Volatility of Top Market-Cap Cryptocurrencies During COVID-19 and the Russia-Ukraine War: Evidence from GARCH Models

1. Introduction

The global financial landscape has experienced unprecedented disruptions in recent years, primarily due to the COVID-19 pandemic and the Russia-Ukraine war. The COVID-19 outbreak triggered a severe economic downturn, leading to heightened uncertainty in financial markets. The Russia-Ukraine war further exacerbated commodity volatility, driven by geopolitical tensions and investor panic.

Key Insights:

• Cryptocurrency markets showed significant volatility during these crises.
• Regulatory announcements during the pandemic intensified market fluctuations.
• Geopolitical conflicts reduced liquidity and returns for cryptocurrencies.

This study examines the resilience of cryptocurrencies during these extreme events using GARCH-type models, focusing on volatility persistence, leverage effects, and event-specific impacts.

2. Literature Review

2.1 Cryptocurrency Market Evolution

The cryptocurrency market has grown exponentially, with over 10,000 digital assets traded by 2024. Key developments include:

• DeFi and NFTs: Innovations driving market expansion.
• Market Corrections: Notable drops during COVID-19 (e.g., Bitcoin fell 35.2% on March 13, 2020).
• Geopolitical Impact: Russia-Ukraine war caused a 12% decline in Ethereum.

2.2 Volatility Drivers

• Speculative Trading: Over 30% of Bitcoin is held for investment purposes.
• Market Forces: Bitcoin prices are primarily demand-driven.
• Global Events: COVID-19 and geopolitical conflicts amplified volatility.

2.3 GARCH Models in Cryptocurrency Research

GARCH models are widely used to analyze cryptocurrency volatility. Studies highlight:

• Volatility Clustering: Persistent high volatility periods.
• Leverage Effects: Negative shocks disproportionately impact volatility.

3. Research Hypotheses

H1: Volatility Dynamics

• H1.1: No persistent volatility during crises.
• H1.2: Persistent volatility during crises (confirmed).

H2: Leverage Effects

• H2.1: No amplified volatility from negative shocks.
• H2.2: Amplified volatility from negative shocks (partially confirmed).

H3: Event-Specific Impact

• H3.1: Equal impact from COVID-19 and war.
• H3.2: Stronger impact from COVID-19 (confirmed).

H4: Stablecoin Stability

• H4.1: No risk-hedging role.
• H4.2: Effective risk-hedging role (partially confirmed).

4. Methodology

4.1 Data Selection

• Assets Analyzed: Bitcoin (BTC), Ethereum (ETH), Tether (USDT), BNB (BNB), USDC (USDC), XRP (XRP), Cardano (ADA).
• Period: January 2020 to September 2024.
• Variables: COVID-19 and WAR dummies to capture event impacts.

4.2 Models Used

1. GARCH(1,1): Baseline volatility persistence.
2. EGARCH(1,1): Asymmetric volatility effects.
3. TGARCH(1,1): Threshold effects.
4. DCC-GARCH: Dynamic correlations.

5. Empirical Results

5.1 Descriptive Statistics

• Leptokurtic Distributions: Heavy tails for all cryptocurrencies.
• Volatility Clustering: ADA, BNB, and CC7 showed pronounced clustering.

5.2 Stationarity Tests

• ADF Test: All series stationary (p < 0.01).
• Zivot-Andrews Test: Confirmed stationarity with structural breaks.

5.3 Model Outcomes

• GARCH(1,1): High volatility persistence (sum of ARCH + GARCH ≈ 1).
• EGARCH(1,1): Significant leverage effects for BTC and ETH.
• TGARCH(1,1): Negative shocks increased volatility disproportionately.
• DCC-GARCH: Strong dynamic correlations among assets.

6. Discussion

Key Findings:

1. Volatility Persistence: Confirmed during crises.
2. Leverage Effects: More pronounced in speculative assets (BTC, ETH).
3. COVID-19 Impact: Stronger than geopolitical conflicts.
4. Stablecoins: Partial hedging effectiveness.

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7. Conclusion

Policy Implications:

1. Regulatory Clarity: Needed to manage volatility.
2. Investor Awareness: Highlight risks during crises.
3. Stablecoin Oversight: Ensure liquidity and reserve adequacy.

Future Research:

• Extend analysis to newer cryptocurrencies.
• Investigate DeFi tokens' behavior during crises.

FAQs

Q1: How did COVID-19 affect cryptocurrency volatility?

A1: COVID-19 significantly increased volatility, with Bitcoin dropping 35.2% on March 13, 2020.

Q2: Are stablecoins effective hedges during crises?

A2: Partially. USDC and USDT showed relative stability but faced liquidity constraints.

Q3: Which model best captures cryptocurrency volatility?

A3: EGARCH(1,1) effectively models asymmetric volatility responses.

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