Market efficiency hypothesis suggests a zero level for the intraday interest rate. However, a liquidity crisis introduces frictions related to news, which can cause an upward jump of the intraday rate. This paper documents that these dynamics can be partially predicted during turbulent times. A long memory approach outperforms random walk and autoregressive benchmarks in terms of point and density forecasting. The gains are particular high when the full distribution is predicted and probabilistic assessments of future movements of the interest rate derived by the model can be used as a policy tool for central banks to plan supplementary market operations during turbulent times. Adding exogenous variables to proxy funding liquidity and counterparty risks does not improve forecast accuracy and the predictability seems to derive from the econometric properties of the series more than from news available to financial markets in realtime.