This paper introduces the probabilistic formulation of continuous-time economic models: forward stochastic differential equations (SDE) govern the dynamics of backward-looking variables, and backward SDEs capture that of forward-looking variables. Deep learning streamlines the search for the...

This paper introduces a new test of the predictive performance and market timing for categorical forecasts based on contingency tables when the user has non-categorical loss functions. For example, a user might be interested in the return of an underlying variable instead of just the direction....

Using a novel dataset that contains qualitative firm survey data on sales forecasts as well as balance-sheet data on realized sales, we document that only major forecast errors are predictable and display autocorrelation. This result is a particular violation of the Full Information Rational...

This paper provides a detailed assessment of the real-time forecast accuracy of a wide range of vector autoregressive models (VAR) that allow for both structural change and indicators sampled at different frequencies. We extend the literature by evaluating a mixed-frequency time-varying...

We have argued that from the standpoint of a policy maker who has access to a number of expert forecasts, the uncertainty of a combined forecast should be interpreted as that of a typical forecaster randomly drawn from the pool. With a standard factor decomposition of a panel of forecasts, we...