Does the Facial Trustworthiness of Hosting Staff Lead to Forecast Bias? Evidence from Analysts’ Site Visits

We use unique data about corporate site visits in China to examine whether face‐to‐face interactions introduce bias in analyst forecasts. We find that analysts tend to issue more optimistic forecasts when accompanied by hosting staff with high facial trustworthiness, indicating a cognitive bias. This effect is amplified when firms convey more positive information during visits, but is attenuated for firms with high disclosure quality, for experienced and star analysts, for analysts with science, technology, engineering, and mathematics backgrounds, and for analysts visiting industry peers concurrently. Furthermore, the bias is stronger for sole‐visiting analysts but diminishes over time as additional information becomes available or with repeated interactions. Additional analyses show that forecast accuracy also declines, but the effect of facial trustworthiness does not extend to analysts’ stock recommendations or market reactions. Overall, our findings highlight that even sophisticated analysts are susceptible to cognitive bias in face‐to‐face interactions, while alternative information sources, professional experience, and repeated engagement help mitigate such bias.

Authors

Institutions

Publication Details

Journal
Abacus
Published
2026-11-05
DOI
https://doi.org/10.1111/abac.70061
Primary Topic
Auditing, Earnings Management, Governance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
article

Does the Facial Trustworthiness of Hosting Staff Lead to Forecast Bias? Evidence from Analysts’ Site Visits

Zihui Li, Jiyuan Li
Abacus
Auditing, Earnings Management, Governance
article

Does the Facial Trustworthiness of Hosting Staff Lead to Forecast Bias? Evidence from Analysts’ Site Visits

Zihui Li, Jiyuan Li
article en

Abstract

We use unique data about corporate site visits in China to examine whether face‐to‐face interactions introduce bias in analyst forecasts. We find that analysts tend to issue more optimistic forecasts when accompanied by hosting staff with high facial trustworthiness, indicating a cognitive bias. This effect is amplified when firms convey more positive information during visits, but is attenuated for firms with high disclosure quality, for experienced and star analysts, for analysts with science, technology, engineering, and mathematics backgrounds, and for analysts visiting industry peers concurrently. Furthermore, the bias is stronger for sole‐visiting analysts but diminishes over time as additional information becomes available or with repeated interactions. Additional analyses show that forecast accuracy also declines, but the effect of facial trustworthiness does not extend to analysts’ stock recommendations or market reactions. Overall, our findings highlight that even sophisticated analysts are susceptible to cognitive bias in face‐to‐face interactions, while alternative information sources, professional experience, and repeated engagement help mitigate such bias.

Abacus
University of International Business and Economics (CN), Chongqing University of Technology (CN)
Openalex Percentile: Top 8%
Auditing, Earnings Management, Governance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon