David Magerman, a computer scientist and veteran of quantitative hedge fund management with Renaissance Technologies, discussed his move into venture capital on the AFI podcast.
The interview covered his years with the world’s most successful quantitative hedge fund firm, the future of the industry and outlook for such strategies today, and which of his skills are most effectively deployed in venture.
1. There’s an AI understanding deficit
David Magerman’s extensive experience in fund management and technology gives him a unique perspective in venture capital, especially when it comes to judging which companies in the AI space are worth investing in.
He believes a lot of investors who have put venture money to work in companies using artificial intelligence — a huge boom area in the past decade, and especially the past couple of years — don’t understand it. “They can’t differentiate between a founder talking about AI and one that’s actually doing it,” he says.
In short, he can the tell the “companies that are really deploying AI from the charlatans.”
2. Venture could learn from quant HFs on risk management
Magerman believes venture capital could learn from the hedge fund industry when it comes to risk management. He hasn’t seen a lot of discussion from venture funds he’s been involved with as an LP about portfolio construction from a diversification and risk management perspective — quantitative hedge funds are ahead of the game on this.
“I am used to looking at a portfolio from a multi-factor model with 30 or 40 different factors: macro, industry, customer-focused.” When adding a holding to a portfolio you need to be “cognisant of what aspects of the investment are amplifying your risk, and which are actually reducing your risk by diversifying you.”
There isn’t enough data in venture to do a “statistical modelling, full-blown data optimisation,” he adds. “But when I’m looking at a company I can at least think the way I would have at Renaissance about the different factors the company represents.”
For instance, hiring is a huge issue in early-stage technology. “If we’re investing in a company that’s hiring from the exact same pool as a lot of other companies, that’s a risk factor we have to take into account.”
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3. The most “recession-proof” tech investments are in cyber
Cybersecurity was labelled a bigger risk than market volatility by Nicolai Tangen, the AKO Capital founder now running Norway’s national oil fund.
Magerman concurs and sees cybersecurity as the “safest and most recession-proof industry in technology. People have been under-aware in the last decade of how important cybersecurity is.”
The more breaches that happen the more people will spend on tools and software, as well as human resources who understand cybersecurity, he says. The remote working trend sparked by Covid has heightened its importance.
From cars to ovens and refrigerators, “everything we have is basically like a phone” and connected to the internet. “Those are all risks. You don’t want someone turning your oven on when you are on holiday and burning your house down.”
4. “AI has a history of over-promising and under-delivering”
“Going back to the 1960s, the marketing was ahead of the technology,” he says, and calls AI the mimicking of intelligence — not genuine intelligence.
“Computers don’t think. Computers don’t understand. They don’t communicate in a human sense. They just have algorithms that implement behaviours which try to mimic in small ways different human behaviours.”
Understanding the limitations of AI is fundamental to success in the field. “People that try to create intelligences that can think on their own are always going to fail.”
5. Quant hedge funds have opportunity — and existing players a big advantage
Magerman says the outlook in stat arb, the strategy he worked on at Renaissance, is very positive. “The volatility in the market is wonderful for them. The long flat period of the mid-2010s when the market was creeping up casually was good for investors but not quantitative hedge funds.”
Events like the pandemic and war in Ukraine have created shocks and quant hedge funds often profit from the market recovery to shocks. There is also a lot of opportunity due to the rise of retail trading, which presents short-term opportunities for quantitative strategies focused on different trends and factors like liquidity.
That said, he wouldn’t start a quant hedge fund today. “The biggest advantage an existing quantitative hedge fund has is data.” Historical data is the fuel of a quantitive hedge fund — giving existing players a head-start or moat over newcomers, providing a high barrier to entry.
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