This paper employs a recent statistical algorithm (CRAGGING) in order to build an early warning model for banking crises in emerging markets. We perturb our data set many times and create "artificial" samples from which we estimated our model, so that, by construction, it is flexible enough to...

Suppose a fund manager uses predictors in changing portfolio allocations over time. How does predictability translate into portfolio decisions? To answer this question we derive a new model within the Bayesian framework, where managers are assumed to modulate the systematic risk in part by...

We model the learning process of market traders during the unprecedented COVID-19 event. We introduce a behavioral heterogeneous agents' model with bounded rationality by including a correction mechanism through representativeness (Gennaioli et al., 2015). To inspect the market crash induced by...

We construct a unique and comprehensive data set of 19 real-time daily macroeconomic indicators for 11 Eurozone countries, for the 5/11/2009{4/25/2013 period. We use this new data set to characterize the time-varying dependence of the cross-section of sovereign credit default swap (CDS) spreads...

A major gap exists between the conceptual suggestion of how much a nation should invest in science, innovation, and technology, and the practical implementation of what is done. We identify 4 critical challenges that must be address in order to develop an environment conducive to collaboration...