Systemic risk from financial leverage in digital asset markets: evidence from cryptocurrency derivatives

Purpose This paper aims to investigate how financial leverage in cryptocurrency perpetual swap markets generates and transmits systemic risk. Design/methodology/approach 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. Findings 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. Research limitations/implications 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. Practical implications 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. Social implications Mitigating leverage-driven crashes protects retail investors disproportionately affected by liquidation cascades and strengthens confidence in digital asset markets. Originality/value 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.