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Cybernetic approach to investment decision making


  • Felsen, J


This paper summarizes the results of our research into applications of cybernetic concepts and artificial intelligence techniques to investment analysis: it outlines the philosophy underlying the cybernetic approach to market forecasting and investment selection. This approach is computer oriented--it enables us to automate or program directly the complex judgmental aspects of investment decision making. The cybernetic approach alleviates some deficiencies of conventional statistical methods. Specifically, it (1) explicitly includes the time dimension into investment analysis, (2) is based on methods for decision making under uncertainty rather than risk, (3) yields computationally feasible methods for coping with the high complexity in investment analysis, and (4) yields decisions that are optimal rather than satisficing, i.e. performance of the Cybernetic Investment Decision System (CIDS) gradually improves during its operation through learning from past experience. A simplified CIDS has been implemented and tested in actual investment analysis. The experimental results of these tests indicate that through the cybernetic approach quality of investment decisions can be improved.

Suggested Citation

  • Felsen, J, 1978. "Cybernetic approach to investment decision making," Omega, Elsevier, vol. 6(3), pages 237-247.
  • Handle: RePEc:eee:jomega:v:6:y:1978:i:3:p:237-247

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    References listed on IDEAS

    1. Richard Ehrhardt, 1979. "The Power Approximation for Computing (s, S) Inventory Policies," Management Science, INFORMS, vol. 25(8), pages 777-786, August.
    2. Richard Ehrhardt & Charles Mosier, 1984. "A Revision of the Power Approximation for Computing (s, S) Policies," Management Science, INFORMS, vol. 30(5), pages 618-622, May.
    3. Arthur F. Veinott, Jr. & Harvey M. Wagner, 1965. "Computing Optimal (s, S) Inventory Policies," Management Science, INFORMS, vol. 11(5), pages 525-552, March.
    4. Eliezer Naddor, 1975. "Optimal and Heuristic Decisions in Single-and Multi-Item Inventory Systems," Management Science, INFORMS, vol. 21(11), pages 1234-1249, July.
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