High Performance Exploration Of Emergent Financial Phenomena In Spatial Segregation Models

Models of segregation [1] are known to exhibit many fascinating spatial phenomena, by combining such models with financial interactions [2] positions of equilibria are disturbed and phase-transitional parameter interactions can be discovered. Utilising high performance computation for parameter space exploration significantly enhances analytical capability, inviting more rigorous exploration via statistical methods than has been historically presented. This work presents the execution of one such model inviting discussion as to the implications on both fiscal and more general domestic policy when tackling issues surrounding income inequality and wealth distribution.

Figure 1 shows the Gini coefficient of 10^4 model executions, highlighting the phase-transitional nature of the relationship between amount traded during local interactions and satisfaction threshold of agents within the model in relation to the financial inequality of the system as a whole. Cells were confined to a hexagonal mesh, negating the choice of neighbourhood type (nearest/Moore). Future work is to incorporate more sophisticated trading mechanics, compare effects of spatial mesh variants, and explore other models using the framework written to facilitate the parallelized execution.

Authors: 
Oliver Scholten and Ken Hawick
Room: 
6
Date: 
Tuesday, September 25, 2018 - 18:15 to 18:30

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