The global financial landscape has faced profound disruptions in recent years, primarily due to the COVID-19 pandemic and the Russia–Ukraine war. These events have not only shaken traditional markets but also triggered significant shifts in cryptocurrency volatility, raising crucial questions about digital assets' resilience and role during times of extreme uncertainty. This article presents a comprehensive analysis of how top-market-cap cryptocurrencies responded to these dual crises, using advanced GARCH-type models to assess volatility persistence, leverage effects, and the impact of exogenous shocks.
By analyzing Bitcoin (BTC), Ethereum (ETH), BNB, XRP, Cardano (ADA), Tether (USDT), and USDC from January 2020 to September 2024, we uncover key behavioral patterns that matter for investors, risk managers, and regulators navigating volatile crypto markets.
Understanding Cryptocurrency Market Dynamics
The cryptocurrency ecosystem has evolved rapidly, growing from around 5,000 listed digital assets in 2020 to over 10,000 by 2024. This expansion has been fueled by innovations in decentralized finance (DeFi), non-fungible tokens (NFTs), and blockchain-based applications. Despite this growth, market behavior remains heavily influenced by speculation, investor sentiment, and external macroeconomic shocks.
During the March 2020 "Black Thursday" crash, the total crypto market cap plummeted from $223.7 billion to $135.1 billion in a single day. Bitcoin dropped 35.2%, while Ethereum fell 43.1%. Similarly, following Russia’s invasion of Ukraine in February 2022, Bitcoin briefly dipped below $35,000, and Ethereum declined over 12%, reflecting heightened risk aversion.
These episodes highlight the sensitivity of digital assets to global crises — a trait that challenges their perceived role as safe-haven instruments or diversification tools.
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Core Research Hypotheses
To evaluate cryptocurrency behavior under stress, four key hypotheses were tested:
- H1.2: Volatility exhibits persistence during financial uncertainty.
- H2.2: Negative price shocks disproportionately amplify volatility (leverage effect).
- H3.2: The COVID-19 pandemic had a stronger impact on volatility than the Russia–Ukraine war.
- H4.2: Stablecoins (USDT, USDC) serve as effective risk-hedging instruments during financial crises.
Using GARCH(1,1), EGARCH(1,1), TGARCH(1,1), and DCC-GARCH models, we examine log returns from the top seven cryptocurrencies to test these assumptions with empirical rigor.
Methodology: Modeling Volatility with GARCH Frameworks
Data Selection and Timeframe
Our dataset spans 1,705 daily observations from January 1, 2020, to September 1, 2024, capturing both the pandemic and geopolitical conflict periods. Prices were sourced from CoinMarketCap, and log returns were calculated for each asset.
Two dummy variables were introduced:
- "COVID-19": Active from March 11, 2020 (WHO declaration) to May 5, 2023 (end of global emergency).
- "WAR": Active from February 24, 2022 (start of conflict) onward.
A composite crypto index (CC7) was created as a weighted average of the seven assets to assess overall market behavior.
Model Specifications
We applied four GARCH-type models:
- GARCH(1,1): Measures volatility persistence through past shocks and lagged variance.
- EGARCH(1,1): Captures asymmetric effects — whether negative shocks increase volatility more than positive ones.
- TGARCH(1,1): Explicitly models threshold effects to detect leverage.
- DCC-GARCH: Analyzes time-varying correlations between assets.
All models included dummy variables to isolate the impact of global events on conditional volatility.
Key Empirical Findings
Volatility Persistence Is Strong — Especially During Crises
Results confirm H1.2: Cryptocurrency volatility is highly persistent. The sum of ARCH and GARCH coefficients exceeded 0.9 for most assets, indicating that shocks have long-lasting effects.
- BTC, ETH, and CC7 showed mean-reverting volatility (sum < 1), suggesting eventual stabilization.
- USDC and USDT exhibited sums > 1 — an unexpected finding given their design as stable assets — implying potential non-stationarity under stress.
This persistence underscores the importance of dynamic risk management during turbulent periods.
Leverage Effects Are Real — But Not Universal
H2.2 is partially confirmed: Negative price shocks amplify volatility in major cryptos like BTC and ETH.
