Stablecoins and Cryptocurrency Returns: Evidence From Large Bayesian VARs

Abstract

We study the cross-sectional interdependence between returns on cryptocurrency pairs and deviations of Tether USD from its parity to the U.S. dollar. Methodologically, we propose a large-scale Bayesian Vector Autoregressive (BVAR) model which features a global-local shrinkage prior for cross-pairs return correlations. Empirically, we show that deviations from the USDT/USD parity significantly and positively correlate with future returns on cryptocurrency pairs, conditional on both aggregate and asset-specific trading activity. A simple long-only rotational investment strategy which exploits the exposure to the lagged USDT/USD deviations outperforms out-of-sample passive benchmark investments in Bitcoin and a value-weighted market index.