References on Applications of Neural Networks in Finance & Economics

REFERENCES ON APPLICATIONS OF NEURAL NETWORKS IN FINANCE & ECONOMICS

Version 99.1. July 1998. By: Athanasios Episcopos, Ph.D., Roditsa Fthiotidos, 35100, Greece. Copyright © 1995-1999 Athanasios Episcopos

If you want your work to be added in this reference list, or if you know of papers or books with neural nets / finance / economics content, please e-mail your information to OPTIONAL: I would appreciate it if you also send me a complimentary hard copy of your work.

COPYRIGHT & DISCLAIMERS: Copyright © 1995-1998 Athanasios Episcopos. All rights reserved. This document is distributed AS IS and no warranties explicit or implied are attached to it. It can be retrieved from http//

CONTENTS

1) PURPOSE, CONTENT, AND GUIDELINES FOR AUTHORS
2) BOOKS & CHAPTERS IN BOOKS
3) PUBLISHED JOURNAL ARTICLES
4) FORTHCOMING PUBLICATIONS (BOOKS & ARTICLES)
5) CONFERENCE PROCEEDINGS VOLUMES, ARTICLES, REPORTS
6) WORKING PAPERS
7) INTERNET LINKS ON NEURAL NETWORKS, FINANCE & ECONOMICS
8) ACKNOWLEDGMENTS

1) PURPOSE, CONTENT, AND GUIDELINES FOR AUTHORS

These references are intended for the researcher who wants to use artificial neural networks (NN) in finance and economics. The motivation is that, although NN's have been extensively studied, there is little in the form of a comprehensive list of recent references focused specifically on the application of NN's in finance and economics. This document aspires to eventually become such a list and serve as a starting point of research. All sections, including the Working Papers section, will be updated as authors send me their titles. To find the mail address of an author, you may want to try the search engines.

The reader must carefully evaluate the usefulness of the sources sited here. I cannot guarantee that a paper, journal, book, or site will be useful.

The general guidelines for the type of references that should be included here are as follows. Refereed journal articles, books, papers presented in major conference proceedings, working academic papers, and links to academic sites are acceptable. Non refereed journals and articles will be included at the discretion of the list author. Sites affiliated with private firms will be included, provided that they are educationally useful and that they do not contain direct links to pages of commercial character.

New references will be recorded as frequently as possible with minor editing. Contributors: Try to use a Last Name - First Initial - Paper Title - Journal Title - Year - Volume - Pages scheme or something similar to make it easy for me to record these in the file. Avoid abbreviations. Thanks.

BACK TO CONTENTS

2) BOOKS & CHAPTERS IN BOOKS

Apte, C. and S.J. Hong [1996] "Predicting Equity Returns from Securities Data," in Advances in Knowledge Discovery and Data Mining, The MIT Press, Cambridge, Mass.

Azoff, M. Neural Network Time Series Forecasting of Financial Markets, John Wiley & Sons, 1994.

Berndt, D. and J. Clifford [1996] "Finding Patterns in Time Series: A Dynmaic Programming Approach," in Advances in Knowledge Discovery and Data Mining, The MIT Press, Cambridge, Mass.

Baestaens, D., Van den Bergh, W.M. and Wood, D.. Neural Network Solutions for Trading in Financial Markets. Financial Times / Pitman Publishing, 1994.

Bose, N.K., and P. Liang, Neural Network Fundamentals with Graphs, Algorithms, and Applications, McGraw-Hill, 1996.

Deco, Gustavo, and Dragan Obradovic, An Information-Theoretic Approach to Neural Computing, Springer Verlag, 1996.

Eyden, Robert Van [1996] The Application of Neural Networks in the Forecasting of Share Prices, Finance & Technology Publishing, Haymarket, VA. ISBN 0-9651332-0-6

Goonatilake, S. and P. Treleaven (Eds.) Intelligent Systems for Finance and Business, John Wiley, 1995.

Hecht-Nielsen, R, Neurocomputing. Reading, MA, Addison-Wesley, 1990.

Hertz, J., Krogh, A. and Palmer, R. Introduction to the Theory of Neural Computation. Redwood City: Addison-Wesley, 1991.

Hagan, Martin, Howard Demuth, and Mark Beale, Neural Network Design, PWS Publishing Company, 1996.

