In this paper, we propose asset class liquidity risk indicators constructed by aggregating financial, monetary and credit variables. We measure the presence of liquidity in six highly representative markets such as the Equity Europe, Long Term Italian Government Bond, Short Term Euro Government Bond, Equity US, Bond Corporate Investment Grade USD, Short Term US Government Bond markets over the period January 2007–January 2023. Our approach allows for a time-varying measure of the relative contribution of the raw drivers to the asset class indicators. We use endogenous Markov-switching models to identify episodes of financial distress which have characterized the behaviour of assets over the last two decades. Finally, we map the Markov-switching regimes with bubble episodes identified via recursive testing procedures.