This paper sheds new light on herding of institutional investors by using a unique database that identifies every transaction made by financial institutions in the German stock market. First, the analysis reveals that herding behavior of institutions occurs daily. Second, replication of the...

This paper sheds new light on herding of institutional investors by using a unique and superior database that identifies every transaction of financial institutions. First, the analysis reveals herding behavior of institutions. Second, the replica- tion of the analysis with low-frequent and...

This paper employs a new and comprehensive data set to investigate short-term herding behavior of institutional investors. Using data of all transactions made by financial institutions in the German stock market, we show that herding behavior occurs on a daily basis. However, in contrast to...

This paper employs numerical simulations of the Park and Sabourian (2011) herd model to derive new theory-based predictions for how information risk and market stress influence aggregate herding intensity. We test these predictions empirically using a comprehensive data set of highfrequency and...

Due to data limitations and the absence of testable, model-based predictions, theory and evidence on herd behavior are only loosely connected. This paper contributes towards closing this gap in the herding literature. We use numerical simulations of a herd model to derive new, theory-based...

Herd behavior is often viewed as a significant threat for the stability and effciency of financial markets. This paper sheds new light on the relevance of herd behavior for observed correlation of trades. We introduce numerical simulations of a herd model to derive theory-guided predictions...

This paper sheds new light on the impact of information risk and market stress on herding of institutional traders from both, a theoretical and an empirical perspective. Using numerical simulations of a herd model, we show that buy and sell herding intensity should increase with information...