Finding 4562Emerging EvidenceValidation V0
This paper uniquely applies advanced LLMs (ChatGPT, Claude, Gemini) to sentiment analysis of Japanese 10-K reports, an underexplored dataset. Its findingthat LLM-derived sentiment predicts future stock returns while traditional methods do notchallenges the efficient market hypothesis, offering novel insights and significant implications for both academic research and investment practice.
78%Confidence
1Evidence objects
v1Version
DraftStatus
Evidence trail
Supporting78% linkage confidence
This paper uniquely applies advanced LLMs (ChatGPT, Claude, Gemini) to sentiment analysis of Japanese 10-K reports, an underexplored dataset. Its findingthat LLM-derived sentiment predicts future stock returns while traditional methods do notchallenges the efficient market hypothesis, offering novel insights and significant implications for both academic research and investment practice.
key_findings bullet 4 · key_findings
Inspect source: From words to returns: sentiment analysis of Japanese 10-K reports using advanced large language models →This Finding was extracted from the configured corpus. It is versioned, traceable, and may evolve through editorial review or new corpus evidence.