BECS: Understanding Complex Systems: Large-Scale Data Driven Modeling

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The objective of the proposal is to discover the general properties of complex systems so that these principles can be applied to both manipulate existing complex systems and to design engineered complex systems for future applications. As a model complex system, this proposal addresses modeling and analysis of the financial markets and the financial time series. There are numerous non-trivial fluctuation patterns in financial systems at every scale. These systems are composed of many agents, and the interactions and strategies on the microscopic scale build up to the macroscopic scale, which get reflected in the prices of single and multiple assets in the economy. The large scale dynamics and structure are often independent of the particular details of the microscopic interaction. This "universality" makes it meaningful to design the most convenient "minimal model". The financial markets and the financial time series are clearly such phenomena. Using ideas from statistical physics based models, minority games, adaptive systems, and non-linear systems theory, we propose to develop multi-agent succinct models that can capture various features of the highly-observable systems. The project will lead to a fundamental understanding of the types of microscopic rules and their interactions that lead to the emergence of global systems and an understanding of what gives rise to complex behavior such as fluctuations, long-term correlations and memory, and successful recovery from a major collapses in such systems.The societal impact of successful research in large complex systems ranges from theglobal information economy, to shared infrastructure, to global ecology and human health. The scientific impact extends to statistical mechanics, nonlinear dynamics and systems and numerous other areas. At the same time, our project will contribute significantly to training, education and outreach. For example, graduate students and postdoctoral researchers will broaden their exposure by working jointly with both a mathematician and an engineering faculty, and we will use a proven model for engaging undergraduates in our research through the Institute for Pure and Applied Mathematics (IPAM at UCLA). We will offer a summer school to train many more young scientists in the relevant techniques.