In the era of Big Data our society is given the unique opportunity to understand the inner dynamics and behavior of complex socio-economic systems. Advances in the availability of very large databases, in capabilities for massive data mining, as well as progress in complex systems theory, multi-agent simulation and computational social science open the possibility of modeling phenomena never before successfully achieved. This contributed volume from the Perm Winter School address the problems of the mechanisms and statistics of the socio-economics system evolution with a focus on financial markets powered by the high-frequency data analysis.

About the Author

Anil K. Bera, Ph.D., Professor of Economics at University of Illinois. Since 1989, Dr. Bera has been awarded eight degrees from Calcutta University, the Indian Statistical Institute, and the Australian National University for his excellence in teaching as well as professional and postgraduate training. He is the author of the popular Jarque–Bera goodness-of-fit test, as well as numerous publications in econometrics and economic statistics.

Sergey Ivliev, Ph.D. in economics, Associate Professor at Perm State University, Chief Research Officer at PROGNOZ, Member of Steering committee of PRMIA Russia. He is a Principal coordinator of Perm Winter School and editor of the Market Risk and Financial Markets Modeling book published by Springer.

Fabrizio Lillo, Professor of Quantitative Finance at the Scuola Normale Superiore di Pisa (Italy), Assistant Professor of Physics at Palermo University (Italy) and External Professor at the Santa Fe Institute (USA). He is author of more than 60 referred scientific papers. The ISI papers have received more than 800 citations and his h-index is 16. His research is focused on the application of methods and tools of statistical physics to economic, financial, and biological complex systems.

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