DocumentCode
3351534
Title
Visual market sector analysis for financial time series data
Author
Ziegler, Hartmut ; Jenny, Marco ; Gruse, Tino ; Keim, Daniel A.
Author_Institution
Univ. of Konstanz, Konstanz, Germany
fYear
2010
fDate
25-26 Oct. 2010
Firstpage
83
Lastpage
90
Abstract
The massive amount of financial time series data that originates from the stock market generates large amounts of complex data of high interest. However, adequate solutions that can effectively handle the information in order to gain insight and to understand the market mechanisms are rare. In this paper, we present two techniques and applications that enable the user to interactively analyze large amounts of time series data in real-time in order to get insight into the development of assets, market sectors, countries, and the financial market as a whole. The first technique allows users to quickly analyze combinations of single assets, market sectors as well as countries, compare them to each other, and to visually discover the periods of time where market sectors and countries get into turbulence. The second application clusters a selection of large amounts of financial time series data according to their similarity, and analyzes the distribution of the assets among market sectors. This allows users to identify the characteristic graphs which are representative for the development of a particular market sector, and also to identify the assets which behave considerably differently compared to other assets in the same sector. Both applications allow the user to perform investigative exploration techniques and interactive visual analysis in real-time.
Keywords
data analysis; data visualisation; financial data processing; pattern clustering; stock markets; time series; user interfaces; characteristic graphs; data cluster; interactive visual analysis; market mechanism; market sector; stock market; time series data; Clustering algorithms; Data visualization; Pixel; Real time systems; Stock markets; Time series analysis; Visualization; Explorative Analysis; Financial Information Visualization; Time Series Clustering; Time Series Data; Visual Analytics;
fLanguage
English
Publisher
ieee
Conference_Titel
Visual Analytics Science and Technology (VAST), 2010 IEEE Symposium on
Conference_Location
Salt Lake City, UT
Print_ISBN
978-1-4244-9488-0
Electronic_ISBN
978-1-4244-9487-3
Type
conf
DOI
10.1109/VAST.2010.5652530
Filename
5652530
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