Institutional Investor Attention: Kwan, Liu & Matthies (2026)
What this is. The paper’s core results, datasets, and theory: enough to know what it found without reading all 38 pages. To replicate or extend it, read the full source: the verbatim PDF (machine-accessible) or the original.
Using a proprietary dataset of institutional investors’ Internet news reading (Nov 2017 to Jun 2022; ~482M fund-firm-quarters, 4,075 funds), the paper measures fund attention to macro vs firm-specific news. Funds reallocate attention to macro news when aggregate volatility rises; funds that reallocate more strongly earn higher future returns. Firm-specific attention tracks holdings (“attention habitats”), and attention to a stock predicts that position’s value-add, most so for value-relevant news and for buying hedge funds, whose attention predicts stock returns.
Core results
Section titled “Core results”Magnitudes and significance are as reported; **/*** = 5%/1%. Locators
point into the source PDF.
| # | Result | Locator | Magnitude |
|---|---|---|---|
| R1 | Funds shift attention toward macro news when aggregate volatility is high | Table III, p. 804 | β = 0.25** on VIX²ₜ₋₁; robust to VIX and realized vol; ≈ 5% of sample-SD in macro-attention share per 1-SD VIX² |
| R2 | Funds with higher attention-reallocation sensitivity (β^VIX²) earn higher future returns | Table IV, p. 806 | coef 0.31→0.36 (sig 5–1%); ≈ +0.36%/qtr (~1.4%/yr) per 1-SD; ~2× stronger in top VIX quartile (interaction 0.73**) |
| R3 | High-β^VIX² funds look more efficient | §III.C | 0.78–1.74% less attention-weighted salience (sig 5%); +17% advanced-degree staff; trait persistent (62–66% stay vs 25% random); hedge funds >2× mutual funds’ β^VIX² |
| R4 | Firm-specific attention strongly tracks portfolio holdings (“attention habitats”) | Table V, p. 809 | held read 5–6× more than non-held (t sig 1%); with firm×time FE, 1-SD holdings ≈ 1.02-SD attention; fund×firm FE dominate the variance |
| R5 | Attention to a stock predicts that position’s value-add | Table VI, p. 813 | 1-SD attention ≈ +3.3% SD position value-add; trade-based coef 0.074**; ×trade-size 0.58*** (bigger trades, more value) |
| R6 | Value-add is concentrated in value-relevant news (business/financial newswires) | Table VIII, p. 817 | biz/fin-newswire attention×holdings 0.107** / 0.123***; retail and general news insignificant |
| R7 | Funds attend more to buys than sells; attentive buys outperform | Table IX, p. 819 | residualized attention: buy ≈ 1.6 vs sell ≈ 0.6 vs hold ≈ 0 (buy>sell sig 1%); attentive buys add value, sells mixed/insignificant |
| R8 | Attention by buying hedge funds predicts future stock returns | Tables X–XI, pp. 821–823 | Fama-MacBeth: buying-HF attention 0.51*/0.56*** (MF & other negative/insignificant); ≈ +0.35%/mo (~4%/yr) per 1-SD; HF long-short 0.53%/mo EW (t=2.75), 0.80%/mo VW; FF5 α ≈ 0.45%** EW; no predictability for held/sold |
Overall (paper’s conclusion). Attention is a resource that funds allocate, and the allocation contributes to performance. Funds that reallocate attention to macro news in volatile times, and that attend to value-relevant firm news, do better; the strongest stock-return signal is attention by buying hedge funds.
Datasets used
Section titled “Datasets used”| Dataset | Role in paper | Wiki page |
|---|---|---|
| Proprietary Internet news-reading data (“Data Partner”, anonymized analytics firm), Nov 2017–Jun 2022 | The attention measure itself | Proprietary; not public or redistributable; no page |
| RavenPack 1.0 | News topic / subject / sentiment; stock-ticker mapping | No wiki page yet (commercial dataset) |
| FactSet LionShares | Institutional holdings (13-F), institution classification | No wiki page yet (commercial dataset) |
| CRSP & Compustat | Returns, fundamentals, stock characteristics | WRDS / CRSP / Compustat (licensed) |
| VIX (CBOE) | Aggregate-volatility measure (VIX²) | FRED, free, series VIXCLS |
| SEC Form ADV, Form N-1A | Fund descriptions for classification | SEC EDGAR for N-1A; Form ADV is via SEC IAPD, not EDGAR |
| LinkedIn / Revelio Labs | Fund human capital (advanced-degree share) for R3 | No wiki page yet |
Sample: 481,820,400 fund-firm-quarters; 4,075 distinct funds.
Theory tested
Section titled “Theory tested”No original structural model. The paper is empirical: it tests predictions common to limited- and rational-inattention models: Peng & Xiong (2006), Van Nieuwerburgh & Veldkamp (2009, 2010), Glode (2011), Kacperczyk, Van Nieuwerburgh & Veldkamp (2016); related: Sims (2003), Maćkowiak & Wiederholt. The shared predictions tested: (i) attention shifts to macro news when aggregate uncertainty is high; (ii) attention and holdings are positively linked; (iii) attention to a stock raises its value-add. Identification: panel regressions with fund / fund×time / firm×time fixed effects, Fama-MacBeth, and portfolio sorts (Newey-West).
When to read the full paper
Section titled “When to read the full paper”Use the mirrored PDF if you are: replicating (code in the journal’s Supporting Information); extending the attention measure or the value-add tests; doing a literature review where the Internet Appendix robustness matters; or auditing a specific coefficient. The locators above point you to the exact table. For “what did this paper find,” the table above is sufficient and is the intended default.
Attribution & rights
Section titled “Attribution & rights”Source: peer-reviewed, The Journal of Finance 81(2). This distillation was extracted by an LLM on 2026-05-17 and is not human-verified or independently reproduced. Licence, verification trail, and takedown policy: Open Library.
Attribution (CC BY 4.0). Kwan, Alan, Yukun Liu, and Ben Matthies. “Institutional Investor Attention.” The Journal of Finance 81, no. 2 (April 2026): 791–827. DOI: 10.1111/jofi.70009. © 2026 The Author(s). Licensed under CC BY 4.0. This page is an adaptation by the Institute for Automated Research: core results extracted and re-expressed; changes were made. The verbatim, unmodified PDF is mirrored in the Open Library.