Share Email Print
cover

Proceedings Paper

Tile-based parallel coordinates and its application in financial visualization
Author(s): Jamal Alsakran; Ye Zhao; Xinlei Zhao
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Parallel coordinates technique has been widely used in information visualization applications and it has achieved great success in visualizing multivariate data and perceiving their trends. Nevertheless, visual clutter usually weakens or even diminishes its ability when the data size increases. In this paper, we first propose a tile-based parallel coordinates, where the plotting area is divided into rectangular tiles. Each tile stores an intersection density that counts the total number of polylines intersecting with that tile. Consequently, the intersection density is mapped to optical attributes, such as color and opacity, by interactive transfer functions. The method visualizes the polylines efficiently and informatively in accordance with the density distribution, and thus, reduces visual cluttering and promotes knowledge discovery. The interactivity of our method allows the user to instantaneously manipulate the tiles distribution and the transfer functions. Specifically, the classic parallel coordinates rendering is a special case of our method when each tile represents only one pixel. A case study on a real world data set, U.S. stock mutual fund data of year 2006, is presented to show the capability of our method in visually analyzing financial data. The presented visual analysis is conducted by an expert in the domain of finance. Our method gains the support from professionals in the finance field, they embrace it as a potential investment analysis tool for mutual fund managers, financial planners, and investors.

Paper Details

Date Published: 18 January 2010
PDF: 12 pages
Proc. SPIE 7530, Visualization and Data Analysis 2010, 753003 (18 January 2010); doi: 10.1117/12.838819
Show Author Affiliations
Jamal Alsakran, Kent State Univ. (United States)
Ye Zhao, Kent State Univ. (United States)
Xinlei Zhao, Kent State Univ. (United States)
Office of Comptroller of the Currency (United States)


Published in SPIE Proceedings Vol. 7530:
Visualization and Data Analysis 2010
Jinah Park; Ming C. Hao; Pak Chung Wong; Chaomei Chen, Editor(s)

© SPIE. Terms of Use
Back to Top