Herding Behavior across Different Market Return and Volatility Conditions

Articles in Press

Document Type : Original Article

Authors

majid aghaei ¹

mohammad abdi ²

alireza hosseini ²

¹ Department of economic, university of Mazandaran, Passdaran Street, Babolsar, Iran

² Department of Economics, University of Mazandaran

10.22067/ijaaf.2026.100413.1732

Abstract

This study examines the nonlinear relationships between market returns, historical volatility, and cross-sectional stock return dispersion in the Tehran Stock Exchange (TSE). Daily firm-level and market-index data from March 2015 to March 2021 are analyzed using a volatility-augmented Cross-Sectional Absolute Deviation (CSAD) model. The reference cross-sections comprise 100 actively traded TSE firms benchmarked to the TSE Total Index and 30 firms selected from the TSE Top 50 Most Active Companies universe benchmarked to the corresponding index. Historical volatility is measured over a 20-trading-day rolling window. Estimation combines Ordinary Least Squares (OLS), with Newey–West HAC standard errors, and quantile regression. The squared-return coefficient is negative and statistically significant in both OLS specifications and at conditional CSAD quantiles 0.01, 0.05, 0.25, 0.50, and 0.75, providing evidence consistent with the conventional herding criterion. The estimates at quantiles 0.95 and 0.99 are statistically insignificant. Volatility terms are jointly significant in both OLS models. Evaluating the linear and quadratic terms together shows that the fitted OLS volatility–dispersion slope remains positive throughout the observed range for the Total Index-based sample, whereas the Top 50-based specification has a turning point within its observed range. Quantile estimates provide further evidence of nonlinear volatility–dispersion relationships at several conditional quantiles. The study contributes comparative evidence on return-based herding indicators and historical volatility across two Iranian equity-market samples. Its findings distinguish negative volatility curvature from declining dispersion and show that historical volatility adds explanatory information beyond market returns. The estimated associations leave intentional imitation and common responses to information unresolved.

Keywords

Herding Behavior

Market Volatility

Market Return

Quantile Regression

CSAD

Subjects

• Finance

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