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FINANCIAL VISUALIZATION SUPPORT FOR BREAKDOWN ANALYSIS

A method to visualize multiple foci polyarchies by breaking down visualization based on causalities, utilizing DuPont analysis for company performance evaluation. Explore the challenges, solutions, and future work in this innovative approach.

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FINANCIAL VISUALIZATION SUPPORT FOR BREAKDOWN ANALYSIS

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  1. FINANCIAL VISUALIZATIONSUPPORT FOR BREAKDOWN ANALYSIS A method to visualize multiple foci polyarchies by successive breaking down of visualization based on its causalities Sandeep Prabhakar Muthukumar Thirunavukkarasu Anusha Dandapani Ganesh Panchanathan

  2. Domain information • DuPont analysis • DuPont analysis is a method of analyzing the performance of a company by means of various Ratios • E.g. Return on Equity, Net Income, Total Equity • The data • The data consisted of the annual statements of 100 companies for the last 20 years. Each company had 180 data items. • These data items are used in calculating DuPont Ratios

  3. What is a polyarchy? Polyarchy = multiple hierarchies

  4. Different aspects to breakdown • Breakdown based on attributes • Decomposition based on predefined formulae • E.g. Frequency = wavelength / c • Frequency = R(wavelength, c) • Breakdown based on values • Decomposition and grouping based on distinct values • State = R(Virginia, California, ….)

  5. What are the problems? • Hierarchy + Visualization at each node? • Multiple Foci • I want to see B and C siblings side by side • B and C are in different hierarchies • I want to see A (ancestor) and J (a deep descendant) side by side • <A,J> not in each other’s context • Top – Down breakdown of data sets • I want to see which sub division affects the superset causality

  6. Our solution – Breakdown Visualization

  7. Navigating Hierarchies

  8. Interactions Supported • Fix and move technique • Brushing and linking • Details on demand • Drill down • Comparison of two nodes not in each other’s context • Visualization type can be selected that best suits the data • Implicit representation of hierarchy

  9. System Diagram MS SQL database queried with JDBC

  10. Future Work • Allow a knowledgeable user to dynamically modify and store new hierarchies • Implicit hierarchy may not be suitable in all cases

  11. Results • HCI metrics: • Scale • Tends to infinity as user selects the visualizations to be currently seen • User performance • Every click accomplishes work! • Learning time • Good • Error rate • Going down the wrong path problems? Yes, Easy to recover from it • Retention time ??? • User satisfaction ???

  12. Acknowledgements Nathan Conklin (bowls for independent study students) Dr. Chris North Dr. Raman Kumar for data access

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