Artificial intelligence has made its footing in the stock market, driven by algorithmic trading at its very core. More and more investors and hedge funds now turn to the might of AI-driven algorithms for quicker, more incisive decisions on trading. These algorithms can process huge quantities of information, identify patterns, and execute trades in microseconds, something no human can do. The question that piqued my interest was whether these algorithmic models can outperform even today’s best traders.
In many of these cases, the answer to the question would be an easy yes, as seen in the case of the hedge fund Renaissance Technologies, popularly known for its Medallion Fund, which makes investment decisions based on AI-based quantitative models. The fund has been able to maintain better performance than its human counterparts, with an average annual return of approximately 66% over the last two decades (S., 2024). Another example is Bridgewater Associates, which uses AI to critically analyze global economic data to assist in trading (Jensen & Moriarty, 2024).
The real edge that AI has over humans is the fact that it can analyze both structured and unstructured data on the stock market, including in the news, social media, and financial reports, enabling more accurate predictions for future market movements (Gnibus, 2024). Furthermore, these insight-driven trades are executed much faster than any human trader. This saves a great amount of time, and as they say in the world of trading, time is money. With great speed and precision, AI-driven trading has now taken Wall Street by storm, with 60% of all trades being executed by algorithms (Schlaepfer, 2024).
However, AI isn’t foolproof per se. The most critical issue it faces is the dependence on historical data. Although this may sound normal, the over-reliance on past information does not help in the case of unprecedented events like the 2008 financial crisis or the COVID-19 pandemic, leading to poor decisions in such scenarios. Programs trained on old data can often fail to adapt to the abrupt market swings and eventually cause large losses. Additionally, AI-controlled strategies contribute to volatility, as seen in the case of a “flash crash”, when automated high-frequency trades create huge, unexpected market fluctuations, and can lead to major setbacks for many players (Needhi, 2024).
I personally feel that although AI has tremendous potential, it still needs to be used with and not instead of human traders. Rather than replacing human counterparts, AI should be used to enhance stock market decisions ultimately made by humans. What are your thoughts on this – will AI become the norm when making trading decisions and eventually dominate the stock market?
References
Gnibus, A. (2024, April 15). Why Unstructured Data is Having a Moment, Thanks to AI. Medium. https://medium.com/@alexgnibus/why-unstructured-data-is-having-a-moment-thanks-to-ai-ad546e5a7158
Jensen, G., & Moriarty, J. (2024, May 30). Are we on the brink of an AI investment arms race? Bridgewater. https://www.bridgewater.com/research-and-insights/are-we-on-the-brink-of-an-ai-investment-arms-race
Needhi, J. (2024, July 9). AI’s Role in the 2024 Stock Market Flash Crash: A Case Study. Medium. https://medium.com/@jeyadev_needhi/ais-role-in-the-2024-stock-market-flash-crash-a-case-study-55d70289ad50
S, R. (2024, September 27). How Jim Simons built the best AI that solved the market. Medium. https://suenrankine.medium.com/how-jim-simons-built-the-best-ai-that-solved-the-market-f3e23319db29
Schlaepfer, D. (2024, July 2). Humans vs. AI in The Stock Market: The Worst Trade Ever Made? Forbes. https://www.forbes.com/sites/forbesbooksauthors/2024/06/18/humans-vs-ai-in-the-stock-market-the-worst-trade-ever-made/
Thank you for your post, I found it very fascinating! As someone who’s interested in finance and technology, I also noticed the trend. As you mentioned hedge funds are increasingly using AI for trading because of its efficiency and speed in processing data.
I found an article in Bloomberg which highlights that ING Bank has made use of AI for pricing currencies, and the results showed that it outperformed human traders. Its head of global electronic explained that the AI model has taken over the full-time tasks of monitoring the market, adjusting spreads, and managing risk, effectively freeing up an entire role within the team (Atkins, 2024).
This is a clear example of the trend you mentioned. In my opinion the increased usage of AI for trading purposes will still need oversight, but the role of human traders will more supervisory rather than a hands-on trading task.
Atkins, A. (2024, September 25). AI model is better at pricing currencies than humans, ING says. Bloomberg.com. https://www.bloomberg.com/news/articles/2024-09-25/ai-model-is-better-at-pricing-currencies-than-humans-ing-says