scholarly journals Tropical forest dynamics correspond to fair games in economic theory of financial markets

2021 ◽  
Author(s):  
Yue Lin ◽  
James Rosindell ◽  
Uta Berger ◽  
Helge Bruelheide ◽  
Jens Kattge ◽  
...  

Ecological and economic systems both comprise of autonomous adaptive agents. It is thus possible that similar mechanisms determine the organization of both these complex systems. Indeed several economic theories have already been successfully applied in an ecological context. Here we show that 'efficient market theory' in economics, where future earnings are distributed between competitors by a 'fair game', corresponds to fitness-equalizing mechanisms of coexistence in ecology. In contrast to stabilizing mechanisms, which promote coexistence by giving each species an equilibrium abundance that is resilient to perturbations, equalizing mechanisms promote coexistence without such resilience by minimizing the net fitness differences between species. However, identifying stabilizing and equalizing mechanisms from the short time-series data that are typically available in ecology is challenging. We used techniques from economics that are applied to collections of short time-series from a system. We found that observed species abundance dynamics in a neotropical forest are generally in agreement with efficient market theory implying a dominant role of equalizing mechanisms, which finding quantifies and supports what was generally believed about that specific forest system. Our study highlights that complex systems from ecology and economics share common features suggesting the possibility of further synergy between ecology and economics in future.

Fractals ◽  
2020 ◽  
Vol 28 (08) ◽  
pp. 2040017
Author(s):  
SHAOFEI WU

Users use the network more and more frequently, and more and more data is published on the network. Therefore, how to find, organize, and use the useful information behind these massive data through effective means, and analyze user intentions is a huge challenge. There are many time series problems in user intentions. Time series have complex characteristics such as randomness and multi-scale variability. Effectively identifying the inherent laws and objective phenomena contained in time series is the purpose of analyzing and processing time series data. Fractal theory provides a new way to analyze time series, and obtains the characteristics and rules of time series from a new perspective. Therefore, this paper introduces the fractal theory to analyze the time series problem, and proposes an improved G-P algorithm to realize the prediction and mining of user intentions. First, the method of array storage instead of repeated calculations is used to improve the method of saturated correlation dimension. Second, the Hurst exponent of the time series is obtained by the variable scale range analysis method. Finally, a fractal model for predicting user intent in short time series is established using the accumulation and transformation method. The experimental results show that the use of fractal theory can effectively describe the relevant characteristics of time series, the development trend of user intentions can be mined from big data, and the prediction model for short time series can be established to achieve information mining of user intentions.


2006 ◽  
Vol 7 (S2) ◽  
Author(s):  
Andrey A Ptitsyn ◽  
Sanjin Zvonic ◽  
Jeffrey M Gimble

2007 ◽  
Vol 8 (1) ◽  
Author(s):  
Andrey A Ptitsyn ◽  
Sanjin Zvonic ◽  
Jeffrey M Gimble

2017 ◽  
Vol 11 (S7) ◽  
Author(s):  
Ben-gong Zhang ◽  
Weibo Li ◽  
Yazhou Shi ◽  
Xiaoping Liu ◽  
Luonan Chen

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