A Functional Framework for Evaluating Financial Visualization Products

Development and Application to the Design of a Custom Visual Analytics Solution for a Boutique Asset Management Firm
  • Thomas Luan DangEmail author
  • Victoria L. Lemieux


In this study, we aim to understand and bridge the gap between visual analytics (VA) research and deployment in imperfect conditions to solve multilayered, often vaguely defined, problems in the real world. We further narrow the scope to analysis problems in finance, with a focus on investment portfolio analysis. The goal of this project is to create a functional evaluation framework of VA techniques with regard to investment portfolio analysis problems, as well as a table of existing products that are capable of supporting problems. With a functional evaluation framework and a table of off-the-shelf solutions, more effective and theoretically grounded cost-benefit analysis can be performed to justify and plan applications of VA in financial organizations. We then apply this functional evaluation framework in a case study of a fixed-income investment management company. In this case study, we systematically identify the areas for improvement in the analytic process of the company and isolate the areas that could be improved with VA. We then map these detailed problem definitions to VA techniques in order to find the optimal visualizations of the data. Finally, we implement a solution for the company by building upon one of the free toolkits that we have evaluated in order to achieve all the analytic goals with the least amount of time and expenses.


Visual Analysis Interaction Technique Financial Analyst Requirement Elicitation Line Chart 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors would like to acknowledge the financial support of the Boeing Company in making this research possible. The authors would also like to thank finance students QianQian Yu and Yao Shen for their assistance with this research. Research work carried out by Thomas Dang was in partial fulfillment of the requirements for a M.Sc. in Computer Science at the University of British Columbia under the supervision of Dr. Victoria Lemieux and Dr. Ronald Rensink, and a fuller account may be found in his thesis.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.University of British ColumbiaVancouverCanada

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