I study real effects of uncertainty shocks. Using time-varying volatility of the forecast error, I construct a two-part uncertainty metric that consists of persistent and volatile, burstlike components. These indices are used to study empirically several predictions of uncertainty models: that...

Macroeconomic forecasts are persistently too optimistic. This paper finds that common factors related to general uncertainty about U.S. macrofinancial prospects and global demand drive this overoptimism. These common factors matter most for advanced economies and G-20 countries. The results...

To nowcast output gap turning points, probabilistic indicators are created from a simple and transparent machine-learning algorithm known as Learning Vector Quantization. The real-time ability of the indicators to quickly and accurately detect economic turning points in the United States and in...

A large set of macroeconomic variables have been suggested as equity risk premium predictors in the literature. This paper proposes a forecasting approach for the equity risk premium with two novel features. First, individual month-ahead forecasts are obtained from parsimonious threshold...

We investigate the relationship between long-term U.S. stock market risks and the macroeconomic environment using a two component GARCH-MIDAS model. Our results show that macroeconomic variables are important determinants of the secular component of stock market volatility. Among the various...

We survey the literature on stock return forecasting, highlighting the challenges faced by forecasters as well as strategies for improving return forecasts. We focus on U.S. equity premium forecastability and illustrate key issues via an empirical application based on updated data. Some studies...

Academic research has extensively used macroeconomic variables to forecast the U.S. equity risk premium, with little attention paid to the technical indicators widely employed by practitioners. Our paper fills this gap by comparing the forecasting ability of technical indicators with that of...

Academic research relies extensively on macroeconomic variables to forecast the U.S. equity risk premium, with relatively little attention paid to the technical indicators widely employed by practitioners. Our paper fills this gap by comparing the forecasting ability of technical indicators with...

Academics and practitioners have long recognized the importance of a firm’s industry membership in explaining its financial performance. Yet, contrary to conventional wisdom, recent research shows that industry-specific profitability forecasting models are not better than economy-wide models....

This paper constructs individual-specific density forecasts for a panel of firms or households using a dynamic linear model with common and heterogeneous coefficients and cross-sectional heteroskedasticity. The panel considered in this paper features large cross-sectional dimension (N) but short...