Scholar4AI

← Research ideas

SeedPublished 2026-10-23

Firm peers from contrastive embeddings

Contrastive learning is one of the largest topics in the AI journals, yet only 6 of 749 recent contrastive-learning papers carry a finance or firm keyword. Finance research still defines peer firms mostly by industry codes. Would firm embeddings learned contrastively from filings, returns and supply chains give better peers for valuation, benchmarking and pay?

aifinancemeasurement

What prompted this

Since October 2025, "contrastive learning" appears on 548 papers (538 in AI journals), and 749 papers carry some contrastive-learning keyword; only 6 of them carry a finance, stock, firm, company or industry-classification keyword. "Peer firms" appears on 13 papers and "industry classification" on 4.

Questions

  • Do peers from contrastive embeddings explain a firm's returns, valuation multiples and earnings better than SIC or GICS peers, or text-based peers?
  • Do they pick up a firm's move into new businesses sooner than industry codes do?
  • Would they change results that rely on peers, such as relative performance evaluation in CEO pay?

Data that could help

Business descriptions in 10-K filings, stock returns (CRSP), supply-chain links and industry codes (Compustat).

Next step

Train a contrastive model in which a firm's filing text and its return co-movement in the next year form positive pairs, and compare the resulting peers with GICS peers.

Related research activity

The keywords this note follows, in the tracked finance, accounting, economics, management, operations research and AI journals as of 2026-10-26
KeywordPapers, last 30 daysRankPapers per month, Oct 23 – Oct 26*Papers, last 36 months
contrastive learning27#131,297
peer firms1#288125
industry classification0–12

Markdown version of this note: /ideas/firm-peers-from-contrastive-embeddings.md

← Fiscal expansion and bank credit in the euro area · Finfluencers and the retail trade →

Cite this page

Scholar4AI. (2026). Firm peers from contrastive embeddings. Journal Research Rankings. Retrieved October 23, 2026, from https://scholar4ai.com/ideas/firm-peers-from-contrastive-embeddings

@misc{scholar4ai-ideas-firm-peers-from-contrastive-embeddings,
  author = {{Scholar4AI}},
  title = {Firm peers from contrastive embeddings},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/ideas/firm-peers-from-contrastive-embeddings}},
  urldate = {2026-10-23},
  note = {Journal Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

Free to reuse for non-commercial purposes with attribution (CC BY-NC 4.0).