This paper aims to investigate how financial leverage in cryptocurrency perpetual swap markets generates and transmits systemic risk.
Using daily and hourly derivatives data for 10 major cryptocurrencies on Binance’s USDT-margined perpetual swap market (2023–2024), the authors apply four complementary methods: a panel logit early-warning model, generalized forecast error variance decomposition, event-study cascade analysis and circuit-breaker counterfactual simulations.
Bitcoin open interest changes are the strongest crash predictor (odds ratio = 1.48, out-of-sample area under the receiver operating characteristic curve = 0.677). Ethereum emerges as the dominant net transmitter of risk in the connectedness network (total connectedness = 79.8%). Liquidation cascades propagate across 6 of 10 assets within 2 h. Circuit breakers could reduce crash severity by 6–12 percentage points.
The analysis covers a single exchange and 10 assets; results may not generalize to multi-exchange or decentralized settings. The model is best suited as one component of a broader surveillance system.
Binance, the sampled exchange and comparable centralized derivatives venues can implement real-time leverage dashboards, adaptive margin requirements linked to aggregate open interest and pilot open-interest-based circuit breakers.
Mitigating leverage-driven crashes protects retail investors disproportionately affected by liquidation cascades and strengthens confidence in digital asset markets.
To the best of the authors’ knowledge, this study provides the first integrated framework for analyzing leverage-driven systemic risk in crypto derivatives and the first quantitative evidence supporting leverage-based circuit breakers.
