Complexity and self-organization: data analysis and models
| dc.contributor.advisor | Thomas, Tony | en |
| dc.contributor.advisor | Leinweber, Derek Bruce | en |
| dc.contributor.author | Bartolozzi, Marco | en |
| dc.contributor.school | School of Chemistry and Physics | en |
| dc.date.issued | 2006 | en |
| dc.description.abstract | The understanding of the emergent behaviour of complex systems is probably one of the most intriguing challenges in modern theoretical physics. In the present Thesis we use novel data analysis techniques and numerical simulations in order to shed some light on the fundamental mechanisms involved in their dynamics. We divide the main core of the research into three parts, each of which address a specific, and formally well defined, issue. In the first part, we study the processes of self - organization and herding in the evolution of the stock market. The data analysis, carried out over the fluctuations of several international indices, shows an avalanche - like dynamics characterized by power laws and indicative of a critical state. Further evidence of criticality relates to the behaviour of the price index itself. In this case we observe a power law decline with superimposed embedded log - periodic oscillations which are possibly due to an intrinsic discrete scale invariance. A stochastic cellular automata, instead, is used to mimic an open stock market and reproduce the herding behaviour responsible for the large fluctuations observed in the price. The results underline the importance of the largest clusters of traders which, alone, can induce a large displacement between demand and supply and lead to a crash. The second part of the Thesis focuses on the role played by the complex network of interactions that is created among the elementary parts of the system itself. We consider, in particular, the influence of the so - called " scale - free " networks, where the distribution of connectivity follows a power law, on the antiferromagnetic Ising model and on a model of stochastic opinion formation. Novel features, not encountered on regular lattices, have been pointed out. In the former case a spin glass transition at low temperatures is present while, in the latter, the turbulent - like behaviour emerging from the model is found to be particularly robust against the indecision of the agents. The last part is left for a numerical investigation of an extremal dynamical model for evolution / extinction of species. We demonstrate how the mutual cooperation between them comes to play a fundamental role in the survival probability : a healthy environment can support even less fitted species. | en |
| dc.description.dissertation | Thesis (Ph.D.)--School of Chemistry and Physics, 2006. | en |
| dc.format.extent | 902645 bytes | en |
| dc.format.extent | 2008680 bytes | en |
| dc.format.extent | 4036554 bytes | en |
| dc.format.extent | 1754534 bytes | en |
| dc.format.extent | 118871 bytes | en |
| dc.format.mimetype | application/pdf | en |
| dc.format.mimetype | application/pdf | en |
| dc.format.mimetype | application/pdf | en |
| dc.format.mimetype | application/pdf | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.uri | http://hdl.handle.net/2440/37809 | |
| dc.language.iso | en | en |
| dc.provenance | This electronic version is made publicly available by the University of Adelaide in accordance with its open access policy for student theses. Copyright in this thesis remains with the author. This thesis may incorporate third party material which has been used by the author pursuant to Fair Dealing exception. If you are the author of this thesis and do not wish it to be made publicly available or If you are the owner of any included third party copyright material you wish to be removed from this electronic version, please complete the take down form located at: http://www.adelaide.edu.au/legals | en |
| dc.subject | econophysics | en |
| dc.subject.lcsh | Self-organizing systems | en |
| dc.subject.lcsh | Stock exchanges Mathematical models | en |
| dc.subject.lcsh | Stock exchanges Data processing | en |
| dc.title | Complexity and self-organization: data analysis and models | en |
| dc.type | Thesis | en |
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