Who leads in price discovery? Trading frictions and return transmission in spot Bitcoin ETFs

This paper investigates how trading frictions shape return lead – lag dynamics among U.S. spot Bitcoin ETFs. A structural model predicts that low-cost, high-liquidity ETFs incorporate new information faster, while high-friction ETFs adjust with delay. Using five-minute returns from 11 SEC-approved ETFs covering the period from 11 January 2024 to 31 January 2025, we apply time-varying VAR, Granger causality tests, impulse responses, and variance decompositions. Results show consistent leadership of low-friction ETFs in price discovery, with directional return transmission that depends on bid – ask spreads and trading volume. The findings highlight microstructural segmentation in crypto markets and underscore the importance of transparency and investor protection.