After showing that the distribution of the S&P 500's distortion, i.e. the log difference between its real stock market index and its real fundamental value, is bimodal, we demonstrate that agentbased financial market models may explain this puzzling observation. Within these models, speculators...

Monetary policy shocks have a large impact on stock prices during narrow time windows centered around press releases by the FOMC. We use spatial autoregressions to decompose the overall effect of monetary policy shocks into a direct effect and a network effect. We attribute 50 to 85 percent of...

This paper examines return predictability when the investor is uncertain about the right state variables. A novel feature of the model averaging approach used in this paper is to account for finite-sample bias of the coefficients in the predictive regressions. Drawing on an extensive...

This article contributes to the literature on macroeconomic announcements and their impact on asset prices by investigating how the 15-second Xetra DAX returns reflect the monthly announcements of the two best known business cycle forecasts for Germany, i.e. the ifo Business Climate Index and...

Although the effects of economic news announcements on asset prices are well established, theserelationships are unlikely to be stable. This paper documents the time variation in the responses of yield curves and exchange rates using high-frequency data from January 2000 through August 2011....

We propose a local adaptive multiplicative error model (MEM) accommodating timevarying parameters. MEM parameters are adaptively estimated based on a sequential testing procedure. A data-driven optimal length of local windows is selected, yielding adaptive forecasts at each point in time....

With the recent availability of high-frequency Financial data the long range dependence of volatility regained researchers' interest and has lead to the consideration of long memory models for realized volatility. The long range diagnosis of volatility, however, is usually stated for long sample...

We study the impact of the arrival of macroeconomic news on the informational and noise-driven components in high-frequency quote processes and their conditional variances. Bid and ask returns are decomposed into a common ('efficient return') factor and two market-side-specific components...

Bayesian learning provides the core concept of processing noisy information. In standard Bayesian frameworks, assessing the price impact of information requires perfect knowledge of news' precision. In practice, however, precision is rarely dis- closed. Therefore, we extend standard Bayesian...

Bayesian learning provides a core concept of information processing in financial markets. Typically it is assumed that market participants perfectly know the quality of released news. However, in practice, news' precision is rarely disclosed. Therefore, we extend standard Bayesian learning...