An inductive learning system for rating securities

  • Mehdi R. Zargham
3 Machine Learning Inductive and Deductive Strategies
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1416)

Abstract

During the last few years, we have developed an expect system, called PORSEL (PORtfolio SELection system), which uses a small set of rules to select stocks. This paper improves the PORSEL by incorporating several new features and interfaces. The new PORSEL now consists of three components: the information center, the fuzzy stock selector, and the portfolio constructor. The purpose of the information center is to provide representation of several technical indicators such as candlestick charts, moving average of closing prices, and price trends. The fuzzy stock selector evaluates the listed stocks and then assigns a composite score for each stock. The portfolio constructor generates the optimal portfolios for the selected stocks. The new PORSEL also includes a user-friendly interface for adding and deleting rules during the run time. The results of simulation show that our new version of PORSEL outperformed the market almost every year during the testing period.

Keywords

Cash Flow Stock Price Optimal Portfolio Dividend Yield Investment Policy 
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.
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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Mehdi R. Zargham
    • 1
  1. 1.Department of Computer ScienceSouthern Illinois UniversityCarbondaleUSA

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