Weekly Business Insights from Top Ten Business Magazines | Week 287 | Shaping Section

Extractive summaries of and key takeaways from the articles curated from TOP TEN BUSINESS MAGAZINES to promote informed business decision-making | Week 287 | March 10-16, 2023

Shaping Section : Ideas and forces shaping economies and industries

Lessons from finance’s experience with artificial intelligence

The Economist | March 9, 2023

Listen to the Extractive Summary of the Article

“Quants”, or quantitative investors were the first ones who used data and algorithms to pick stocks and place short-term bets on which assets will rise and fall.   The rest follow.  The hedge funds’ experience demonstrates AI’s ability to revolutionize business—but also shows that it takes time to do so, and that progress can be interrupted.  

AI and machine-learning funds seemed like the final step in the march of the robots. 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. The flagship fund of Renaissance Technologies, the first ever quant outfit, established in 1982, earned average annual returns of 66% for decades.  By the end of 2019, automated algorithms took both sides of trades.  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.

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, e*trade and td Ameritrade, slashed commissions to zero in the face of competition from a new entrant, Robinhood.  At the same time, many quantitative strategies seemed to stall.  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. 

This zigzag, and robots’ growing role, holds lessons for other industries. The first is that humans can react in unexpected ways to new technology.  The second is that not all technologies make markets more efficient.  The third is that robots take time to find their place.

There was a time when everyone thought the quants had figured it out. That is not the perception today. 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.

3 key takeaways from the article

1. “Quants”, or quantitative investors were the first ones who used data and algorithms to pick stocks and place short-term bets on which assets will rise and fall.   As a result of all this automation, the stockmarket was more efficient than ever before.
2. Yet automation’s great march forward has not continued unabated—humans have fought back. Towards the end of 2019 all the major retail brokers slashed commissions to zero in the face of competition from a new entrant, Robinhood.  At the same time, many quantitative strategies seemed to stall.
3. This zigzag, and robots’ growing role, holds lessons for other industries. The first is that humans can react in unexpected ways to new technology.  The second is that not all technologies make markets more efficient.  The third is that robots take time to find their place.

Full Article

(Copyright)

Topics:  Technology, Artificial Intelligence, Stock Exchange