This rule appears to hold for artificial intelligence and machine learning, which were first employed by hedge funds decades ago, well before the recent hype. First came the “quants”, or quantitative investors, who use data and algorithms to pick stocks and place short-term bets on which assets will rise and fall. Two Sigma, a quant fund in New York, has been experimenting with these techniques since its founding in 2001.
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. This hypothesis allows individual stocks to be tested against historical data to assess if their value will continue to rise. By contrast, with machine learning, investors could “start with the data and look for a hypothesis”.
Yet automation’s great march forward has not continued unabated—humans have fought back. Towards the end of 2019 all the major retail brokers, including Charles Schwab,
Lol
I had to fill an excel column with the numbers 1-100 and calculate the sum. Than an AI took my job!
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