AI Executive Claims Human Intelligence Lacks Uniqueness in Outperforming AI in Stock Trading

This content does not constitute investment advice. The author does not hold any positions in the stocks discussed herein.

Insights on AI in Stock Trading from Reflexivity’s CEO

Jan Szilagyi, CEO and co-founder of the software company Reflexivity, recently provided compelling insights on the integration of artificial intelligence (AI) in stock trading during an interview on CNBC’s Squawk Box. He noted that many leading hedge funds are adopting AI software as a supplementary tool alongside their traditional methods, revealing that AI has already demonstrated a significant ability to predict stock market trends throughout this year.

Reflexivity’s innovative technology utilizes advanced analytical engines combined with large language model (LLM) interfaces, enabling enhanced decision-making capabilities for investors. Szilagyi emphasized that, given adequate computing resources and robust training, AI has the potential to surpass human intelligence in stock trading activities.

The Vision for Autonomous Investment Analysis

During the interview, Szilagyi articulated that Reflexivity aspires to develop an “autonomous investment analyst.”The company is currently offering technologies that aggregate data from multiple sources into one cohesive platform, streamlining the decision-making process for investors.

Users engage with the system by posing inquiries, allowing the engine to autonomously retrieve data and conduct analyses. Szilagyi highlighted that this technology can shorten the time required for specific operations from two hours to just two minutes.

Understanding Market Patterns through AI

Szilagyi elaborated on how Reflexivity’s AI algorithms are designed to identify historical parallels, assisting traders in predicting future price movements. By analyzing data from 12 to 15 past events related to the selected securities, the system can provide insights relevant to the current economic environment, helping investors pinpoint stocks that may offer superior returns.

His clientele primarily consists of top-tier hedge funds, which utilize this AI system as an “intelligent overlay”on their diverse data sources, enhancing their analytical capabilities.

Reflexivity Terminal Interface — Reflexivity’s Terminal interface exemplifies how simple queries can yield data-driven answers. Image: Reflexivity

Examining AI’s Prediction Accuracy in the Market

Further into the discussion, Szilagyi analyzed how AI performed with stock market trends in 2024. He pointed out that AI accurately identified the market peak in July and the subsequent false rally. Moreover, it also correctly pinpointed the market’s subsequent bottom.

Nonetheless, he noted that the AI system “turned bullish a bit too early”before a recent Federal Reserve meeting, which subsequently adjusted its interest rate predictions for 2025, moving from four cuts down to two. Szilagyi contextualized this by explaining that his model’s outputs are essentially “probabilistic assessments,”indicating a 70% likelihood for certain forecasts—with a remaining 30% chance of deviation.

The Future of AI in Stock Trading

When posed with the question of AI’s capacity to completely replace human traders, Szilagyi provocatively expressed that he sees no inherent advantage in human intelligence for trading. He advocated that with substantial computational power and continual advancements in AI capabilities, it is not unreasonable to anticipate that AI systems could eventually outperform human traders.

He projected a timeline of “five to ten years”for when AI could take on a more dominant role in trading, though he cautioned that this does not imply total replacement. Certain sectors, particularly private markets, may continue to present challenges due to limited data availability for effective training.

In summary, the adoption of AI in stock trading marks an evolving landscape, where technology continues to reshape the methodologies employed by investors and institutions alike.

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