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FINANCIAL VISUALIZATION SUPPORT FOR BREAKDOWN ANALYSIS

FINANCIAL VISUALIZATION SUPPORT 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. Domain information.

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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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