From the Wall Street Journal, January 31:
Even the smartest algorithm has to operate within its limitations on risk and capital.
The evolution of artificial intelligence raises profound questions for financial markets. Will human portfolio managers become obsolete as AI algorithms become smarter? Will markets become perfectly efficient and reflect the ultimate equilibrium, in which prices mirror economic reality without human distortion?
Economists’ longstanding debate about market efficiency sheds light on these questions. In the 1970s, Eugene Fama argued in his efficient-market hypothesis that asset prices reflect all available information, and it is therefore impossible for an investor to outperform the markets consistently. This thesis shaped modern finance, only to be countered a decade later by Robert Shiller, who argued that stock prices are far more volatile than would be expected if investors were making decisions based on strictly rational thinking. He proposed instead that human irrationality drives market bubbles, crashes and overall inefficiency. Despite their opposing views, Messrs. Fama and Shiller were jointly awarded the Nobel Prize in 2013.
Our perspective aligns with Mr. Shiller’s: Market participants’ irrational behavior can cause market inefficiency. Yet market inefficiency isn’t solely the product of market participants’ acting irrational at times; different circumstances can compel even rational investors toward actions that collectively generate inefficiencies. Each player in the financial market is constrained by unique economic circumstances, and these economics drive even the smartest players to act in a way that isn’t necessarily efficient for the underlying asset or the market as a whole.
Example: A natural-gas producer hedging a production output may have a significantly lower optimal trading price than a utility safeguarding its end users’ contracts. Unless these two participants—which often bring significant volumes of the commodity to the market—trade at exactly the same time, their market actions can drive asset prices far from their fundamental value.
Hedge funds and other speculative entities may intervene, seeking to correct and benefit from the inefficiencies. Their actions, however, are also bound by economic constraints, such as limited capital or risk parameters. When they hit these limits, the speculative entities may be forced to unwind their positions, amplifying the price swing they had been working to dampen. As a result, while trying to solve one mispricing, they may introduce a set of new mispricings, perpetuating and even amplifying the cycle of price inefficiencies. We saw this phenomenon with
and other meme stocks—which gained popularity through social media—when risk limits drove short sellers to buy back the stocks they were shorting, driving those equities ever further from their fundamental value.These inefficiencies aren’t only products of extreme market conditions but are recurring phenomena, even in stable economic periods. Nearly a century ago economist Nicholas Kaldor documented wild price swings for corn and hog markets. Today, speculative traders, including quantitative algorithms, frequently exit their positions while solving for a market price inefficiency. In fact, these market actions are often crucial parameters in their strategies to ensure a consistent volatility of their returns. Their actions can be individually logical and profitable over the long term but collectively disrupt the market’s march toward an efficient equilibrium...
....MUCH MORE
He is a BSD in AI. One of his groups, the Institute for Human-Centered AI, publishes the Stanford University "AI Index Report," to which we last linked in November 2023.
I don't know her or Tiara other than the WSJ blurb linked from their website.