Finding Trading Patterns in Stock Market Data

Keith Nesbitt, Stephen Barrass

Research output: Contribution to journalArticlepeer-review

49 Citations (Scopus)
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This article describes our design and evaluation of a multisensory human perceptual tool for the real-world task domain of stock market trading. The tool is complementary in that it displays different information to different senses - our design incorporates both a 3D visual and a 2D sound display. The results of evaluating the tool in a formal experiment are complex. The data mined in this case study is bid-and-ask data - also called depth-of-market data - from the Australian Stock Exchange. Our visual-auditory display is the bid-ask-land-scape, which we developed over much iteration with the close collaboration of an expert in the stock market domain. From this domain's perspective, the project's principal goal was to develop a tool to help traders uncover new trading patterns in depth-of-market data. In this article, we not only describe the design of the bid-ask-landscape but also report on a formal evaluation of this visual-auditory display. We tested nonexperts on their ability to use the tool to predict the future direction of stock prices
Original languageEnglish
Pages (from-to)45-55
Number of pages11
JournalIEEE Computer Graphics and Applications
Issue number5
Publication statusPublished - 2004
Externally publishedYes


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