Modelling the dynamics of (il)liquidity across assets is an important yet complicated task, especially when considering significant deteriorations of liquidity conditions. Here, we propose a peak-over-threshold method to identify abrupt liquidity drops from limit order book data and we model the time-series of these illiquidity events across multiple assets as a multivariate Hawkes process. This allows us to quantify both the self-excitation of extreme changes of liquidity in the same asset (illiquidity spirals) and the cross-excitation across different assets (illiquidity spillovers). Applying the method to the MTS sovereign bond market, we find significant evidence for both illiquidity spillovers and spirals. The proportion of shocks explained by illiquidity spillovers roughly doubles from 2011 to 2015, suggesting an increased synchronization of extreme illiquidity across assets.
Quantitative Finance , Vol. 18, Issue 2, pp.283-293