We propose a tool to predict risks to economic growth and international business cycles spillovers: the GDP-Network CoVaR. Our methodology to assess Growth-at-Risk is composed by two building blocks. First, we apply the network-based NETS methodology by Barigozzi and Brownlees to identify...

While expected long-term earnings growth plays a pivotal role in valuation and investment applications, its common proxy, analysts' long-term growth forecasts (LTG), is well known for being over-optimistic. Guided by a stylized growth model, this paper uses three information sources to improve...

We compare different approaches to accounting for parameter instability in the context of macroeconomic forecasting models that assume either small, frequent changes versus models whose parameters exhibit large, rare changes. An empirical out-of-sample forecasting exercise for U.S. GDP growth...

A large set of financial variables has only limited power to predict a latent factor common to the year-ahead forecast errors for real Gross Domestic Product (GDP) growth, the unemployment rate, and Consumer Price Index (CPI) inflation for three sets of professional forecasters: the Federal...

Multiannual periods of consecutive above-median or below-median growth rates in operating performance, called runs, have a substantial influence on firm valuations. For estimating the probability of an above-median or below-median run and utilizing information efficiently, we employ a stepwise...