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Quantifying the Behavior of Stock Correlations Under Market Stress: Tobias Preis, Helen Susannah Moat, H. Eugene Stanley & Steven R. Bishop

Understanding correlations in complex systems is crucial in the face of turbulence, such as the ongoing financial crisis. However, in complex systems, such as financial systems, correlations are not constant but instead vary in time. Here we address the question of quantifying state-dependent correlations in stock markets. Reliable estimates of correlations are absolutely necessary to protect a portfolio. We analyze 72 years of daily closing prices of the 30 stocks forming the Dow Jones Industrial Average (DJIA). We find the striking result that the average correlation among these stocks scales linearly with market stress reflected by

normalized DJIA index returns on various time scales. Consequently, the diversification effect which should protect a portfolio melts away in times of market losses, just when it would most urgently be needed. Our empirical analysis is consistent with the interesting possibility that one could anticipate diversification breakdowns, guiding the design of protected portfolios.

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FuturICT: A planetary nervous system for social mining and collective awareness:F.Giannotti, D.Pedreschi, A.Pentland, P.Lukowicz, D.Kossmann, J. Crowley and D.Helbing

FuturICT: A planetary nervous system for social mining and collective awareness:F.Giannotti, D.Pedreschi, A.Pentland, P.Lukowicz, D.Kossmann, J. Crowley and D.Helbing | FuturICT Journal Publications | Scoop.it
By F.Giannotti, D.Pedreschi, A.Pentland, P.Lukowicz, D.Kossmann, J. Crowley and D.Helbing
We present a research roadmap of a Planetary Nervous System (PNS), capable of sensing and mining the digital breadcrumbs of human activities and unveiling the knowledge hidden in the big data for addressing the big questions about social complexity. We envision the PNS as a globally distributed, self-organizing, techno-social system for answering analytical questions about the status of world-wide society, based on three pillars: social sensing, social mining and the idea of trust networks and privacy-aware social mining. We discuss the ingredients of a science and a technology necessary to build the PNS upon the three mentioned pillars, beyond the limitations of their respective state-of-art. Social sensing is aimed at developing better methods for harvesting the big data from the techno-social ecosystem and make them available for mining, learning and analysis at a properly high abstraction level. Social mining is the problem of discovering patterns and models of human behaviour from the sensed data across the various social dimensions by data mining, machine learning and social network analysis. Trusted networks and privacy-aware social mining is aimed at creating a new deal around the questions of privacy and data ownership empowering individual persons with full awareness and control on own personal data, so that users may allow access and use of their data for their own good and the common good. The PNS will provide a goal-oriented knowledge discovery framework, made of technology and people, able to configure itself to the aim of answering questions about the pulse of global society. Given an analytical request, the PNS activates a process composed by a variety of interconnected tasks exploiting the social sensing and mining methods within the transparent ecosystem provided by the trusted network. The PNS we foresee is the key tool for individual and collective awareness for the knowledge society. We need such a tool for everyone to become fully aware of how powerful is the knowledge of our society we can achieve by leveraging our wisdom as a crowd, and how important is that everybody participates both as a consumer and as a producer of the social knowledge, for it to become a trustable, accessible, safe and useful public good.
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JOURNAL: THE EUROPEAN PHYSICAL JOURNAL SPECIAL TOPICS  Vol. 214 (November II 2012)"Participatory Science and Computing for Our Complex World".

http://epjst.epj.org/index.php?option=com_toc&url=/articles/epjst/abs/2012/14/contents/contents.html

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