We provide a framework for inference in dynamic equilibrium models including financial market data at daily frequency, along with macro series at standard lower frequency. Our formulation of the macro-finance model in continuous time conveniently accounts for the difference in observation...

We provide a framework for inference in dynamic equilibrium models including financial market data at daily frequency, along with macro series at standard lower frequency. Our formulation of the macro-finance model in continuous-time conveniently accounts for the difference in observation...

We propose a Bayesian infinite hidden Markov model to estimate time-varying parameters in a vector autoregressive model. The Markov structure allows for heterogeneity over time while accounting for state-persistence. By modelling the transition distribution as a Dirichlet process mixture model,...

This paper provides a comprehensive economic evaluation of the short-horizon predictive ability of liquidity on monthly stock returns, using dynamic asset allocation strategies. We assess the economic value of the out-of-sample power of empirical models based on different liquidity measures and...