Recognition of Stock Exchange Processes as a Poisson Process of Events of Two Types: Models with Stimulation and Learning

This article analyzes the stock exchange phenomenon into the context of the current "culture of finance" and the "theology of prosperity" as the key metaphor of human activity. It makes a conclusion on fundamental different anthropological types which participate in the stock exchange processes. The paper presents the homological comparison between the category of the gamer from the game study philosophy and the category of the actors of the stock exchange processes. It also makes a conclusion on the mutual influence of the mechanisms of making knowledge within the framework of the philosophical academic system and the stock exchange as a social institution.

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Lectures on the Poisson Process

10.1017/9781316104477 ◽

2017 ◽

Cited By ~ 42

Author(s):

Günter Last ◽

Mathew Penrose

Keyword(s):

Poisson Process

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Tests on the Intensity of a Poisson Process

Communications in Statistics - Simulation and Computation ◽

10.1080/03610917508548435 ◽

1975 ◽

Vol 4 (8) ◽

pp. 777-782

Author(s):

John Saw

Keyword(s):

Poisson Process

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Social exchange processes, health behaviour, and health behaviour change

Zeitschrift für Gesundheitspsychologie ◽

10.1026/0943-8149.16.3.131 ◽

2008 ◽

Vol 16 (3) ◽

pp. 131-134

Author(s):

Urte Scholz ◽

Rainer Hornung

Keyword(s):

Social Exchange ◽

Health Behaviour ◽

Psychological Research ◽

Smoking Behaviour ◽

Self Report ◽

Long Term Effects ◽

Main Research ◽

Research Areas ◽

Exchange Processes ◽

Multi Method Approach

Abstract. The main research areas of the Social and Health Psychology group at the Department of Psychology at the University of Zurich, Switzerland, are introduced. Exemplarily, three currently ongoing projects are described. The project ”Dyadic exchange processes in couples facing dementia” examines social exchanges in couples with the husband suffering from dementia and is based on Equity Theory. This project applies a multi-method approach by combining self-report with observational data. The ”Swiss Tobacco Monitoring System” (TMS) is a representative survey on smoking behaviour in Switzerland. Besides its survey character, the Swiss TMS also allows for testing psychological research questions on smoking with a representative sample. The project, ”Theory-based planning interventions for changing nutrition behaviour in overweight individuals”, elaborates on the concept of planning. More specifically, it is tested whether there is a critical amount of repetitions of a planning intervention (e.g., three or nine times) in order to ensure long-term effects.

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Applying the Anderson-Darling Test to Suicide Clusters

Crisis ◽

10.1027/0227-5910/a000197 ◽

2013 ◽

Vol 34 (6) ◽

pp. 434-437 ◽

Cited By ~ 5

Author(s):

Donald W. MacKenzie

Keyword(s):

Poisson Process ◽

Goodness Of Fit ◽

Small Samples ◽

Massachusetts Institute Of Technology ◽

Homogeneous Poisson Process ◽

Cornell University ◽

The Difference ◽

Suicide Clusters ◽

Institute Of Technology ◽

Anderson Darling

Background: Suicide clusters at Cornell University and the Massachusetts Institute of Technology (MIT) prompted popular and expert speculation of suicide contagion. However, some clustering is to be expected in any random process. Aim: This work tested whether suicide clusters at these two universities differed significantly from those expected under a homogeneous Poisson process, in which suicides occur randomly and independently of one another. Method: Suicide dates were collected for MIT and Cornell for 1990–2012. The Anderson-Darling statistic was used to test the goodness-of-fit of the intervals between suicides to distribution expected under the Poisson process. Results: Suicides at MIT were consistent with the homogeneous Poisson process, while those at Cornell showed clustering inconsistent with such a process (p = .05). Conclusions: The Anderson-Darling test provides a statistically powerful means to identify suicide clustering in small samples. Practitioners can use this method to test for clustering in relevant communities. The difference in clustering behavior between the two institutions suggests that more institutions should be studied to determine the prevalence of suicide clustering in universities and its causes.

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