About Hallucination Yield

The concept of "hallucination yield" emerged from a fascinating observation: ChatGPT and other large language models show consistent biases when discussing investments and stocks. As noted by @goodalexander:

"I'm a recently converted fan of 'hallucination yield' - the idea that ChatGPT arbitrarily likes certain stocks or thinks they're bigger than they are. Hard to backtest because of training cutoffs but... yeah, it works."

Large language models are trained on vast amounts of internet data, which creates systematic biases in how they perceive and recommend investments. These biases aren't random - they reflect patterns in the training data that can be measured and analyzed.

Our platform systematically queries multiple LLM services to:

• Identify stocks that LLMs consistently favor or overweight
• Measure the "premium" LLMs assign to specific companies
• Track how these biases change over time
• Provide data-driven insights into LLM market sentiment

As AI becomes increasingly influential in financial markets - through robo-advisors, research tools, and decision-making systems - understanding these built-in biases becomes crucial. The "hallucination yield" represents a new form of market premium that traditional analysis might miss.

We take a rigorous, data-driven approach to understanding LLM market biases:

Nanodolphin Labs LLC is dedicated to researching the intersection of artificial intelligence and financial markets. Our team combines expertise in machine learning, financial analysis, and data science to uncover new insights in the evolving landscape of AI-driven finance.

Founded in 2025, we focus on creating tools and research that help investors and researchers understand how AI systems influence market dynamics. Our work is purely research-focused and educational.