Integrating structured and unstructured data in a business-intelligence-system

The recent liberalization of the German energy market has forced the energy industry to develop and install new information systems to support agents on the energy trading floors in their analytical tasks. Besides classical approaches of building a data warehouse giving insight into the time series to understand market and pricing mechanisms, it is crucial to provide a variety of external data from the web. Weather information as well as political news or market rumors are relevant to give the appropriate interpretation to the variables of a volatile energy market. Starting from a multidimensional data model and a collection of buy and sell transactions a data warehouse is built that gives analytical support to the agents. Following the idea of web farming we harvest the web, match the external information sources after a filtering and evaluation process to the data warehouse objects, and present this qualified information on a user interface where market values are correlated with those external sources over the time axis.

Capital Market Implications of Corporate Disclosure: German Evidence

This paper investigates the relationship between annual report disclosure, market liquidity, and capital cost for firms registered on the Deutsche Börse. Disclosure is comprehensively measured using the innovative Artificial Intelligence Measurement of Disclosure (AIMD). Results show that annual report disclosure enhances market liquidity by changing investors’ expectations and inducing portfolio adjustments. Trading frictions are negatively associated with disclosure. The study provides evidence for a capital-costreduction effect of disclosure based on the analysis of investors’ return requirements and market values. Altogether, no evidence is found that the information processing at the German capital market is structurally different from other markets.