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F I N A L C A L L F O R P A P E R S
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Journal of Computational Intelligence in Finance
Final Call for Papers
Special Issue on
"Complexity and Dimensionality Reduction in Finance"
The Journal of Computational Intelligence in Finance, a peer-reviewed
technical journal, published by Finance & Technology Publishing, is
seeking papers for review and publication in 1998 on "Complexity and
Dimensionality Reduction in Finance".
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. It provides the
international forum for the convergence of the new multi-disciplined
field of computational intelligence in finance.
Papers published in the Journal are eligible for entry in an Annual
Essay Award Contest. The Editorial Advisory Board of the Journal
selects the best paper for which a cash award is presented 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 - USA
Neil Burgess, London Business School - UK
Oscar Castillo, UABC University - USA
Jerry Connor, London Business School - UK
Eric de Bodt, Universite Catholique de Louvain - France
James F. Derry, Mgmt. Engineering Productivity Systems - USA
Athanasios Episcopos, National Bank of Greece
Andrew Flitman, Monash University - Australia
Susan Garavaglia, Dun and Bradstreet - USA
Ramo Gencay, University of Windsor - Canada
Sabyasachi Ghoshray, Florida International University - USA
Lee Giles, NEC Research Institute - USA
Christian Haefke, University of California at San Diego - USA
Ypke Hiemstra, Vrije Universiteit - The Netherlands
Yuval Lirov, Lehman Brothers - USA
Ralph Neuneier, Siemens AG Corporate Research Center - Germany
Zoran Obradovic, Washington State University - USA
Marimuthu Palaniswami, University of Melbourne - Australia
Carlos E. Pedreira, Catholic University, Rio - Brazil
David B. Skalak, IBM, New York - USA
Stephen Slade, Stern Business School, New York University - USA
Leon Sterling, University of Melbourne - Australia
Manoel F. Tenorio, Purdue University - USA
Halbert White, University of California at San Diego - USA
Lei Xu, The Chinese University of Hong Kong
SPECIAL TOPIC
Complexity and Dimensionality Reduction in Finance
PUBLICATION DATE
May 1998
PAPER SUBMISSION DEADLINE
December 15, 1997
SCOPE
In the broad sense, all intelligent perception and data
understanding seeks to reduce redundancy in data and, thus,
its complexity and dimensionality. This special issue of JCIF
focuses on a narrower scope: the theories, methods and
algorithms for mapping financial data from its original
representation into another form with reduced complexity and/or
dimensionality that appear beneficial to financial applications.
Of particular interest are techniques which can serve as
preprocessors to data-driven models and data mining technologies,
including those which address or utilize one or more of the
following: complexity and dimensionality characterization,
identification and analysis; data compression; feature extraction
techniques; regularity discovery; inductive reasoning; randomness
tests; algorithmic entropy; informational distance; minimal
description length; adaptive and nonlinear PCA and other alternatives
to standard forms of linear PCA; finite sequence statistics; variable
combining methods; data filtering; categorical versus continuously-
valued inputs; high-dimensional visualization analysis; and input
space reduction techniques.
MOTIVATION
In finance, we inevitably encounter an unavoidable dilemma: an
interest in collecting and utilizing as much data as possible in its
original form so that potentially useful information is not lost,
although this often results in data with high complexity and/or
dimensionality that increases costs and reduces performance. Despite
this, the notion that more input data is better persists.
The need for managing complexity and dimensionality arises from eroding
profit margins, diminishing arbitrage opportunities, lowered barriers to
entry, increasingly segmented markets, increased costs, and, in general,
the reduced performance (e.g., generalization ability) of tools applied,
such as data-driven models and data mining technologies. Thus, the topic
of this special issue represents very important areas of applied research
across multiple disciplines relevant to computational intelligence in
finance.
DATA REFERENCES
Authors may use any financial datasets of interest. For possible existing
datasets, see the following Web pages:
http://ourworld.compuserve.com/homepages/ftpub/dd.htm
http://ourworld.compuserve.com/homepages/ftpub/other.htm
http://www.cs.colorado.edu/~andreas/Time-Series/Data/Exchange.Rates.Daily
BOOK/ARTICLE REFERENCES
Abarbanel, Henry D.I. [1996] Analysis of Observed Chaotic Data,
Springer-Verlag, New York.
Bishop, Christopher M. [1995] Neural Networks for Pattern Recognition,
Oxford University Press, Oxford and New York.
Calude, C. [1994] Information and Randomness: An Algorithmic Perspective,
Springer-Verlag, New York.
Devijver, P.A. and J. Kittler [1982] Pattern Recognition: A statistical
approach, Prentice-Hall.
