Using a unique data set that contains the complete ownership structure of the German stock market, we study the momentum and contrarian trading of different investor groups. Foreign investors and financial institutions, and especially mutual funds, are momentum traders, whereas private...

We consider an optimal liquidation model in which an investor is required to execute meta-orders during intraday trading periods, and his trading activity triggers child orders and endogenously affects future order flow, both instantaneously and permanently. Under the assumptions of risk...

In this paper we empirically analyze the permanent price impact of trades by investigating the relation between unexpected net order flow and price changes. We use intraday data on German index futures. Our analysis based on a neural network model suggests that the assumption of a linear impact...

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...

Using a unique data set on German banks' sector specific loan exposures to the real economy and the corresponding write-offs and write-downs, we examine the impact of loan portfolio sector concentration on credit risk. By controlling for common risk factors, we separate the bank-specific...

Extant literature consistently documents that investors tilt their domestic equity portfolios towards regionally close stocks (local bias). We hypothesize that individual investors’ local bias is not limited to the domestic sphere but instead also determines their international investment...

This paper examines the international credit portfolios of German banks. We construct a bank-country panel from a unique dataset for a representative set of countries and ask why banks leave diversification opportunities unexploited in some countries. Controlling for bank heterogeneity, we...