scholarly journals Corrigendum to “The Influence of Confidence and Social Networks on an Agent-Based Model of Stock Exchange”

Complexity ◽  
2022 ◽  
Vol 2022 ◽  
pp. 1-1
Author(s):  
Mario A. Bertella ◽  
Jonathas N. Silva ◽  
André L. Correa ◽  
Didier Sornette

2007 ◽  
Vol 60 (3) ◽  
pp. 589-610 ◽  
Author(s):  
Adam Korobow ◽  
Chris Johnson ◽  
Robert Axtell

2019 ◽  
Vol 28 (4) ◽  
pp. 394-412 ◽  
Author(s):  
Björn Ross ◽  
Laura Pilz ◽  
Benjamin Cabrera ◽  
Florian Brachten ◽  
German Neubaum ◽  
...  

2020 ◽  
Author(s):  
Giuseppe Giacopelli

UNSTRUCTURED COVID-19 outbreak is an awful event. However it gives to the scientists the possibility to test theories about epidemic. The aim of this contribution is to propose a individual-based model of Lombardy COVID-19 outbreak at full-scale, where full-scale means that will be simulated all the 10 millions inhabitant population of Lombardy person by person, in a commercial computer. All this to test the impact of our daily actions in epidemic, investigate social networks connectivity and in the end have an insight on the impact of an hypothetical vaccine.


Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-10
Author(s):  
Jun Pan ◽  
Huizhang Shen ◽  
Zhong Chen

Mass incidents, which may influence the stability and security of the society in China, are getting more and more attentions not only from policy makers but also from Chinese social researchers. Catching the diffusion mechanism is believed to be critical to understand essential of these mass incidents since message dissemination plays important roles in every stage of mass incident. Recently, online social networks including Weibo (Chinese Twitter) become more and more popular in China. There are reports showing that Weibo discussion has accompanied the processes of most mass incidents happening in China in these few years. So, in this paper, we aim at introducing K-Core decomposition method from complex network to the analysis on how to manage the diffusion of mass incident in Weibo based on agent based model which can simulate Weibo user’s actions when mass incident happens. This work can help people understand how mass incident messages spread across the network. And then, people may have better strategy to manage the diffusion of mass incidents.


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Mario A. Bertella ◽  
Jonathas N. Silva ◽  
André L. Correa ◽  
Didier Sornette

This paper aims to investigate the influence of investors’ confidence in their portfolio holding relative to their social group and of various social network topologies on the dynamics of an artificial stock exchange. An investor’s confidence depends on the growth rate of his or her wealth relative to his or her social group’s average wealth. If the investor’s confidence is low, the agent will change his or her asset allocation; otherwise, he or she will maintain it. We consider three types of social networks: Barabási, small-world, and random. The actual stock markets’ properties are recovered by this model: high excess kurtosis, skewness, volatility clustering, random walk prices, and stationary return rates. The networks’ topologies are found to impact both the structuration of investors in the space of strategies and their performance. Among other characteristics, we find that (i) the small-world networks show the highest degree of homophily; (ii) as investors can switch to more profitable strategies, the best approach to make profitable investments is the chartist one in Barabási and small-world topologies; and (iii) an unequal distribution and more significant relative wealth gains occur in the Barabási network.


2010 ◽  
Vol 8 (13) ◽  
pp. 37-42 ◽  
Author(s):  
PN Kumar ◽  
Rahul.G Seshadri ◽  
A Hariharan. ◽  
VP Mohandas

2013 ◽  
Vol 11 (1) ◽  
pp. 51-70 ◽  
Author(s):  
Andreas Koulouris ◽  
Ioannis Katerelos ◽  
Theodore Tsekeris

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