Investor heterogeneity and stock market volatility: cross-country evidence from an extended heterogeneous agent model

We study how investor heterogeneity relates to stock-market volatility in a cross-country setting using an extended fundamentalist–chartist heterogeneous agent model (HAM). We propose a time-varying heterogeneity intensity measure that combines belief differentials with endogenous investor composition to capture composition-weighted heterogeneity. Using equity index data for 12 developed and emerging markets over 2010–2023 at multiple sampling frequencies, we estimate the model for each market under a harmonized protocol. Across markets and specifications, the belief-gap measure alone is not systematically related to realized volatility, whereas the composition-weighted heterogeneity intensity exhibits a strong and robust positive association with volatility. The results highlight the importance of incorporating both heterogeneous beliefs and participation dynamics in behavioral asset-pricing frameworks and provide a parsimonious metric for characterizing time-varying heterogeneity in international equity markets.

Authors

Institutions

Publication Details

Journal
Financial Innovation
Published
2026-09-14
DOI
https://doi.org/10.1186/s40854-026-00969-y
Primary Topic
Complex Systems and Time Series Analysis
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Investor heterogeneity and stock market volatility: cross-country evidence from an extended heterogeneous agent model

Zhongqiang Zhou, Jie Li, Chee‐Wooi Hooy, Xiong Xiong
Financial Innovation
Complex Systems and Time Series Analysis
article

Investor heterogeneity and stock market volatility: cross-country evidence from an extended heterogeneous agent model

Zhongqiang Zhou, Jie Li, Chee‐Wooi Hooy, Xiong Xiong
article en

Abstract

We study how investor heterogeneity relates to stock-market volatility in a cross-country setting using an extended fundamentalist–chartist heterogeneous agent model (HAM). We propose a time-varying heterogeneity intensity measure that combines belief differentials with endogenous investor composition to capture composition-weighted heterogeneity. Using equity index data for 12 developed and emerging markets over 2010–2023 at multiple sampling frequencies, we estimate the model for each market under a harmonized protocol. Across markets and specifications, the belief-gap measure alone is not systematically related to realized volatility, whereas the composition-weighted heterogeneity intensity exhibits a strong and robust positive association with volatility. The results highlight the importance of incorporating both heterogeneous beliefs and participation dynamics in behavioral asset-pricing frameworks and provide a parsimonious metric for characterizing time-varying heterogeneity in international equity markets.

Financial InnovationVol. 12(1)
Universiti Sains Malaysia (MY), Tianjin University (CN), Guizhou University of Finance and Economics (CN), Nanjing Audit University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 6%
Complex Systems and Time Series Analysis
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.