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Jørgen Vitting Andersen

Researcher at University of Paris

Publications -  89
Citations -  1795

Jørgen Vitting Andersen is an academic researcher from University of Paris. The author has contributed to research in topics: Financial market & Stock market. The author has an hindex of 21, co-authored 87 publications receiving 1708 citations. Previous affiliations of Jørgen Vitting Andersen include Technical University of Denmark & McGill University.

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Tricritical Behavior in Rupture Induced by Disorder

TL;DR: In this article, the authors show that the disorder is a relevant field leading to tricriticality, separating a first-order regime where rupture occurs without significant precursors from a second order regime where the macroscopic elastic coefficient exhibits power law behavior.
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The $-game

TL;DR: In this article, a payoff function extending Minority Games (MG) is proposed to capture the competition between agents to make money, where the best strategies are not always targeting the minority but are shifting opportunistically between the minority and the majority.
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Slider block friction model for landslides: Application to Vaiont and La Clapière landslides

TL;DR: In this article, the authors provide a physical basis for this phenomenological law based on a slider block model using a state and velocity-dependent friction law established in the laboratory, and use the slider block friction model to analyze quantitatively the displacement and velocity data preceding two landslides, Vaiont and La Clapiere.
Posted Content

A Nonlinear Super-Exponential Rational Model of Speculative Financial Bubbles

TL;DR: In this paper, a hyperbolic stochastic finite-time singularity formula is proposed to transform a Gaussian white noise into a rich time series possessing all the stylized facts of empirical prices, as well as accelerated speculative bubbles preceding crashes.
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A nonlinear super-exponential rational model of speculative financial bubbles

TL;DR: In this article, a hyperbolic stochastic finite-time singularity formula is proposed to transform a Gaussian white noise into a rich time series possessing all the stylized facts of empirical prices, as well as accelerated speculative bubbles preceding crashes.