The Predictive Relationship Between Stablecoin and Cryptocurrency Returns During Periods of Intense Market Stress

Active asset managers are increasingly including cryptocurrencies in their alternative asset allocations, highlighting their speculative and volatile nature. The aim of this research is to examine trends in the returns and volatility of cryptocurrencies while accounting for the depegging of stablecoins driven by speculative trading macroeconomic shocks, and technological shifts. It builds a sample, by market capitalisation, using data from the daily closing prices of Bitcoin (BTC), Ethereum (ETH), Binance (BNB), and Ripple (XRP), two fiat-backed stablecoins (USDT and USDC) and a cryptocurrency-collateralised stablecoin (DAI). As a first step, Granger causality tests were applied to examine the influence of stablecoin depegging events on crypto returns during financial market stress. The results indicate that DAI exhibits the most consistent Granger-causal relationship with cryptocurrency returns; whereas, the predictive power of USDT and USDC depegging events varies across assets. The analysis was extended by modelling volatility using an EGARCH-X model to study whether depegs also affect crypto during periods of market stress. In this case, the evidence for statistically significant effects is limited. Nevertheless, in the instances where significance is detected, the results are consistently linked to USDC.