EXPRESS — A Strategic Software System for Equity Valuation

  • M. P. Foscolos
  • S. Nilchan
Conference paper


This paper examines the problems associated with equity valuation and exposes the weaknesses of current computer based modelling systems. The paper identifies the necessary requirements of a strategic software system for equity valuation and proposes a software system with an integrated architecture, which combines both artificial intelligence technologies with conventional software. The paper then describes a powerful strategic software system, EXPRESS, developed by the authors to significantly de-skill and improve stock valuation. The EXPRESS system is a state-of the-art windows based application capable of performing the three accepted methods of stock valuation namely, quantitative, technical and fundamental analysis. The paper outlines the integrated architecture of EXPRESS and describes the function of each of the three integrated software systems, the EXPRESS decision support generator system, the EXPRESS artificial neural network system and the EXPRESS extension model system.


Expert System Express System Time Series Forecast Equity Valuation Rule Base Expert System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    D.R. Dolk. An Introduction to Model Integration & Integrated Modelling Environments. Decision Support Systems, 10, 1993.Google Scholar
  2. [2]
    J.J. Elam and B. Konsynski. Using AI Techniques to Enhance the Capabilities of Model Management Systems. Decision Science, 1987.Google Scholar
  3. [3]
    M.P. Foscolos. The Development of a Strategic Software System for Resource Equity Valuation. PhD thesis, Imperial College, University of London, 1996.Google Scholar
  4. [4]
    M.P. Foscolos and S. Nilchan. Improving Decision-Making in the Financial Market via the Probablistic Neural Network Paradigm. Neurove$t Journal, March 1997.Google Scholar
  5. [5]
    M.P. Foscolos, S. Nilchan, and P.E. Bell. Improving Financial Market Forcasts via the Recurrent Neural Network Paradigm. In AIC Modelling Techniques in Portfolio Management Conference, Inter-Continental Hotel, Sydney, Australia, August 1996.Google Scholar
  6. [6]
    M.P. Foscolos and C.T. Shaw. Fundamental Resource Equity Evaluation & Modelling. In IASTED International Conference of Applied Modelling and Simulation, Lugano, Switzerland, 1994.Google Scholar
  7. [7]
    D. King. Intelligent Decision Support: Strategies for Integrating Decision Support, Database Management and Expert System Technology. Expert Systems with Applications, 1, 1990.Google Scholar
  8. [8]
    T.J. Martin. Integration With Conventional Information Systems. In Watkins & Eliot, editor, Expert Systems in Business and Finance. Wiley & Son, 1993.Google Scholar
  9. [9]
    R.G. Ramirez, C. Ching, and R.D. Louise. Independence and Mappings in Model Decision Support Systems. Decision Support Systems, 10, 1993.Google Scholar
  10. [10]
    R.H. Sprague and J.H. Watson. Decision Support Systems. Prentice Hall, 1986.Google Scholar
  11. [11]
    G.S. Swales and Y. Yoon. Applying Neural Networks to Investment Analysis. Financial Analysts Journal, Sept/Oct 1992.Google Scholar
  12. [12]
    J.T.C. Tseng. A Unified Architecture for Intelligent DSS. In 21st HICSS, 1988.Google Scholar
  13. [13]
    E. Turban. Decision Support and Expert Systems-Management Support Systems. McMillan, 1988.Google Scholar
  14. [14]
    E. Turban. Expert Systems Integration with Computer Based Information Systems. In Watkins & Eliot, editor, Expert Systems in Business and Finance. Wiley & Son, New York, 1993.Google Scholar
  15. [15]
    W. Wu. An Integrated System Based on the Synergy Between Systems. In International Conference of the Systems Dynamic Society, June 1988.Google Scholar

Copyright information

© Springer-Verlag Wien 1998

Authors and Affiliations

  • M. P. Foscolos
    • 1
  • S. Nilchan
    • 2
  1. 1.School of Information Systems, Faculty of CommerceUniversity of New South WalesSydneyAustralia
  2. 2.Centre for Process Systems EngineeringImperial CollegeLondonUK

Personalised recommendations