Frison, Ted W. [1995] "Chaos and Prediction Horizons in Silver Futures
Trading," NeuroVest Journal, Vol.3, No.3, pp.22-29.
Gershenfeld, N.A. and A.S. Weigend [1994] "The Future of Time Series:
Learning and Understanding," in Time Series Prediction (A.S. Weigend and
N.A. Gershenfeld, editors), Addison-Wesley, Reading, MA, pp.1-70.
Keuzenkamp, H.A. and M. McAleer [1995] "Simplicity, Scientific Inference
and Econometric Modelling," The Economic Journal, Vol.105, pp.1-21.
Kohonen, Teuvo [1995] Self-Organizing Maps, Springer-Verlag, Berlin.
Li, Ming and Paul Vitanyi [1997] An Introduction to Kolmogorov Complexity
and Its Applications, Second Edition, Springer-Verlag, New York.
Linial, N., Mansour, Y. and R.L. Rivest [1991] "Results on Learnability
and the Vapnik-Chervonenkis Dimension," Information and Computation,
90:pp.33-49.
Oja, E. [1983] Subspace Methods of Pattern Recognition, Research Studies
Press, Letchworth, UK.
Samon, John W., Jr. [1969] "A Nonlinear Mapping for Data Structure
Analysis," IEEE Trans. on Computers, Vol.C-18, No.5, May.
Staiger, L. [1993] "Kolmogorov Complexity and Hausdorff Dimension,"
and Computation, 120(2):pp.159-194.
Storer, D. [1988] Data Compression: Method and Theory, Computer Science
Press, New York.
Tenorio, M.F., Pedreira, C.E. and N.M. Roehl [1997] "The Cotton Time Series:
A Study of the Competition Series Behavior and Statistics," In Nonlinear
Financial Forecasting: Proceedings of the First INFFC (R.B. Caldwell,
editor), Finance & Technology Publishing, Haymarket, VA, pp.23-48.
Tukey, John W. [1977] Exploratory Data Analysis, Addison-Wesley, Mass.
Van Bussel, Joroen and Leo P.J. Veelenturf [1997] "Company Viability
Prediction using Neural Networks with Sparse Data," J. of Computational
Intelligence in Finance, Vol.5, No.4, pp.5-13.
Watanabe, O. (editor) [1992] Kolmogorov Complexity and Computational
Complexity, Spinger-Verlag, New York.
Warwick, Keven and Miroslav Karny (editors) [1997] Computer-Intensive
Methods in Control and Signal Processing: The Curse of Dimensionality,
Birkhauser, Boston.
Zurek, W.H. (editor) [1991] Complexity, Entropy and the Physics of
Information, Addison-Wesley, Reading, MA.
ABSTRACTS
Submit 150 to 300 word abstract including full name(s) and
affiliation(s) of the author(s), complete mailing address,
email address and telephone numbers of all authors. Authors
should provide a brief biographic sketch of themselves. Send
to either of the postal or email addresses below:
Post:
Editors
JCIF
P.O. Box 764
Haymarket, VA 20168
USA
E-mail:
ftpub(a)compuserve.com
PAPERS
Submit three copies of each paper. Papers should be double-
spaced, single-sided. 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, email 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 5000 words in length,
containing no more than about 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 preferred media format is IBM PC 3.5", 1.44MB.
The preferred file format is Word 6/95/97 for Windows 3.1/95.
Other acceptable software files (in the IBM PC format) are the following:
Word/DOS 3.0 or later
Word/Mac 4.0 or later
Word/Win 2.0 through 7
WordPerfect 5.1 or later (for DOS or Windows 3.1/95).
Any standard ASCII text file format using the preferred
media format, including bracketed notations for
the locations of symbols, equations or other
non-ASCII characters.
Tex and LaTex may be used for the development and
generation of the hardcopy version of the
paper, provided that a softcopy version is also
submitted in any standard ASCII text file
format using the preferred media format,
including bracketed notations for citations and
for the locations of symbols, equations or
other non-ASCII characters.
GRAPHICS
The preferred graphics format is a Windows compatible format
(.pcx, .bmp, .wmf). For other graphics formats, submit high-quality,
camera-ready hardcopy.
TEXT CITATIONS AND REFERENCES
Papers should be limited to about 15 references. Encouraged are
references to: (a) peer-reviewed journals and (b) books.
Text citations must use the following format: last name(s) of
author(s), publication date and suffix (as necessary) in
brackets. Example:
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: 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 to the following postal address:
Editors
JCIF
P.O. Box 764
Haymarket, VA 20168
USA
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