M. Dashti Moghaddam, Zhiyuan Liu & R. A. Serota 
The European Physical Journal B volume 94, Article number: 83 (2021)

We investigate relaxation and correlations in a class of mean-reverting models for stochastic variances. We derive closed-form expressions for the correlation functions and leverage for a general form of the stochastic term. We also discuss correlation functions and leverage for three specific models— multiplicative, Heston (Cox-Ingersoll-Ross) and combined multiplicative-Heston—whose steady-state probability density functions are Gamma, Inverse Gamma and Beta Prime respectively, the latter two exhibiting “fat” tails. For the Heston model, we apply the eigenvalue analysis of the Fokker-Planck equation to derive the correlation function—in agreement with the general analysis— and to identify a series of time scales, which are observable in relaxation of cumulants on approach to the steady state. We test our findings on a very large set of historic financial markets data.

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Linda Shi and Susanne Moser

Science 29 Apr 2021: eabc8054
As climate change intensifies, civil society is increasingly calling for transformative adaptation that redresses drivers of climate vulnerability. We review trends in how U.S. federal government, private industry and civil society are planning for climate adaptation. We find growing divergence in their approaches and impacts. This incoherence increases maladaptive investment in climate-blind infrastructure, justice-blind reforms in financial and professional sectors, and greater societal vulnerability to climate impacts. If these actors were to proactively and deliberatively engage in transformative adaptation, they would need to address the material, relational and normative factors that hold current systems in place. Drawing on a review of transformation and collective impact literatures, we conclude with directions for research and policy engagement to support more transformative adaptation moving forward.

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Miquel Oliu-Barton, Bary S R Pradelski, Philippe Aghion, Patrick Artus, Ilona Kickbusch, Jeffrey V Lazarus, Devi Sridhar, Samantha Vanderslott

The Lancet

The trade-off between different objectives is at the heart of political decision making. Public health, economic growth, democratic solidarity, and civil liberties are important factors when evaluating pandemic responses. There is mounting evidence that these objectives do not need to be in conflict in the COVID-19 response. Countries that consistently aim for elimination—ie, maximum action to control SARS-CoV-2 and stop community transmission as quickly as possible—have generally fared better than countries that opt for mitigation—ie, action increased in a stepwise, targeted way to reduce cases so as not to overwhelm health-care systems.

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Gerardo Iñiguez, Carlos Pineda, Carlos Gershenson, Albert-László Barabási
Virtually anything can be and is ranked; people and animals, universities and countries, words and genes. Rankings reduce the components of highly complex systems into ordered lists, aiming to capture the fitness or ability of each element to perform relevant functions, and are being used from socioeconomic policy to knowledge extraction. A century of research has found regularities in ranking lists across nature and society when data is aggregated over time. Far less is known, however, about ranking dynamics, when the elements change their rank in time. To bridge this gap, here we explore the dynamics of 30 ranking lists in natural, social, economic, and infrastructural systems, comprising millions of elements, whose temporal scales span from minutes to centuries. We find that the flux governing the arrival of new elements into a ranking list reveals systems with identifiable patterns of stability: in high-flux systems only the top of the list is stable, while in low-flux systems the top and bottom are equally stable. We show that two basic mechanisms – displacement and replacement of elements – are sufficient to understand and quantify ranking dynamics. The model uncovers two regimes in the dynamics of ranking lists: a fast regime dominated by long-range rank changes, and a slow regime driven by diffusion. Our results indicate that the balance between robustness and adaptability characterizing the dynamics of complex systems might be governed by random processes irrespective of the details of each system.

Read the full article at: arxiv.org