Title
A Computational Implementation Of Stock Charting: Abrupt Volume Increase As Signal For Movement In New York Stock Exchange Composite Index
Keywords
Financial decision support; Market efficiency; Pattern recognition; Stock market forecasting; Technical analysis
Abstract
In this case study in knowledge engineering, data mining, and behavioral finance, we implement a variation of the bull flag stock charting heuristic using a template matching technique from pattern recognition to identify abrupt increases in volume in the New York Stock Exchange Composite Index. Such volume increases are found to signal subsequent increases in price under certain conditions during the period from 1981 to 1999, the Great Bull Market. A 120-trading-day history of price and volume is used to forecast price movement at horizons from 20 to 100 trading days. © 2003 Elsevier B.V. All rights reserved.
Publication Date
9-1-2004
Publication Title
Decision Support Systems
Volume
37
Issue
4
Number of Pages
515-530
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1016/S0167-9236(03)00084-8
Copyright Status
Unknown
Socpus ID
2442658129 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/2442658129
STARS Citation
Leigh, William; Modani, Naval; and Hightower, Ross, "A Computational Implementation Of Stock Charting: Abrupt Volume Increase As Signal For Movement In New York Stock Exchange Composite Index" (2004). Scopus Export 2000s. 5079.
https://stars.library.ucf.edu/scopus2000/5079