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Abstract:
A Catastrophe Theory Model modified for the explanation of the evolution/revolution of behavior in the securities market can be classified in the realm of behavioral finance. (See Thaler, 1993; Statman, 1998 and Pruden, 1989). An early model of the Cusp Catastrophe Model modified to explain speculative crashes appeared in Zeeman (1976, 1977). Later, Pruden (1979) expanded upon Zeeman's use of the Cusp Model version of Catastrophe Theory to allow for "buying stampedes" as well as "selling panics". Pruden (1980) also established connections between the Cusp Catastrophe Model and technical market analysis. Whereas the Catastrophe Theory Model, like other models from the behavioral sciences, provides a positive scientific theory as to the "why" of behavior in the stock market, technical market analysis furnishes a nominal theory of rules and principles about "how" a trader or investor may profit from the behavior observed in the stock market. Hence, the presupposition is that behavioral science models that explain the stock market behavior provide solid scientific foundations upon which to base the principles and practices of technical market analysis.

Catastrophe Theory Model, behavioral finance, technical analysis, finance model

Abstract:
In previous papers we have shown another interpretation of the irrationality of financial market agents. Another methodology has been proposed. But it also shown that others questions might be highlighted from both epistemological and social welfare point of view. This paper tries to go further on those aspects to open a new research program about economic action and the social responsibility of actors when they "produce reality".

financial market, social welfare, holistic, coordination, convention

Abstract:
The behavioral finance model for structuring the data of the experiment was the Cusp Catastrophe Model of non-linear behavior. The nominal model, based upon the data exposed by the positive model, was a group of four technical market analysis principles and one mental discipline/trading strategy discipline.

This article, the Part B article of the series, seeks to extend the interpretations of the findings. But rather than the single tightly structured theme of Part A, this time the Part B calls upon the varied talents of all three co-authors.

This article takes advantage of the international, cross-cultural and multiple disciplines represented by the three authors. Hence, each of the three co-authors was asked to analyze and re-interpret the experimental evidence from his particular professional discipline. Thus, the three co-authors reflect interpretations from three different angles.
The first subsection of this article by Walter Baets reflects his area of discipline, which is complexity and knowledge management. Dr. Baets reflected upon the behavior that gave rise to the price behavior generated by the experiment. Dr. Baets provides a broad perspective upon behavioral finance notions and he gives a penetrating look into the structure behind the actions of the student traders in the Cal Tech Experiment. Dr. Baets considers SWARM-like theories to explain the emergent behavior generated by the individualistic, selfserving behavior of interacting agents, the students in the experiment.

The second sub-section by Professor Bernard Paranque reflects his formation as a doctor of economics and his responsibilities as Head Finance and Information Department. Dr. Paranque sets forth reflections upon the experiment described in Part A that touch upon the sensitive and vital but often unexamined issue of risk and welfare and for all market participants. This viewpoint stands opposite to the self-serving behavior of the few elite traders who could have exploited the cusp and profited from the decline using technical analysis tools. In other words, Dr. Paranque takes up the challenge of examining the ethical dimension of behavioral finance and technical market analysis. His point of departure is the greater fool theory operating during the experiment.

Pruden takes a pragmatic yet artistic approach to the extraction of more information from the technical analysis rules that were used to interpret the laboratory data. And that could have been used by the astute, elite trader to exit the market in advance of the crash in prices. The third section by Pruden reflects upon the four technical rules of principles that were applied in the Part A article. Pruden in Part B seeks to extend the analytical capacity each of the four technical rules or principles by carrying them into the realm of Sequential Art. These were the tools that could have been employed by the astute, elite trader to identify the cusp in time to avoid the catastrophic crash. His goal is to offer ideas and techniques for extracting even more information from the data found in the laboratory experiment.

Extensions stimulated by notions from Sequential Art 1may offer value added to technical analysts in general.

Evaluation, social welfare, autopoetic system, learning, coordination, Chart Analysis as Sequential Art