We propose a general method for the Bayesian estimation of nonlinear no-arbitrage term structure models. The main innovations we introduce are: 1) a computationally efficient method, based on deep learning techniques, for approximating no-arbitrage model-implied bond yields to any desired degree...

We propose a methodology to build and validate a composite indicator of the market liquidity of euro-area sovereign bonds. The indicator aggregates several metrics from different trading venues, with the aim of providing a comprehensive measurement of prevailing bond-market liquidity conditions...