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Journal of Computational Intelligence in Finance

Final Call for Papers

Special Issue on

"Financial News Analysis using Distributed Data Mining"

The Journal of Computational Intelligence in Finance, a peer-reviewed technical journal, published by Finance & Technology Publishing, is seeking papers for review and publication on "Financial News Analysis using Distributed Data Mining".

The Journal of Computational Intelligence in Finance publishes applied research and practical applications of high quality that are based on sound theoretical, empirical or quantitative analysis. For practitioners and applied researchers, JCIF serves as the journal of record on "the application of advanced computational technologies and analytical techniques for financial modeling, investing and trading, and risk management."

Papers published in JCIF are eligible for the "Distinguished Essay on Computational Intelligence in Finance" award, which is selected by the Editorial Board each year.

EDITORIAL BOARD

Randall B. Caldwell, Editor-in-Chief

Emilio Barucci - University of Florence, Italy Richard J. Bauer, Jr. - St. Mary's University, Texas Neil Burgess - London Business School Oscar Castillo - UABC University, California Jerry Connor - London Business School Eric de Bodt - Universite Catholique de Louvain, France James F. Derry - Mgmt. Engineering Productivity Systems, Ohio Athanasios Episcopos - National Bank of Greece Andrew Flitman - Monash University, Australia Susan Garavaglia - Dun and Bradstreet, New Jersey Ramo Gencay - University of Windsor, Canada Sabyasachi Ghoshray - Florida International University Lee Giles - NEC Research Institute, New Jersey Christian Haefke - University of California at San Diego Ypke Hiemstra - Vrije Universiteit, The Netherlands Jason Kingdon - Searchspace Limited, University College London Ralph Neuneier - Siemens AG Corporate Research Center, Germany Zoran Obradovic - Washington State University Marimuthu Palaniswami - University of Melbourne Carlos E. Pedreira - Catholic University, Rio Stuart H. Rubin - Central Michigan University David B. Skalak - IBM, New York Leon Sterling - University of Melbourne Manoel F. Tenorio - Purdue University, Indiana Halbert White - University of California at San Diego Lei Xu - The Chinese University of Hong Kong

SPECIAL TOPIC

Financial News Analysis using Distributed Data Mining

PAPERS DUE September 15, 1998

ACCEPTANCE NOTIFICATION November 30, 1998

FINAL REVISED MANUSCRIPTS DUE January 15, 1999

PUBLICATION DATE March 1999

GUEST EDITORS Zoran Obradovic Stuart H. Rubin Associate Professor Associate Professor Elec. Eng. & Comp. Sci. Dept. of Comp. Sci. Washington State University Central Michigan University Pullman, WA 99164-2752, USA Mt. Pleasant, MI 48859, USA zoran@eecs.wsu.edu rubin@cps.cmich.edu

FOR THE LATEST AND MOST COMPLETE INFORMATION ON THIS CALL, SEE:

http://ourworld.compuserve.com/homepages/ftpub/call.htm

MOTIVATION

Recent technological developments, the rapid growth of the World Wide Web, and maturing corporate intranet structures have led to the rapid dissemination of huge amounts of financial news and information (newspaper articles, financial services information, corporate publications, stock exchange news, peer-reviewed financial journal articles, etc.). However, cost and time constraints prohibit an exhaustive search through or download of all potentially relevant financial news and information available on the Internet, for later analysis and processing. One possible solution is to distribute information sampling over a large number of locations in order to classify local data, construct a pool of relevant information, and generate useful rules that might be further analyzed or processed at a central location. This requires intelligent and dynamic domain decomposition, as well as flexible software agents for symbolic information processing.

SCOPE

All papers submitted must focus on the data mining of financial news and information, and on applications of interest to financial analysis or decision-making, investing or trading. Of particular interest are algorithms and techniques that both incorporate computational intelligence and are unique or especially relevant to financial tasks. Authors are invited to submit papers on the design of automated, scalable, distributed knowledge discovery systems for financial information mining on the Internet, to address issues related to:

- search strategies - knowledge representation - reasoning mechanisms - learning algorithms

Suggested topics include but are not limited to the following:

- intelligent software agent structures - sampling strategies for mining the World Wide Web - distributed search algorithms for mining financial news - collaborative and heuristic search methods - statistical text mining - incremental knowledge discovery methods - financial news and information quality - dynamic domain decomposition - expert and decision-based strategies - knowledge representation issues - knowledge-base design and segmentation - communications and query issues - Knowledge Interchange Format (KIF) - Knowledge Query and Manipulation Language (KQML) - semantic nets and frames - combining natural language processing and statistical text mining - algorithms for organizing, filtering and summarizing textual information - state space methods and issues - novel learning and reasoning algorithms

ABSTRACTS

Submit 150 to 300 word abstract including full name(s) and affiliation(s) of the author(s), complete mailing address and telephone numbers of all authors. Authors should provide a brief biographic sketch of themselves. Send abstracts to:

Post: JCIF, P.O. Box 764, Haymarket, VA 20168 USA E-mail: ftpub@compuserve.com Fax: 1-703-753-2634

PAPERS

Papers must not have been previously published or currently submitted for publication elsewhere. All material must be provided in the English language.

Submit three copies of each paper. Papers must be formatted for 8.5x11-inch page format. Authors should provide a brief biographic sketch of themselves. Each copy submitted should include a page that contains the title of the paper, the full name(s) and affiliation(s) of the author(s), complete mailing address and telephone numbers of all authors, and a 150 to 300 word abstract. The Journal reserves the right to edit all material to meet space requirements and to make grammatical and typographical corrections.

The final text should be 4000 to 6000 words in length, contain no more than 15 references, and be provided as follows: (1) Hardcopy: printed and double-spaced, with notations for the location of graphics, mathematical equations, given thereon, as necessary, (2) Softcopy: The REQUIRED MEDIA FORMAT is IBM PC 3.5", 1.44MB. The PREFERRED FILE FORMAT is Word for Windows 3.1/95 (Word 6/7/97). Other acceptable software file formats are the following: Tex and LaTex using the required media format (Scientific Workplace 3.0 preferred, use standard features)

The PREFERRED GRAPHICS formats are Windows 3.1/95 (*.bmp,*.wmf,*.eps). For other graphics formats, submit high-quality, camera-ready hardcopy, or make an inquiry.

Include pseudo-code or source code in separate figures (listings). Extensive code listings may be published on the Web site because of space limitations in the journal.

Text citations must use the following format: last name(s) of author(s), publication date and suffix (as necessary) in brackets. Example: (a) direct reference: Watkins and McCoy [1993a] (b) indirect reference: [Watkins and McCoy 1993a]

References must be listed alphabetically by the last name of the first author according to the following formats: Journal Article: authors' names, publication date and suffix (as necessary) in brackets, article title (in double quotations), periodical title (in italics), volume and number, pages cited. Book: authors' names, publication date and suffix (as necessary) in brackets, book title (in italics), publisher, publisher location, pages cited. Chapter in Book/Proceedings: authors' names, publication date and suffix (as necessary) in brackets, chapter title (in double quotations), editors' names, book title (in italics), publisher, location, pages cited.

Send all manuscripts by Post to:

Editors, JCIF, P.O. Box 764, Haymarket, VA 20168 USA

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