Asymmetric return dynamics and stock price crash risk: Evidence from a quantile regression analysis of an emerging market

Purpose — Understanding extreme downside risk is particularly important in emerging equity markets, where higher market volatility, lower liquidity, and weaker information environments make stock prices more vulnerable to sudden, severe crashes. This study examines downside risk, stock price crash risk, and lower-tail return dynamics using firm-level stock return data for firms listed in the Pakistan Stock Exchange over the period 2014–2024. Method — Using panel regression and quantile regression techniques, the study investigates the determinants of crash risk and assesses the predictive role of downside risk for future equity returns. Findings — The results indicate that downside risk is strongly associated with a higher likelihood of extreme negative return realisations, while its effect on average returns remains limited. Quantile-based estimates further show that the impact of downside risk intensifies substantially in the lower tail of the return distribution, highlighting pronounced return asymmetries. These patterns persist across both financial and non-financial firms, although their magnitude varies with market conditions. Implications — The results carry important implications for investors, regulators, and risk managers concerned with downside protection and the identification of early warning signals in emerging equity markets.Originality — This study provides new firm-level evidence from an emerging equity market by jointly examining downside risk, crash risk, and return tail behaviour within a unified empirical framework by using quantile regression.

Authors

Publication Details

Journal
Economic Journal of Emerging Markets
Published
2026-04-30
DOI
https://doi.org/10.20885/ejem.vol18.iss1.art9
Primary Topic
Financial Markets and Investment Strategies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Asymmetric return dynamics and stock price crash risk: Evidence from a quantile regression analysis of an emerging market

Fizza Rizvi, Unbreen Arif, Bilal Ahmad, Sarah Azhar
Economic Journal of Emerging Markets
Financial Markets and Investment Strategies
article

Asymmetric return dynamics and stock price crash risk: Evidence from a quantile regression analysis of an emerging market

Fizza Rizvi, Unbreen Arif, Bilal Ahmad, Sarah Azhar
article en

Abstract

Purpose — Understanding extreme downside risk is particularly important in emerging equity markets, where higher market volatility, lower liquidity, and weaker information environments make stock prices more vulnerable to sudden, severe crashes. This study examines downside risk, stock price crash risk, and lower-tail return dynamics using firm-level stock return data for firms listed in the Pakistan Stock Exchange over the period 2014–2024. Method — Using panel regression and quantile regression techniques, the study investigates the determinants of crash risk and assesses the predictive role of downside risk for future equity returns. Findings — The results indicate that downside risk is strongly associated with a higher likelihood of extreme negative return realisations, while its effect on average returns remains limited. Quantile-based estimates further show that the impact of downside risk intensifies substantially in the lower tail of the return distribution, highlighting pronounced return asymmetries. These patterns persist across both financial and non-financial firms, although their magnitude varies with market conditions. Implications — The results carry important implications for investors, regulators, and risk managers concerned with downside protection and the identification of early warning signals in emerging equity markets.Originality — This study provides new firm-level evidence from an emerging equity market by jointly examining downside risk, crash risk, and return tail behaviour within a unified empirical framework by using quantile regression.

Economic Journal of Emerging Markets
Openalex Percentile: Top 7%
Financial Markets and Investment Strategies
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.