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pro vyhledávání: '"Heckens, Anton J."'
Risk assessment for rare events is essential for understanding systemic stability in complex systems. As rare events are typically highly correlated, it is important to study heavy-tailed multivariate distributions of the relevant variables, i.e. the
Externí odkaz:
http://arxiv.org/abs/2412.11601
Multivariate Distributions are needed to capture the correlation structure of complex systems. In previous works, we developed a Random Matrix Model for such correlated multivariate joint probability density functions that accounts for the non-statio
Externí odkaz:
http://arxiv.org/abs/2412.11602
Autor:
Heckens, Anton J., Guhr, Thomas
Publikováno v:
Physica A: Statistical Mechanics and its Applications 604, 127704 (2022)
Complex systems are usually non-stationary and their dynamics is often dominated by collective effects. Collectivity, defined as coherent motion of the whole system or of some of its parts, manifests itself in the time-dependent structures of covaria
Externí odkaz:
http://arxiv.org/abs/2202.00297
Autor:
Heckens, Anton J., Guhr, Thomas
Publikováno v:
J. Stat. Mech. (2022) 043401
Prediction of events in financial markets is every investor's dream and, usually, wishful thinking. From a more general, economic and societal viewpoint, the identification of indicators for large events is highly desirable to assess systemic risks.
Externí odkaz:
http://arxiv.org/abs/2107.09048
Publikováno v:
J. Stat. Mech. (2020) 103402
The measured correlations of financial time series in subsequent epochs change considerably as a function of time. When studying the whole correlation matrices, quasi-stationary patterns, referred to as market states, are seen by applying clustering
Externí odkaz:
http://arxiv.org/abs/2004.12336
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