Hiemstra, Y. and C. Haefke (1996), "Two Multilayer Perceptron Training Strategies For Low Frequency S&P500 Prediction", in "Neural Networks in Finance and Investing", R. R. Trippi and E. Turban (eds.) 2nd Edition, Irwin Professional Publishing Co., Burr Ridge, IL, pp. 511-523

Hiemstra, Ypke (1995), "Modeling Structured Nonlinear Knowledge to Predict Stock Market Returns", in Chaos and Nonlinear Dynamics in the Financial Markets, R. R. Trippi (ed.), Irwin Professional Publishing Co., Burr Ridge, IL, pp. 163-175

Johnson, J. and A. Whinston. (eds) Advances in Artificial Intelligence in Economics, Finance, and Management, JAI Press, v. 1, 1994.

Madala H.R., Ivakhnenko A.G. Inductive Learning Algorithms for Complex Systems Modeling, CRC Press Inc., Boca Raton, 1994, p.384.

Masters, T. Practical Neural Network Recipes in C++, Academic Press, San Diego, CA (1993).

Moody J., and J. Utans, "Architecture Selection Strategies for Neural Networks: Application to Corporate Bond Rating Prediction'', in Refenes A.N. (ed.) Neural Networks in the Capital Markets, John Wiley \& Sons, 1994.

Poddig, T. Bankruptcy Prediction: A Comparison with Discriminant Analysis. In Refenes A.N. (ed.) Neural Networks in the Capital Markets, John Wiley \& Sons, 1994.

Powel, M., Radial Basis Functions for Multivariate Interpolation: A Review, in J., Mason, and M. Cox (eds) Algorithms for Approximation. Oxford: Clarendon Press (1987).

Refenes, A.-P., (ed.) Neural Networks in the Capital Markets, John Wiley & Sons (1995).

Refenes, A-P., Y. Abu-Mostafa, J. Moody, A. Weigend (editors) Neural Networks in Financial Engineering; Proceedings of the Third International Conference on Neural Networks in the Capital Markets. Word Scientific 1996.

Ripley, B. Statistical Aspects of Neural Networks. In O.E. Barndorff-Nielsen, J. Jensen, and W. Kendall (eds) Networks and Chaos - Statistical and Probablilistic Aspects, London: Chapman and Hall, 1993.

Rumelhart, E., & McClelland, J. Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Cambridge, MA, MIT Press, 1986.

Sen, T., R. Oliver, N. Sen. Predicting Corporate Mergers, in Refenes A.N. (ed.) Neural Networks in the Capital Markets, John Wiley \& Sons, 1994.

Simoudis, E. et al. [1996] "Integrating Inductive and Deductive Reasoning for Data Mining," in Advances in Knowledge Discovery and Data Mining, The MIT Press, Cambridge, Mass.

Siriopoulos, Costas. [1996] Analysis and Control of Univariate Financial Time Series. (In Greek). Typothito. Athens.

Trippi, R., and E. Turban, (eds) Neural Networks in Finance and Investing, Irwin/Probus Publishing, 1993.

Wasserman, P. Advanced Methods in Neural Computing. New York, Van Nostrand Reinhold, 1993.

Weiss, S., and C. Kulikowski, Computer Systems that Learn: Classification and Prediction Methods from Statistics, Neural Nets, Machine Learning, and Expert Systems, Morgan Kaufman, San Francisco, CA. 1991.

Weigend, A., and N. Gershenfeld, Time Series Prediction: Forecasting the Future and Understanding the Past. Proceedings Volume. Santa Fe Institute. 1992.

White, A, Gallant, A R, Hornik, K, Stinchcombe, M, & Wooldridge, J. Artificial Neural Networks: Approximation and Learning Theory. Cambridge, MA. Blackwell Publishers 1992

Wong, F. & Tan C., "Hybrid Neural, Genetic and Fuzzy Systems," in Trading on the Edge (Deboeck G. Ed.), John Wiley & Sons, Inc., 1994.

Wong F., Tan P., "Neural Networks and Genetic Algorithm For Economic Forecasting", AI in Economics and Business Administration, Ed. I.H. Daniels & Feelders, Netherland.

Wong F., "Hybrid Systems of Neural Network, Fuzzy Logic and Genetic Algorithms", in Advanced Technology for Trading, Portfolio and Risk Management, Edited by Dr. Guido Deboeck, Advanced Analytical Laboratory, Investment Dept., World Bank.

BACK TO CONTENTS

3) PUBLISHED JOURNAL ARTICLES

Abecasis, Sara M. and Evangelina S. Lapenta [1996] "Nonstationary Time-Series Forecasting within a Neural Network Framework," NeuroVe$t Journal, Vol.4, No.4, pp. 9-16.

Abu-Mostafa, Y. "Hints" Neural Computation (1995) 7: 639-671.

