Finding 3893Emerging EvidenceValidation V0
This dissertation uniquely applies advanced NLP (word embeddings, word2vec) to measure managerial attention, leverages a natural experiment to separate value from values in sustainable investing, and analyzes regulatory claritys impact on digital finance. Its originality, novel methodologies, and large-scale data make it compelling and significant for quantitative finance research.
82%Confidence
1Evidence objects
v1Version
DraftStatus
Evidence trail
Supporting82% linkage confidence
This dissertation uniquely applies advanced NLP (word embeddings, word2vec) to measure managerial attention, leverages a natural experiment to separate value from values in sustainable investing, and analyzes regulatory claritys impact on digital finance. Its originality, novel methodologies, and large-scale data make it compelling and significant for quantitative finance research.
key_findings bullet 4 · key_findings
Inspect source: Essays on (Frictions in) Corporate Finance →This Finding was extracted from the configured corpus. It is versioned, traceable, and may evolve through editorial review or new corpus evidence.