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A new approach for estimating divisional betas is developed in this study. The approach is based on a sound theoretical foundation; utilizes all available information, yet still has parsimonious data requirements; can be implemented with simple statistical tools; and provides unambiguously interpretable results. The proposed methodology is applied to a large sample of stocks. The results indicate that the proposed methodology can more accurately estimate divisional betas than other approaches previously advocated in the finance literature.
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Stored only when both papers are in the corpus — 37 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.