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...

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...

This paper presents a Heterogeneous Agent Model of a financial market with chartist and fundamentalist traders that exhibit bounded rationality and short-term thinking to explain the effect of under and overreaction to news. The existence of the Market Maker's finite price adjustment speed leads...

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...

Residual income valuation is based on the assumption that the clean surplus relation holds. As pointed out by Ohlson (2000), among others, the standard clean surplus relation is frequently violated. Moreover, standard residual income valuation models rest on the implicit assumption that future...

We study the trading dynamics in an asset market where the quality of assets is private information of the owner and finding a counterparty takes time. When trading of a financial asset ceases in equilibrium as a response to an adverse shock to asset quality, a large player can resurrect the...

We consider a carbon emissions tax announced today, but implemented after a known time-lag. Before implementation, the announcement induces higher emissions than without intervention. In welfare terms, this adverse announcement effect could more than outweigh the gain after tax implementation....

We propose a new approach to measuring the effect of unobservable private information or beliefs on volatility. Using high-frequency intraday data, we estimate the volatility effect of a well identified shock on the volatility of the stock returns of large European banks as a function of the...

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...

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...