DelhiDesk The use of artificial intelligence (AI) and machine learning in hedge funds has been a slow but steady process, with quant funds experimenting with these techniques since the early 2000s. However, the recent retail trading boom and pandemic-related market volatility have caused some quant strategies to underperform. This highlights the need for humans to adapt and react to new technology, and that not all technologies make markets more efficient. It also shows that robots take time to find their place, and that machine-learning funds have not yet amassed vast assets due to the need for education and understanding of the risks involved. Overall, the use of automation in the stock market is more like a tug-of-war between humans and machines, with neither side fully winning.
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👉 Hedge funds have been using AI and machine learning for decades, well before the recent hype.
👉 Quantitative investors use data and algorithms to pick stocks and place short-term bets on asset values.
👉 Automated algorithms now manage a majority of investors’ assets in passive index funds.
👉 The stock market has become more efficient than ever before due to automation.
👉 Retail trading has spiked due to commission-free trading and pandemic boredom.
👉 Many quantitative strategies underperformed the markets and human hedge funds in 2020 and early 2021.
👉 Humans can react unexpectedly to new technology, like falling trade execution costs.
👉 Not all technologies make markets more efficient, social media can lead to weird price action.
👉 Robots take time to find their place and amass assets, as they are a hard sell.
👉 Automation is more like a tug-of-war between humans and machines, with machines winning but humans not letting go yet.
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