A Survey on Visual Analysis Approaches for Financial Data

TLDR

Financial decision‑making increasingly relies on visual analytics to manage large, diverse, and complex data, driving extensive research and collaboration with domain experts. This survey systematically reviews task requirements and existing visual analytics systems for financial data. We conduct a comprehensive survey, categorizing financial visual analytics systems by data source, automated techniques, visualization, interaction, and evaluation, using established taxonomies. Task requirements from domain‑expert interviews are provided to guide future system design.

Abstract

Abstract Market participants and businesses have made tremendous efforts to make the best decisions in a timely manner under varying economic and business circumstances. As such, decision‐making processes based on Financial data have been a popular topic in industries. However, analyzing Financial data is a non‐trivial task due to large volume, diversity and complexity, and this has led to rapid research and development of visualizations and visual analytics systems for Financial data exploration. Often, the development of such systems requires researchers to collaborate with Financial domain experts to better extract requirements and challenges in their tasks. Work to systematically study and gather the task requirements and to acquire an overview of existing visualizations and visual analytics systems that have been applied in Financial domains with respect to real‐world data sets has not been completed. To this end, we perform a comprehensive survey of visualizations and visual analytics. In this work, we categorize Financial systems in terms of data sources, applied automated techniques, visualization techniques, interaction, and evaluation methods. For the categorization and characterization, we utilize existing taxonomies of visualization and interaction. In addition, we present task requirements extracted from interviews with domain experts in order to help researchers design better systems with detailed goals.