Abstract
The cryptocurrency market offers significant investment opportunities but also entails higher risks compared to traditional asset classes. This article analyzes the financial risk characteristics of individual cryptocurrencies and a broad cryptocurrency market portfolio. We examine a portfolio comprising the 20 largest cryptocurrencies, covering 82.1% of the total market capitalization.
Key findings:
- Cryptocurrencies exhibit high volatility and heavy-tailed return distributions.
- Bitcoin is the most stable cryptocurrency, while Shiba Inu shows the highest risk.
- Strong intra-market correlations exist, particularly with Bitcoin and Ethereum.
- No diversification benefits are observed in portfolio aggregation.
Introduction
The cryptocurrency market has grown exponentially since Bitcoin's inception in 2009. By 2021, global cryptocurrency ownership surged from 66 million to over 295 million users (Hon et al., 2022). This growth reflects increasing investor interest but also highlights knowledge gaps and risk management challenges.
Key Objectives:
- Assess tail risks using Extreme Value Theory (EVT).
- Apply the GARCH-EVT approach to model volatility and tail distributions.
- Evaluate portfolio diversification via a t-Student Copula.
Methodology
Data Sources
- CoinGecko: Primary data provider for cryptocurrency prices and market caps.
- Portfolio Selection: 20 largest cryptocurrencies by market capitalization (e.g., Bitcoin, Ethereum, Solana).
Analytical Framework
- Descriptive Statistics: Mean, variance, skewness, and kurtosis of returns.
Risk Measures:
- Value-at-Risk (VaR)
- Expected Shortfall (ES)
Extreme Value Theory (EVT):
- Peaks-over-Threshold Method (POTM) for tail risk modeling.
- Automated threshold selection via the FindTheTail algorithm.
Copula Analysis:
- t-Student Copula to model joint distributions and dependencies.
Results
Individual Cryptocurrency Risks
| Cryptocurrency | Daily Return Mean | Standard Deviation | VaR (99%) |
|---------------|------------------|-------------------|-----------|
| Bitcoin (BTC) | 0.17% | 4.13% | 12.51% |
| Ethereum (ETH)| 0.34% | 6.00% | 16.22% |
| Shiba Inu (SHIB)| 1.61% | 24.38% | 51.91% |
Portfolio Aggregation
- Strong correlations between cryptocurrencies (e.g., BTC-ETH: 0.568).
- No diversification benefit: Portfolio VaR (99.9%) = 21.98%.
Discussion
Key Takeaways:
- Cryptocurrencies are highly volatile with extreme tail risks.
- Bitcoin remains the least risky asset, while altcoins (e.g., SHIB) amplify risk.
- Portfolio formation does not mitigate risk due to strong intra-market correlations.
Future Research Directions:
- Stablecoin integration for risk reduction.
- Sector-specific analysis (e.g., DeFi, NFTs).
FAQ Section
1. How does EVT improve risk assessment?
EVT models extreme quantiles of return distributions, providing more accurate VaR and ES estimates for tail events.
2. Why use a t-Student Copula?
It captures tail dependencies better than Gaussian copulas, crucial for cryptocurrency markets.
3. Can diversification reduce cryptocurrency risk?
Our analysis shows minimal benefits due to high correlations.
👉 Learn more about cryptocurrency risk management
References
- Hon, H., et al. (2022). Global Crypto Adoption Trends.
- CoinGecko. (2022). Cryptocurrency Market Data.