He recently co-researched ways to determine the optimal moment to pull out of their trades using a mathematical concept used in nuclear cooling. 

Singapore’s GIC sovereign wealth fund owns Kepler FI which wants to find and scale strategies “with the potential to disrupt institutional asset management.” It has developed an ideas network called AlphaShare.

Bjarn Graven Larsen, chairman of Danish family office Kirk Kapital, has developed Qblue, a risk manager driven by data and a systematic approach.

A new firm, Project One Capital, has developed alpha-learning algorithms and an enthusiastic marketing spiel: “If  you missed out on Medallion, don’t miss Project One,” says CEO Andrew Sobko.

There are an enormous range of quant services on offer from investment banks, prime brokers and the fintech sector.

Data supplier ClearMacro has scored an early win by the decision of the British Columbia Investment Management, a $108 billion state-funded investor, to back them. 

Level E Research, based in Edinburgh, is an interesting newcomer which has closed a seed funding round of £1.2m from investment professionals. The business, founded by Sonia Schulenburg, combines machine learning, data science and behavioural economics enabling clients to develop, test and implement smart AI investment strategies. It is keen to pitch to family offices.

All that said, it can be challenging to find an AI strategy that works. Many would even challenge the use of an AI tag for strategies dominated by data sets and machine learning.

Back in 2019, for example, the CFA Institute analysed an index comprising fourteen so called AI hedge funds. The index outperformed but did not include 36 funds that had shut.

Some machine learning systems are capable of reacting to a pattern, even where evidence is slight. The strategies that use them face the risk of “overfitting” where machines suggest outcomes using misleading signals.

Or they can fail to take account of changes in market liquidity which can render previous signals redundant. Programming based on past performance can lead to chaos, as we saw across the quant world during the credit crisis of 2008.

RenTech has weathered many crises, but it has disappointed its institutional followers with funds which have not always performed as well as Medallion – maybe because they take a longer view of opportunities. Quant often struggles with long-term forecasts, as variables multiply. 

Backers of quant products will also know the costs involved updating systems, which suggests the likes of RenCap will remain ahead of the opposition by updating its existing systems. 

In due course, the quant world will also need to tangle with quantum computing, which could be capable of ferreting out every investment signal for every market on the planet. The consequences could be enormous. 

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