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Probability of large movements in financial markets

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TLDR
Based on empirical financial time series, it is shown that the “silence-breaking” probability follows a super-universal power law: the probability of observing a large movement is inversely proportional to the length of the on-going low-variability period.
Abstract
Based on empirical financial time series, we show that the “silence-breaking” probability follows a super-universal power law: the probability of observing a large movement is inversely proportional to the length of the on-going low-variability period . Such a scaling law has been previously predicted theoretically [R. Kitt, J. Kalda, Physica A 353 (2005) 480], assuming that the length-distribution of the low-variability periods follows a multi-scaling power law.

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Journal ArticleDOI

The predictive power of power-laws: An empirical time-arrow based investigation

TL;DR: In this article , the authors analyzed the statistical features of financial time series and showed that the future and reversed-looking time series possess very similar properties, with some features being distinguishable with their method.
References
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Book

The Fractal Geometry of Nature

TL;DR: This book is a blend of erudition, popularization, and exposition, and the illustrations include many superb examples of computer graphics that are works of art in their own right.
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Introduction to Econophysics: Correlations and Complexity in Finance

TL;DR: Economists and workers in the financial world will find useful the presentation of empirical analysis methods and well-formulated theoretical tools that might help describe systems composed of a huge number of interacting subsystems.
Journal ArticleDOI

Punctuated equilibrium and criticality in a simple model of evolution.

TL;DR: A simple and robust model of biological evolution of an ecology of interacting species that self-organizes into a critical steady state with intermittent coevolutionary avalanches of all sizes and exhibits ``punctuated equilibrium'' behavior.
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