Introduction
The 2008 whitepaper "Bitcoin: A Peer-to-Peer Electronic Cash System" marked the birth of Bitcoin and the subsequent rise of blockchain-based cryptocurrencies. As a nascent financial market, cryptocurrencies have garnered global attention from governments, investors, and researchers. The COVID-19 pandemic in Q1 2020 triggered a "cliff-like drop" in U.S. stocks, alongside the "Black Thursday" crash (March 12, 2020) in cryptocurrency markets. This raises a critical question: Is there a measurable correlation between these markets that drives synchronized reactions to macroeconomic events?
This study investigates the dynamic linkage between cryptocurrency and U.S. equity markets, employing time-varying conditional correlation coefficients to decode volatility patterns. Our goal is to provide actionable insights for regulators and investors.
Literature Review
Key Financial Models
- ARCH/GARCH: Engel’s ARCH (1982) and Bollerslev’s GARCH (1986) models address conditional volatility clustering in asset returns.
- Copula Theory: Patton (2006) demonstrated asymmetric dependencies in currency markets using Copula-GARCH, while Chinese scholars like Wei Yanhua applied it to equity market analysis.
Cryptocurrency Research Themes
- Market Attributes: Studies highlight Bitcoin’s high risk-return profile and speculative nature (Dyhrberg, 2016).
- Portfolio Hedging: Bitcoin shows hedging potential against FTSE indices (Dyhrberg) but fails as a "safe haven" during COVID-19 (Conlon et al., 2020).
- Market Linkages: Cryptocurrencies exhibit weak but growing ties to traditional markets (Zeng et al., 2021).
Research Gaps
- Few studies analyze linkages post-2018, when cryptocurrencies matured.
- Divergent conclusions (e.g., Bitcoin’s similarity to gold) warrant fresh methodologies.
Our Contributions:
- First use of t-Copula-GARCH-Skewed-T to model nonlinear dependencies.
- Updated dataset (2016–2021) reflecting recent market shifts.
- Policy recommendations for regulatory frameworks.
Methodology
1. Copula Functions
Sklar’s theorem enables joint distribution modeling via marginal distributions and Copulas. We test four Copulas:
- Gaussian: Linear correlations.
- Clayton: Lower-tail dependence.
- SJC: Asymmetric tails.
- t-Copula: Best fit (lowest AIC, highest log-likelihood).
2. Marginal Distributions
GARCH(1,1) with Skewed-T errors accommodates:
- Volatility clustering (ARCH effects).
- Fat tails and negative skewness in returns.
Mean Equation:
[
r_t = \mu + \epsilon_t
]
Variance Equation:
[
\sigma_t^2 = \omega + \alpha \epsilon_{t-1}^2 + \beta \sigma_{t-1}^2
]
3. Dynamic Conditional Correlation (DCC)
Time-varying t-Copula parameters:
- Persistence (β ≈ 0.95): Past correlations heavily influence current linkages.
- Freedom parameter (v ≈ 20): Captures tail dependence.
Empirical Analysis
Data
- Cryptocurrency: NYXBT Bitcoin Index.
- Stocks: S&P 500.
- Sample: 1,261 daily observations (2016–2021).
Key Findings
Strengthening Linkage:
- Correlation coefficients rose from 0.10 (2017) to 0.24 (2020).
- Peaks aligned with major events (Figure 5).
Event-Driven Volatility:
- 2017 Regulatory Shifts: U.S. policies boosted investor optimism, lifting both markets.
- 2018 Trade War: Tariffs eroded confidence, amplifying synchronized sell-offs.
- 2020 COVID-19: Pandemic-induced panic caused the highest correlation spike (Figure 7).
Conclusions & Recommendations
Findings
- Cryptocurrencies and U.S. stocks show asymmetric, fat-tailed returns, with stronger post-2018 linkages.
- Macroeconomics (e.g., trade wars, pandemics) drive synchronized volatility via investor sentiment.
Policy Actions
👉 For Regulators:
- Enhance crypto oversight to prevent spillover risks.
- Develop central bank digital currencies (CBDCs) to curb illicit uses while harnessing blockchain benefits.
👉 For Investors:
- Diversify across low-correlation assets.
- Monitor event-driven linkages (e.g., Fed policies, geopolitical crises).
FAQs
Q1: Why did COVID-19 amplify market linkages?
A1: Panic-induced asset reallocations reduced liquidity, causing parallel crashes in both markets.
Q2: Is Bitcoin a viable hedge against stocks?
A2: Only in short-term bull markets; long-term hedging efficacy is weak.
Q3: How can regulators mitigate crypto-stock spillovers?
A3: Stress-test financial systems for crypto shocks and mandate transparent reporting.
👉 Explore real-time market trends here to stay ahead of volatility shifts!
Methodology Note: All hyperlinks except the OKX anchor are removed per guidelines. Tables/figures are described textually for accessibility.