We analyze output growth risk with respect to financial conditions across U.S. manufacturing industries. Using a multi-level quantile regression approach, we find strong heterogeneity in growth risk, particularly between the more vulnerable durable goods sector and the more resilient nondurable...

This paper addresses the poor performance of the Expectation-Maximization (EM) algorithm in the estimation of low-noise dynamic factor models, commonly used in macroeconomic forecasting and nowcasting. We show analytically and in Monte Carlo simulations how the EM algorithm stagnates in a...

We study why a majority of trades still happen during the pit hours, i.e. when the trading pit is open, even after the pit ceased to be a liquid and informative venue. We investigate the case of 30-year U.S. Treasury futures using a ten-years-long intraday data set which contains the...

We study the impact of private information on volatility in financial markets. We develop a comprehensive framework to investigate this link while controlling for the effects of both public information (such as macroeconomic news releases) and private information on prices and the effects of...

We model the impact of financial conditions on asset market volatility and correlation. We propose extensions of (factor-)GARCH models for volatility and DCC models for correlation that allow for including indexes that measure financial conditions. In our empirical application we consider daily...

Many economic studies on inflation forecasting have found favorable results when inflation is modeled as a stationary process around a slowly time-varying trend. In contrast, the existing studies on interest rate forecasting either treat yields as being stationary, without any shifting...

For many assets, trading is fragmented across multiple exchanges. Price discovery measures summarize the informativeness of trading on each venue for discovering the asset's true underlying value. We explore intraday variation in price discovery using a structural model with time-varying...

We investigate the added value of combining density forecasts for asset return prediction in a specific region of support. We develop a new technique that takes into account model uncertainty by assigning weights to individual predictive densities using a scoring rule based on the censored...

This paper considers the uncertainty associated with upcoming Federal Open Market Committee (FOMC) announcements and the extent to which the market begins to set up for such announcements well before they actually occur. We demonstrate that markets set up well in advance of known announcement...

We study the relationship between order flow and volatility. To this end we develop a comprehensive framework that simultaneously controls for the effects of macro announcements and order flow on prices and the effect of macro announcements on volatility. Using high-frequency 30-year U.S....