Steven Edwards This paper tests whether aggregating stock selections from a large, philosophically diverse ensemble of LLM personas can produce genuine investment signals beyond passive benchmark exposure. The author built 100 distinct investor pe rsonas spanning value, momentum, growth, ESG, quantitative, and contrarian philosophies, each independently selecting fifty US-listed equities. The picks were backtested across…
An autonomous AI research agent was tasked with replicating nine published U.S. equity anomalies on clean, survivorship-free data. On a faithful build, none survive out-of-sample — and the lone apparent survivor turned out to be the agent’s own construction error. The real lesson is that an AI researcher is only as trustworthy as the guardrails…
Using tick-level data from Polymarket and Kalshi, this study finds the classic favorite-longshot bias is largely a ‘Yes Bias,’ that the most capitalized traders systematically underperform smaller ones, and that the most vocal participants add no informational edge. It offers a reproducible method for denoising prediction-market probabilities.
Valued at around $10 trillion, the U.S. corporate bond market is slow, expensive, and inefficient. This Article argues that the bond market – premised on contract – rests on a flawed regulatory design that delivers neither investor protection nor market quality.