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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@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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