COVID-19 Containment Measures and Expected Stock Volatility: High-Frequency Evidence from Selected Advanced Economies

IMF Working Papers, June 4, 2021

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Study of the effect of COVID-19 containment measures on expected stock price volatility in some advanced economies.
Uses event studies with hand-collected minute-level data and panel regressions with daily data.
Authors: Viral V. Acharya, Yang Liu, Yunhui Zhao.
Publication date: June 4, 2021.

Event studies using minute-level (hand-collected) data to capture high-frequency market reactions to containment announcements.
Panel regressions using daily data to analyze broader patterns across countries and over time.

Six-month-ahead volatility indices:
- Dropped following announcements of initial or re-imposed lockdowns.
- Did not drop significantly following the easing of lockdowns.
Three-month-ahead expected volatility:
- Patterns of decline following lockdown announcements are present but not as strong as for six-month-ahead indices.
One-month-ahead expected volatility:
- Generally absent patterns; no consistent decline following lockdown announcements.
Interpretation:
- Findings provide suggestive evidence for an intertemporal trade-off: although stringent containment measures cause short-term economic disruptions, they may reduce medium-term uncertainty (reflected in expected stock volatility) by boosting markets’ confidence that the outbreak would be under control more quickly.

Stringent containment measures can reduce medium-term market uncertainty even if they introduce short-term disruptions.
Easing of lockdowns may not immediately reduce medium-term expected volatility; markets may not interpret easing as reducing uncertainty about outbreak control.
Consideration of intertemporal trade-offs is important when designing containment and reopening policies given financial market reactions.