Artificial intelligence-powered tools, such as ChatGPT, have the potential to revolutionize the way humans work by increasing efficiency, effectiveness and speed. This is true not only in financial markets but also in sectors like healthcare, manufacturing and many other aspects of our daily lives.
As someone who has been researching financial markets and algorithmic trading for 14 years, I can attest to AI’s many benefits. However, the growing use of these technologies in financial markets also presents potential risks. A look at Wall Street’s past efforts to speed up trading by embracing computers and AI offers important lessons on the implications of using them for decision-making.
In the early 1980s, advancements in technology and financial innovations such as derivatives led institutional investors to begin using computer programs to execute trades based on predefined rules and algorithms. This allowed them to complete large trades quickly and efficiently.
Initially, these algorithms were relatively simple and primarily used for index arbitrage, which involves profiting from discrepancies between the price of a stock index, like the S&P 500, and the prices of the stocks it comprises.
As technology progressed and more data became available, program trading became increasingly sophisticated. Algorithms were able to analyze complex market data and execute trades based on a wide range of factors. The number of program traders grew on the largely unregulated trading freeways, where over a trillion dollars’ worth of assets change hands every day, causing market volatility to increase dramatically.