March 12, 2023 Fintech AI/ML, Data-driven, Automation, Generative AI, FinTech and Alternative Finance, Fintech Services, Fundraising, Investing, Trading, Innovation and Resources, Stories No comments
Human vs Machine’s Tug-of-War: Stockmarket Automation Lessons
The Economist | Mar 9, 2023
Image: Unsplash/Tech Daily
When it comes to the stockmarket, at least, automation has not been the winner-takes-all event that many fear elsewhere. It is more like a tug-of-war between humans and machines. And though the machines are winning, humans have not let go just yet.
- Cheap index funds, with stocks picked by algorithms, had already swelled in size, with assets under management eclipsing those of traditional active funds in 2019. Exchange-traded funds offered cheap exposure to basic strategies, such as picking growth stocks, with little need for human involvement.
- By the end of 2019, automated algorithms took both sides of trades; more often than not high-frequency traders faced off against quant investors, who had automated their investment processes; algorithms managed a majority of investors’ assets in passive index funds; and all of the biggest, most successful hedge funds used quantitative methods, at least to some degree.
See: OSC Report: How Gamification Influences Retail Investors
- The traditional types were throwing in the towel. Philippe Jabre, a star investor, blamed computerised models that had “imperceptibly replaced” traditional actors when he closed his fund in 2018. As a result of all this automation, the stockmarket was more efficient than ever before. Execution was lightning fast and cost next to nothing. Individuals could invest savings for a fraction of a penny on the dollar.
- Machine learning held the promise of still greater fruits. The way one investor described it was that quantitative investing started with a hypothesis: that of momentum, or the idea that stocks which have risen faster than the rest of the index would continue to do so. In other words, the algorithms could decide both what to pick and why to pick it.
- Humans fought back: Towards the end of 2019 all the major retail brokers, including Charles Schwab,e*tradeandtd
Ameritrade, slashed commissions to zero in the face of competition from a new entrant, Robinhood. - A few months later, spurred by pandemic boredom and stimulus cheques, retail trading began to spike. It reached a peak in the frenzied early months of 2021 when day traders, co-ordinating on social media, piled into unloved stocks, causing their prices to spiral higher
- When markets reversed in 2022, many of these trends flipped. Retail’s share of trading fell back as losses piled up. The quants came back with a vengeance.aqr’s longest-running fund returned a whopping 44%, even as markets shed 20%.
See: How AI Has Revolutionized The Canadian Banking Industry
- So what lessons?
- The first is that humans can react in unexpected ways to new technology. The falling cost of trade execution seemed to empower investing machines—until costs went to zero, at which point it fuelled a retail renaissance. Even if retail’s share of trading is not at its peak, it remains elevated compared with before 2019. Retail trades now make up a third of trading volumes in stocks (excluding marketmakers).The second is that not all technologies make markets more efficient. “Getting information and getting it quickly does not mean processing it well,” reckons Mr Asness. “I tend to think things like social media make the market less, not more, efficient.
- The third is that robots take time to find their place. Machine-learning funds have been around for a while and appear to outperform human competitors, at least a little. But they have not amassed vast assets, in part because they are a hard sell.
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