In economic news, journalists and analysts give objective information on recent events while also discussing the implications of events in an implicitly subjective manner. We investigate automated text mining approaches for extracting structured factual data alongside subjective information from Dutch and English economic news reporting. Event extraction obtains detailed information about economic events such as acquisitions, CEO changes, or product launches: it summarizes an event and tells us who is involved in what event with which event properties. Aspect-based sentiment analysis gives us an overview about what negative or positive opinion is expressed about what part of an event or entity.