Heavy-Tail Risk in Traditional Versus Crypto Markets: A Q-Q Plot-Based Analysis
Abstract
This paper investigates extreme risk in cryptocurrency markets by comparing Bitcoin and Ethereum daily returns with those of S&P 500 and SPY ETF. Using the Generalized Tempered Stable (GTS) distribution to model heavy tails and Quantile-Quantile (Q-Q) plots to assess fitness, we find that all assets deviate sharply from normal distribution. Within this framework, Ethereum exhibits a higher frequency of extreme returns than Bitcoin, highlighting differences in risk profiles even among leading cryptocurrencies.
Fields of Study & Subjects
Credit Risk and Financial Regulations
Financial Risk and Volatility Modeling
Financial Markets and Investment Strategies
Publication details
- Journal / source
- 2026 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA)
- Publisher
- IEEE
- Pages
- 1–6
- Publication date
- 5 February 2026