A new approach to user behavior modeling based on Game Theory was proposed. It was developed to consider initial intensity, a strategy applied, a profit gained, and resources utilized as inalienable attributes of users' behavior. The approach covers various aspects of users' motivation and rational actions, not only a statistical image of a pool's summary. Additionally, the given model is strongly connected to profit and loss parameters by operating with profit and utilized resources as parts of model inputs. The proposed model can enable efficient modeling aimed to validate an economic result of existing interfaces and assume results of new ones.
Manipulations are taking place widely on various capital, commodity, derivative and other markets. They are reported regularly and sometimes causing significant losses. But it doesn’t mean that the efforts intended to limit this sort of activity are insignificant. Surveillance budgets, as well as applied fines, are impressing. The annual volume of manipulative attempts and the efforts, intended to deter these attempts, are growing exponentially year after year. The imperfection and low versatility of detection methods are leaving space for successful attempts, making manipulative behavior still attractive. This paper is representing the model, based on the Game Theory and aimed to fit modern requirements of surveillance. The article defines basic problems in manipulation detection and proves model’s capability to solve them. However, the problem is reviewed on a general level allowing to elaborate the versatile model, but not a specific manipulative scenario. At the same time, the model allows complementing it with precise tools defining aspects related to actual manipulation. Manipulation and the shaping of it's economic results are reviewed in-depth, revealing it's core phenomenology.
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