Finding 6120Emerging EvidenceValidation V0
This paper uniquely extends 'nonstandard errors' (NSE) analysis from human researchers to autonomous AI agents, using 150 Claude Code agents on NYSE TAQ SPY data. Its novel three-stage protocol reveals AI analytical diversity and convergence via imitation, offering fresh insights into AI-driven empirical finance, replication credibility, and automated policy evaluation.
78%Confidence
1Evidence objects
v1Version
DraftStatus
Evidence trail
Supporting78% linkage confidence
This paper uniquely extends 'nonstandard errors' (NSE) analysis from human researchers to autonomous AI agents, using 150 Claude Code agents on NYSE TAQ SPY data. Its novel three-stage protocol reveals AI analytical diversity and convergence via imitation, offering fresh insights into AI-driven empirical finance, replication credibility, and automated policy evaluation.
key_findings bullet 4 · key_findings
Inspect source: Nonstandard Errors in AI Agents →This Finding was extracted from the configured corpus. It is versioned, traceable, and may evolve through editorial review or new corpus evidence.