Azoff, E. "Reducing Error in Neural Network Time Series Forecasting" Neural Computing & Applications, (1993) 1: 240-247.

Azoff, Michael E., "Monitoring Forecast Performance Using the Breakeven Locus," NeuroVe$t Journal Vol.3, No.2, Mar/Apr 1995, pp. 8-12. (See web site for NeuroVe$t Journal in the Internet Links section below)

Azoff, E. Michael. "Extracting Meaning from a Neural Network," NeuroVe$t Journal, Vol.3, No.1, Jan/Feb 1995, pp. 7-10. (See Web site for NeuroVe$t Journal in the Internet Links section below)

M. Aiken, "Forecasting T-Bill Rates with a Neural Network," Technical Analysis of Stocks and Commodities, Vol. 13, No. 5, May 1995, pp. 85-88.

M. Aiken, Jay Krosp, Chitti Govindarajulu, M. Vanjani, and Randy Sexton, "A Neural Network for Predicting Total Industrial Production," Journal of End User Computing, 7(2), Spring 1995, 19-23.

Altman, E., G. Marco, and Varetto, F. "Corporate Distress Diagnosis: Comparisons Using Linear Discriminant Analysis and Neural Networks (the Italian Experience)." Journal of Banking and Finance, 18 (1994) 505-529.

Baldi, P. and Hornik, K (1989) "Neural Networks and Principal Component Analysis: Learning from Examples Without Local Minima", Neural Networks, 2, 53-8.

Bandy, Howard B. "Thoughts on Desirable Features for a Neural Network-based Financial Trading System," NeuroVe$t Journal, Vol.2, No.3, May/Jun 1994, pp. 19-22.

Bandy, Howard B. "Neural Network-based Trading System Design: Prediction and Measurement Tasks," NeuroVe$t Journal, Vol.2, No.5, Sep/Oct 1994, pp. 26-32.

Bansal, A., R. J. Kauffman, and R.R. Weitz, `Comparing the Modeling Performance of Regression and Neural Networks as Data Quality Varies: A Business Value Approach', Journal of Management Information Systems, 10, 1993, pp 11-32.

Barr, D. and G. Mani, `Using Neural Nets to Manage Investments', AI Expert, 9, 16-21, 1994

Bauer, Richard, Jr. "An Introduction to Genetic Algorithms: A Mutual Fund Screening Example," NeuroVe$t Journal, Vol.2, No.4,Jul/Aug 1994, pp. 16-19.

Billings, Paul. A. "Backpropagation versus Conjugate Gradient Training Methods," NeuroVe$t Journal, Vol.3, No.5, Sep/Oct 1995, pp. 8-12.

Borst, R. A. "Artificial Neural Networks: The Next Modeling/Calibration Technology for the Assessment Community" Artificial Neural Networks, 10, 1991, pp. 69-94.

Bortoli, Mario [1996] "Nonstationary State Space Models for Multivariate Financial Time Series: An Introduction," NeuroVe$t Journal, Vol.4, No.4, pp. 17-26.

Bowen, James E. "Distributed Intelligence Systems," NeuroVe$t Journal, Vol.2, No.1, Jan/Feb 1994, pp. 5-7.

Bowen, James. "A Neural Network Project Roadmap, NeuroVe$t Journal, Vol.2, No.5, Sep/Oct 1994, pp. 7-11.

Cheng, Wei, Wagner, Lori, and Chien-Hua Lin [1996] "Forecasting the 30-year U.S. Treasury Bond with a System of Neural Networks," NeuroVe$t Journal, Vol. 4, No.1, pp. 10-15.

Caldwell, Randall B. [1996] "Three Methods of Neural Network Sensitivity Analysis for Input Variable Reduction: A Case Study in Forecasting the S&P 500 Index (Part 2)," NeuroVe$t Journal, Vol.4, No.1, pp. 16-22.

Caldwell, Randall B. "Performance Evaluation Overview," NeuroVe$t Journal, Vol.1, No.2, Nov/Dec 1993, pg. 4.

Caldwell, Randall B. "Performance Metrics for Neural Network-based Trading System Development," Vol.3, No.2, Mar/Apr 1995, pp. 13-23.

Caldwell, Randall B. "Improved Prediction Performance Metrics for Neural Network-based Financial Forecasting Systems," NeuroVe$t Journal, Vol.3, No.5, Sep/Oct 1995, pp. 22-26.

Caldwell, Randall B. "Fuzzy Systems and Trading," NeuroVe$t Journal, Vol.1, No.1, Sep/Oct 1993, pp. 13.

