Abstract
This paper introduces a Peer Index (PI) constructed from economically motivated peer networks that summarizes (i) the strength of a firm’s peers and (ii) the firm’s position within its peer group. PI predicts stock returns and earnings surprises over short and long horizons. Machine-learning models based solely on firm-level characteristics do not subsume PI’s predictive power, supporting the interpretation that it captures genuine cross-stock information. Lag-augmented local projections show that positive PI innovations are followed by higher next-month returns that gradually decay without reversal, consistent with slow diffusion of peer information into prices.
| Original language | English |
|---|---|
| Article number | 104274 |
| Journal | Journal of Financial Economics |
| Volume | 180 |
| DOIs | |
| State | Published - Jun 2026 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
Keywords
- Asset pricing
- Cross-stock predictability
- Economic links
- G11
- G12
- G14
- Information aggregation
- Peer effect
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