VirtualVet: intelligence platform for early identification of physiological and en...
Deep Reinforcement Learning Applied to Investment Portfólio Management
Work accident: from sociotechnical analysis towards social construction of changes
Grant number: | 18/22562-4 |
Support Opportunities: | Scholarships abroad - Research |
Start date: | August 26, 2019 |
End date: | February 25, 2020 |
Field of knowledge: | Applied Social Sciences - Economics - Fiscal and Monetary Policies |
Principal Investigator: | Mario Augusto Bertella |
Grantee: | Mario Augusto Bertella |
Host Investigator: | Didier Sornette |
Host Institution: | Faculdade de Ciências e Letras (FCL). Universidade Estadual Paulista (UNESP). Campus de Araraquara. Araraquara , SP, Brazil |
Institution abroad: | Swiss Federal Institute of Technology Zurich, Switzerland |
Abstract This research targets to simulate computationally an environment with heterogeneous agents where their behaviors differ from the optimizer and rational pattern of the conventional economic theory incorporating psychological or emotional biases. The Behavioral Finance, in conjunction with Psychology, has revealed that successful agents are not as rational as neoclassical theory assumes. On the other hand, the Agent-Based Computational Economics verifies which result prevails when various agents with different behaviors interact. In this sense, the instrumental agent based is an important tool to test and simulate whether micro aspect predominates and which factors may explain the divergent results under the macro point of view. On the other hand, since economic agents relate to each other in some way, the goal is to include one or more types of social network to ascertain their influence on the formation of booms and crashes. | |
News published in Agência FAPESP Newsletter about the scholarship: | |
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