Relevance Driven Visualization of Financial Performance Measures

Visual data analysis has received a lot of research interest in recent years, and a wide variety of new visualization techniques and applications have been developed to improve insight into the various application domains. In financial data analysis, however, analysts still primarily rely on a set of statistical performance parameters in combination with traditional line charts in order to evaluate assets and to make decisions, and information visualization is only very slowly entering this important domain. In this paper, we analyze some of the standard statistical measures for technical financial data analysis and demonstrate cases where they produce insufficient and misleading results that do not reflect the real performance of an asset. We propose a technique for visualizing financial time series data that eliminates these inadequacies, offering a complete view on the real performance of an asset. The technique is enhanced by relevance and weighting functions according to the user...

• Type: Conference
• Year: 2007
• Where: VISSYM
• Authors: Hartmut Ziegler, Tilo Nietzschmann, Daniel A. Keim
• Keywords: Data Analysis, Financial Data Analysis, VISSYM 2007, Visual Data Analysis, Visualization