Caldwell, Randall B. "The Stochastics Indicator: A New Perspective Using Neural Networks," NeuroVe$t Journal, Vol.3, No.2, Mar/Apr 1995, pp. 31-35.

Caldwell, Randall B. "Interpretation of Neural Network Outputs using Fuzzy Logic," NeuroVe$t Journal, Vol.2, No.3, May/Jun 1994, pp. 15-18.

Caldwell, Randall B. "Design of Neural Network-based Financial Forecasting Systems: Data Selection and Data Processing," NeuroVe$t Journal, Vol.2, No.5, Sep/Oct 1994, pp. 12-20.

Caldwell, Randall B. "Three Methods of Neural Network Sensitivity Analysis for Input Variable Reduction: A Case Study in Forecasting the S&P 500 Index (Part 1)," NeuroVe$t Journal, Vol.3, No.6, Nov/Dec 1995, pp. 22-25.

Caldwell, Randall B. "Three Methods of Neural Network Sensitivity Analysis for Input Variable Reduction: A Case Study in Forecasting the S&P500 Index," NeuroVe$t Journal, Jan/Feb 1996, Vol.4, No.1, pp. 16- 22.

Cheng, Wei, Lorry Wagner and Chien-Hua Lin "Forecasting the 30-year U.S. Treasury Bond with a System of Neural Networks," NeuroVe$t Journal, Vol.4, No.1, Jan/Feb 1996, pp. 10-15.

Chenoweth, Tim and Zoran Obradovic, "An Explicit Feature Selection Strategy for Predictive Models of the S&P 500 Index," NeuroVe$t Journal, Vol.3, No.6, Nov/Dec 1995, pp. 14-21.

Chakraborty, K., Kishan, M., Mohan, C., and S. Ranka. "Forecasting the Behavior of Multivariate Time Series". Neural Networks, (1992) 5: 961-970.

Chen, H. Estimation of a Projection-Pursuit Type Regression Model. The Annals of Statistics, 1991, 19(1): 142-157.

Cheng, B, & Titterington, D, Neural Networks: A Review from a Statistical Perspective. Statistical Science, 1994, 9(1): 2-54

Coats, P. and Fant, L. (1992) "A Neural Network Approach to Forecasting Financial Distress", Journal of Business Forecasting, 10, 4, 9-12.

Coats, P. and Fant, L. "Recognizing Financial Distress Patterns Using a Neural Network Tool", Financial Management, 22, 1993, 142-155.

Collins, A. and Evans, A. `Aircraft Noise and Residential Property Values: An Artificial Neural Network Approach' Journal of Transport Economics and Policy, 28, 1994, pp. 175-197.

Connor, J., R. D. Martin, and L.E. Atlas. "Recurrent Neural Networks and Robust Time Series Prediction" IEEE Transactions on Neural Networks (1994) 5: 240-254.

Costantino, Marco, et al. [1996] "Qualitative Information in Finance: Natural Language Processing and Information Extraction," NeuroVe$t Journal, Vol.4, No.6, pp. 14-19.

Costa, A., Markellos, R.N. (1997) "Evaluating Public Transport Efficiency with Artificial Neural Network Models", Transportation Research C, 5 (5), December.

Derry, J.F. [1995] "Induction: Learning Rules from Data (part 1)," NeuroVe$t Journal, Vol.3, No.1.

Derry, J.F. [1995] "Induction: Learning Rules from Data (part 2)," NeuroVe$t Journal, Vol.3, No.4.

Dasgupta, C. G., G. S. Dispensa, and S. Ghose "Comparing the Predictive Performance of a Neural Network Model with Some Traditional Market Response Models" International Journal of Forecasting 10 (1994) 235-244.

Davies, Peter. "Design Issues in Neural Network Development," NeuroVe$t Journal, Vol.2, No.5, Sep/Oct 1994, pp. 21-25.

Davies, Peter. "Implementation Issues in Neural Network Development," NeuroVe$t Journal, Vol.2, No.6, Nov/Dec 1994, pp. 7-10.

Deng, P. `Automatic Knowledge Aquisition and Refinement for Decision Support: A Connectionist Inductive Inference Model` Decision Sciences, 24, 1993, 371-393.

Derry, James F. "A Fuzzy Expert System and Market Psychology: A Primer (Part 1)," NeuroVe$t Journal, Vol.1, No.1, Sep/Oct 1993, pp. 10-12.

