Predicting the performance of a company’s stock for decision purposes is typically made using a scientifically rigorous method known as technical and fundamental analysis. In this paper, such techniques appear insufficient for potentially extreme decision making situations. For argumentation purposes a typical ‘random walk’ high volatility stock market scenario is reformulated using derivative instruments, as well as CFD’s (Contracts for Difference), as a way to control the interplay between results and risk. In the process attempts are made to transform an ‘ill’ structured decision situation into a manageable solution that is supported by an N*M factorial experimental design. The treatment consists of different types of Decision Support Systems (DSS) architectures that range from a simple calculator to an experimentally induced intelligent STOP and LIMIT mechanisms that control the critical entry and exit portfolio conditions. In the conclusion we discuss the results obtained in a laboratory experimentation as they appear “too good to be true” In particular, the results challenge the economic market efficiency principles with, it’s classical “no –arbitrage’ clause” and ‘portfolio diversification’ principle.
Jacques, Ajenstat, "DSS for Extreme Decision Making: the case of high volatility stock market portfolio" (2007). ICDSS 2007 Proceedings. 17.