Artificial Intelligence & Its Investment Implications

Artificial Intelligence & Its Investment Implications

If you were to poll strangers on what comes to mind when they hear the term artificial intelligence or AI, I suspect the most likely answer would be ChatGPT. The generative chat program launched in 2022 seems to have drawn the most mainstream attention to AI applications since Arnold Schwarzenegger promised he’d be back or Keanu Reaves took the red pill, revealing The Matrix. But the history of AI tools is far older than ChatGPT, although less dramatic than its depiction in these science fiction films. And from an investment standpoint, artificial intelligence pales in comparison to the informational content of the market’s AI—aggregate intelligence.

AI Not New

ChatGPT is but a recent example of AI. One watershed moment came in 1997 when the machine named Deep Blue became the first computer to secure victory in a match against a chess grandmaster. In the mid-2000s, IBM researchers created the Watson computer to compete with star Jeopardy! contestants, ultimately defeating two of the show’s most decorated past champions. And how many of us routinely dispense orders to, and receive suggestions from, Siri or Alexa?

The common thread among these examples is that each represents a tool that processes and organizes data to identify patterns and summarize information or make suggestions. This type of interaction with AI has grown to permeate our everyday lives. Have you noticed your phone offer an unsolicited ETA for your commute when you get in your car? Does your text app suggest grammar revisions based on the context of your overall message? Congrats—you’re an AI user, even if you’ve never opened a ChatGPT session.

AI & Stock Picking

AI has a similarly long history with investing. Active investors have attempted to get an informational edge on markets by using AI processes to retrieve and process data. For example, tools that gauge sentiment from social media or scrape text from company financial reports predate ChatGPT by many years.

While these efforts may have been aimed at selecting stocks that would outperform markets, it’s not clear AI tools are a recipe for consistently generating abnormally high returns. Material information gleaned from running AI processes is very likely a subset of the vast information set known by the market in aggregate and already reflected in market prices. If new information is obtained, the process of buying or selling based on that information quickly incorporates it into market prices. As more investors employ these tools, any edge from doing so should wane.

Another reason to question AI’s role in helping market timing is limitations with its predictions. AI’s forecasting ability fares well when assessing patterns that are relatively stable. For example, my phone’s navigation app is often successful at “guessing” when I’m commuting to work because I come to the office on the same days each week. Autonomous car navigation programs know to slow down at the sight of a stop sign because these visual cues are universal and evergreen.

AI is far less likely to successfully predict changes within complex systems that are as dynamic as stock and bond markets. AI trying to predict market prices is like self-piloting cars trying to read stop signs with words, shapes, and colors that differ from one day to the next. The continuous emergence of new information material to market prices is antithetical to static patterns fostering predictability.

Aggregate Intelligence

Over time, the best chess players realized computers were a powerful supplement to strategy and pattern recognition. Similarly, the best path forward for investment management is likely an amalgam of humans and technology such as AI.

Sure AI and algorithmic trading can help the execution of trades. But there’s no reason to think that AI should fundamentally influence the way people think about stock prices anytime soon. The market is fantastically complex and aggregates all intelligence as buyers and sellers set market prices each trading day.

Based on nearly a century’s worth of data, the U.S. stock market has returned about 10% a year, which is 7% above inflation.1 That was true before and after computers, before and after the internet, and even before and after the second world war. It makes sense to me that it will continue to be roughly similar after AI.

Unconvinced? Ponder this: if some cool AI actually did predict stock prices better than the market, why would the creators share the information with you? It would be in their interest to keep that edge and solely profit from it.

This article adapted with permission from Dimensional Fund Advisors. 

Kevin Kroskey, CFP®, MBA | September 2023

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