Derry, James F. "A Fuzzy Expert System and Market Psychology: A Primer (Part 2)," NeuroVe$t Journal, Vol.1, No.2, Nov/Oct 1993, pp. 12-15.

Derry, James F. "A Fuzzy Expert System and Market Pyschology: A Primer (Part 3)," NeuroVe$t Journal, Vol.2, No.1, Jan/Feb 1994, pp. 20-22.

Derry, James F. "A Fuzzy Expert System and Market Psychology: A Primer (Listing for Part 3)," NeuroVe$t Journal, Vol.2, No.2, Jan/Feb 1994, pp.23-24.

Derry, James F. "Neurofuzzy Hybrids," NeuroVe$t Journal, Vol.2, No.3, May/Jun 1994, pp. 11-14.

Derry, James F. "Induction: Learning Rules from Data (Part 1)," NeuroVe$t Journal, Vol.3, No.1, Jan/Feb 1995, pp. 11-15.

Derry, James F. "Induction: Learning Rules from Data (Part 2)," NeuroVe$t Journal, Vol.3, No.4, Jul/Aug 1995, pp. 13-17.

Dobronogov A.V., Levkov S.P., Makarenko A.S., Nickshich D.A., Plostak M. New models of socio- economical processes and the problem of mentality account in them. Advance in synergetics.Vol.5 Minsk, BSU Press,1995. p. 202-207.

Dobronogov A.V., Makarenko A.S. Global economical and geopolitical model of society of associative memory type. Advances in Synergetics.V.7 Minsk: BSU Press, 1995.

Drossu, Radu and Zoran Obradovic [1996] "Regime Signaling Techniques for Non-Stationary Time-Series Forecasting," NeuroVe$t Journal, Vol.4, No.5, pp. 7-15.

Elman, J. (1990) "Finding Structures in Time", Cognitive Science, 14, 179-211.

Episcopos, A., and J. Davis ‘Predicting Returns on Canadian Exchange Rates with Artificial Neural Networks and EGARCH-M Models’ Neural Computing and Applications Journal 4: 168-174.

Fletcher, D. and E. Goss, `Forecasting with Neural Networks: An Application Using Bankruptsy Data' Information and Management, 24, 1993, pp 159-167.

Fortner, Brand [1996] "An Overview of Data Dimensions and Visualization," NeuroVe$t Journal, Vol.4, No.2, pp. 14-20.

Frison, Ted W. "Chaos and Prediction Horizons in Silver Futures Trading," NeuroVe$t Journal, Vol.3, No.3, May/Jun 1995, pp. 22-29.

Hampton, James [1996] "A Visualization Technique for Selecting Neural Network Trading Thresholds," NeuroVe$t Journal, Vol.4, No.2, pp. 25-29.

Hiemstra, Ypke [1996] "Applying Neural Networks and Genetic Algorithms to Tactical Asset Allocation," NeuroVe$t Journal, Vol.4, No.3, pp. 8-15.

Hampton, James [1996] "Rescaled Range Analysis: Approaches for the Financial Practitioner (Part 1)," NeuroVe$t Journal, Vol.4, No.1, pp. 23-28.

Hampton, James [1996] "Rescaled Range Analysis: Approaches for the Financial Practitioner (Part 3)," NeuroVe$t Journal, Vol.4, No.4, pp. 27-30.

Hampton, James [1996] "Rescaled Range Analysis: Approaches for the Financial Practitioner (Part 4)," NeuroVe$t Journal, Vol.4, No.5, pp. 24-32.

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Hampton, James and Randall B. Caldwell [1996] "Visualization Tools for Complexity and Finance," NeuroVe$t Journal, Vol.4, No.2, pp. 7-13.

Hampton, James "Rescaled Range Analysis: Approaches for the Financial Practitioner," NeuroVe$t Journal, Jan/Feb 1996, Vol.4, No.1, pp. 23-28.

Hampton, James [1996] "Rescaled Range Analysis: Approaches for Financial Practitioner (Part 2)," NeuroVe$t Journal, Vol.4, No.3, pp. 23-29.

Hampton, James "A Visualization Technique for Selecting Neural Network Trading Thresholds," NeuroVe$t Journal, Vol.4, No.2, pp. 25-29.

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Hiemstra, Ypke (1996), "Applying Neural Networks and Genetic Algorithms to Tactical Asset Allocation", NeuroVe$t Journal, Vol. 4, No. 3, pp. 8-15

Hoptroff, R. "The Principles and Practice of Time Series Forecasting and Business Modeling Using Neural Networks", Neural Computing and Applications, (1993) 1, 59-66

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