A rapidly growing literature has documented important improvements in volatility measurement and forecasting performance through the use of realized volatilities constructed from high-frequency returns coupled with relatively simple reduced-form time series modeling procedures. Building on...

A rapidly growing literature has documented important improvements in volatility measurement and forecasting performance through the use of realized volatilities constructed from high-frequency returns coupled with relatively simple reduced-form time series modeling procedures. Building on...

This paper uses a unique data set from credit files of six leading German banks to provide some empirical insights into their rating systems used to classify corporate borrowers. On the basis of the New Basle Capital Accord, which allows banks to use their internal rating systems to compute...

This paper addresses the open debate about the usefulness of high-frequency (HF) data in large-scale portfolio allocation. Daily covariances are estimated based on HF data of the S&P 500 universe employing a blocked realized kernel estimator. We propose forecasting covariance matrices using a...

We studied information and interaction processes in six lending relationships between a universal bank and medium sized firms. The study is based on the credit files of the respective firms. If no problems occur in these lending relationships, bank monitoring is based mainly on cheap,...

We study to what extent firms spread out their debt maturity dates across time, which we call granularity of corporate debt. We consider the role of debt granularity using a simple model in which a firm's inability to roll over expiring debt causes inefficiencies, such as costly asset sales or...

During the last years the lending business has come under considerable competitive pressure and bank managers often express concern regarding its profitability vis-a-vis other activities. This paper tries to empirically identify factors that are able to explain the financial performance of bank...

We examine intra-day market reactions to news in stock-specific sentiment disclosures. Using pre-processed data from an automated news analytics tool based on linguistic pattern recognition we extract information on the relevance as well as the direction of company-specific news....

We argue for incorporating the financial economics of market microstructure into the financial econometrics of asset return volatility estimation. In particular, we use market microstructure theory to derive the cross-correlation function between latent returns and market microstructure noise,...