Tail Effects and Industry Heterogeneity in Stock Return Responses to Macroeconomic Shocks: Evidence from Quantile Regression

Jintong Li ()
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Jintong Li: Northeast Forestry University

A chapter in Proceedings of the 2026 11th International Conference on Social Sciences and Economic Development (ICSSED 2026), 2026, pp 960-970 from Springer

Abstract: Abstract This paper examines Google (GOOGL), Chevron (CVX), and Southern Copper (SCCO) from the US technology, energy, and basic materials industries using monthly data from January 2016 to December 2025. We investigate the heterogeneous effects of market return, oil price return, VIX, inflation indicators, and PMI changes on stock returns. As traditional OLS regression relies on normality assumptions and cannot capture tail effects, quantile regression is applied to estimate coefficients at 19 quantiles. Wald tests and Holm-corrected pairwise tests are used to check the significance of quantile heterogeneity. Results show that key factors have significant quantile-dependent and industry-heterogeneous effects on stock returns. Systematic market factors show universal impacts, market volatility depends on extreme market conditions, and economic sentiment displays a common “right-tail strengthening” pattern. The findings provide empirical support for investors and managers, and enrich asset pricing research.

Keywords: Quantile regression; Stock return; Industry heterogeneity; Quantile heterogeneity; Market volatility (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6239-701-9_98

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DOI: 10.2991/978-94-6239-701-9_98

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