- EGARCH results show significant negative leverage coefficients across all assets.
- News impact curves reveal that bad news increases volatility more than good news — especially for BTC, ETH, and CC7.
- However, TGARCH results show no significant leverage effect for BTC and XRP, suggesting symmetric responses in some cases.
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Pandemic Shock Outweighed Geopolitical Conflict
H3.2 is strongly supported: The pandemic had a greater impact on crypto volatility than the war.
- GARCH and EGARCH models show significant positive coefficients for the COVID-19 dummy in BTC (+0.0004), ETH (+0.0008), USDC (+0.0000), and CC7 (+0.0001).
- In contrast, the WAR dummy showed negative effects on BTC (−0.0011) and ETH (−0.0015), possibly due to reduced speculative activity or flight to fiat during geopolitical instability.
This suggests that global economic shocks generate broader market uncertainty than localized conflicts.
Stablecoins Show Resilience — But With Limits
H4.2 is partially validated: While USDT and USDC displayed lower volatility than other cryptos, they are not immune to market stress.
- Their near-zero mean returns align with their pegged nature.
- However, high kurtosis (fat tails) in DCC-GARCH results indicates susceptibility to extreme movements.
- Liquidity constraints during crises may undermine their reliability as hedging tools.
Thus, while stablecoins offer relative stability, they should not be assumed risk-free in systemic downturns.
Frequently Asked Questions
Q: Why is GARCH modeling important for cryptocurrencies?
A: Cryptocurrencies exhibit high volatility clustering — periods of high volatility tend to follow each other. GARCH models capture this time-varying volatility better than traditional statistical methods, making them essential for risk forecasting and portfolio management.
Q: Did Bitcoin act as a safe haven during the pandemic?
A: No conclusive evidence supports this. While some studies suggested hedging potential early in the crisis, our analysis shows Bitcoin experienced significant volatility spikes during both the pandemic and war — inconsistent with safe-haven behavior.
Q: How do stablecoins maintain price stability?
A: Stablecoins like USDT and USDC are typically backed by reserves (e.g., USD or short-term securities) and use arbitrage mechanisms to maintain their peg. However, reserve transparency and liquidity risks can challenge stability during extreme market stress.
Q: What causes leverage effects in crypto markets?
A: Leverage effects occur when negative returns lead to larger volatility increases than positive returns. In crypto, this is driven by margin trading, forced liquidations, and investor panic — all amplified during crises.
Q: Can machine learning outperform GARCH models?
A: Emerging research shows deep learning models like LSTM can outperform GARCH in short-term forecasts. However, GARCH remains widely used due to its interpretability, lower computational cost, and strong performance in modeling volatility clustering.
Q: Are cryptocurrencies decoupled from traditional markets?
A: Not entirely. While crypto markets show some independence, major events like pandemics or central bank policies (e.g., Fed rate hikes) create spillover effects that synchronize crypto with equities and commodities.
Implications for Investors and Policymakers
The findings carry practical implications:
- For investors: Diversification benefits exist but are limited during systemic shocks. Risk management strategies should account for volatility persistence and asymmetric responses.
- For exchanges: Circuit breakers or trading halts could mitigate panic selling during extreme volatility.
- For regulators: Clearer oversight of stablecoin reserves and liquidity is needed to ensure their reliability during crises.
Moreover, the growing interdependence among major cryptos — evidenced by high BTC-ETH correlation (0.88) — suggests contagion risks within the ecosystem.
Conclusion
This study confirms that major cryptocurrencies exhibit persistent volatility, especially during global crises like the COVID-19 pandemic. While negative shocks amplify volatility — supporting the presence of leverage effects — the impact varies across assets. The pandemic significantly increased market uncertainty compared to the Russia–Ukraine war, highlighting the differential effects of economic vs. geopolitical shocks.
Stablecoins offer relative stability but face limitations under extreme stress, questioning their role as full-fledged safe-haven assets.
As digital assets become increasingly integrated into global finance, understanding their behavior under duress is vital for building resilient investment strategies and regulatory frameworks.
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