Liquidity Recovery Dynamics Following Volatility Shocks: Evidence from an Emerging Equity Market

Understanding how quickly trading liquidity recovers after volatility shocks is central to evaluating market resilience and trading costs in financial markets. The purpose of this study is to examine how quickly trading liquidity recovers after volatility-based stress shocks in an emerging equity market and to evaluate whether recovery horizons vary systematically across shock severity, market fear, downside-risk conditions, and sectors. Using a balanced panel of NIFTY-50 firms over 2018–2024, comprising 91,350 firm-day observations, the analysis employs a non-parametric event-time framework, combined with bootstrap inference and episode-level regression diagnostics, to trace the adjustment in market liquidity following episodes of elevated volatility. Liquidity conditions are measured using the Amihud illiquidity indicator, while stress episodes are identified through firm-specific volatility shocks derived from a standardised realised-volatility measure. The framework introduces duration-based recovery metrics—liquidity half-life and time-to-normalisation—to quantify the persistence of post-shock trading frictions relative to firm-specific pre-stress baselines. Across 602 declustered stress episodes, liquidity deteriorates sharply on the stress day and recovers only gradually thereafter. The estimated mean recovery half-life is slightly above five trading days, while nearly one-third of episodes do not fully normalise within twenty trading days, indicating economically meaningful persistence in post-shock illiquidity. Recovery dynamics also vary systematically across stress severity, market-wide fear conditions (India VIX), downside-risk regimes, and sectors, highlighting that market resilience is state-dependent rather than uniform. The findings provide new evidence on the temporal structure of liquidity adjustment in emerging equity markets and introduce operational recovery-horizon metrics that can inform liquidity risk management, trading execution strategies, and market surveillance during periods of elevated volatility. These recovery-horizon measures have direct practical relevance for portfolio managers and institutional traders because they provide an operational basis for planning execution strategies when market liquidity remains impaired after volatility shocks. They are also useful for exchanges and regulators seeking to complement volatility monitoring with post-shock liquidity surveillance, thereby improving the assessment of market functioning during periods of elevated stress.

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Publication Details

Journal
International Journal of Financial Studies
Published
2026-05-02
DOI
https://doi.org/10.3390/ijfs14050111
Primary Topic
Financial Markets and Investment Strategies
Type
article
Field-Weighted Citation Impact
0.00
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article

Liquidity Recovery Dynamics Following Volatility Shocks: Evidence from an Emerging Equity Market

Ashok Kumar Panigrahi, Varun Sarda, Anita Sharma
International Journal of Financial Studies
Financial Markets and Investment Strategies
article

Liquidity Recovery Dynamics Following Volatility Shocks: Evidence from an Emerging Equity Market

Ashok Kumar Panigrahi, Varun Sarda, Anita Sharma
article en

Abstract

Understanding how quickly trading liquidity recovers after volatility shocks is central to evaluating market resilience and trading costs in financial markets. The purpose of this study is to examine how quickly trading liquidity recovers after volatility-based stress shocks in an emerging equity market and to evaluate whether recovery horizons vary systematically across shock severity, market fear, downside-risk conditions, and sectors. Using a balanced panel of NIFTY-50 firms over 2018–2024, comprising 91,350 firm-day observations, the analysis employs a non-parametric event-time framework, combined with bootstrap inference and episode-level regression diagnostics, to trace the adjustment in market liquidity following episodes of elevated volatility. Liquidity conditions are measured using the Amihud illiquidity indicator, while stress episodes are identified through firm-specific volatility shocks derived from a standardised realised-volatility measure. The framework introduces duration-based recovery metrics—liquidity half-life and time-to-normalisation—to quantify the persistence of post-shock trading frictions relative to firm-specific pre-stress baselines. Across 602 declustered stress episodes, liquidity deteriorates sharply on the stress day and recovers only gradually thereafter. The estimated mean recovery half-life is slightly above five trading days, while nearly one-third of episodes do not fully normalise within twenty trading days, indicating economically meaningful persistence in post-shock illiquidity. Recovery dynamics also vary systematically across stress severity, market-wide fear conditions (India VIX), downside-risk regimes, and sectors, highlighting that market resilience is state-dependent rather than uniform. The findings provide new evidence on the temporal structure of liquidity adjustment in emerging equity markets and introduce operational recovery-horizon metrics that can inform liquidity risk management, trading execution strategies, and market surveillance during periods of elevated volatility. These recovery-horizon measures have direct practical relevance for portfolio managers and institutional traders because they provide an operational basis for planning execution strategies when market liquidity remains impaired after volatility shocks. They are also useful for exchanges and regulators seeking to complement volatility monitoring with post-shock liquidity surveillance, thereby improving the assessment of market functioning during periods of elevated stress.

International Journal of Financial StudiesVol. 14(5)
Guru Gobind Singh Indraprastha University (IN), Manipal Academy of Higher Education (IN), Narsee Monjee Institute of Management Studies (IN)
Partnerships for the goals
Openalex Percentile: Top 6%
Financial Markets and Investment Strategies
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