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

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Mario A. Bertella ◽  
Jonathas N. Silva ◽  
André L. Correa ◽  
Didier Sornette
Keyword(s):  
Social Networks ◽  
Asset Allocation ◽  
Stock Exchange ◽  
Small World ◽  
Small World Networks ◽  
Unequal Distribution ◽  
Volatility Clustering ◽  
Agent Based ◽  
Return Rates ◽  
Network Topologies

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.

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
Keyword(s):  
Social Networks ◽  
Stock Exchange ◽  
Agent Based Model ◽  
Agent Based

scholarly journals Switch between critical percolation modes in city traffic dynamics

2018 ◽  
Vol 116 (1) ◽  
pp. 23-28 ◽  
Author(s):  
Guanwen Zeng ◽  
Daqing Li ◽  
Shengmin Guo ◽  
Liang Gao ◽  
Ziyou Gao ◽  
...  
Keyword(s):  
High Speed ◽  
Small World ◽  
Real Data ◽  
Switching Behavior ◽  
Small World Networks ◽  
Critical Percolation ◽  
Percolation Transition ◽  
Traffic Dynamics ◽  
Network Topologies ◽  
Percolation Phenomena

Percolation transition is widely observed in networks ranging from biology to engineering. While much attention has been paid to network topologies, studies rarely focus on critical percolation phenomena driven by network dynamics. Using extensive real data, we study the critical percolation properties in city traffic dynamics. Our results suggest that two modes of different critical percolation behaviors are switching in the same network topology under different traffic dynamics. One mode of city traffic (during nonrush hours or days off) has similar critical percolation characteristics as small world networks, while the other mode (during rush hours on working days) tends to behave as a 2D lattice. This switching behavior can be understood by the fact that the high-speed urban roads during nonrush hours or days off (that are congested during rush hours) represent effective long-range connections, like in small world networks. Our results might be useful for understanding and improving traffic resilience.

scholarly journals The Efficiency of Active Asset Allocation Funds in the Period of Instability at Financial Markets

2012 ◽  
Vol 12 (2) ◽  
pp. 147-159
Author(s):  
Wojciech Krawiec
Keyword(s):  
Financial Markets ◽  
Asset Allocation ◽  
Stock Exchange ◽  
Investment Strategies ◽  
Investment Portfolio ◽  
Investment Funds ◽  
Financial Reports ◽  
Return Rates ◽  
Adequate Information ◽  
Online Investing

Abstract The objective of the hereby paper is the assessment of domestic active asset allocation funds efficiency in the period of 2007-2012, including the comparison of earned return rates against the return rates obtained by other mixed funds, as well as WIG and WIG20 stock exchange indices. Additionally, the purpose of the paper is to analyse the investment policy applied by the above listed funds, carried out based on records included in adequate information prospectuses, and also having considered the investment portfolio compositions presented in annual and 6-month financial reports covering these funds. The assessment of applied investment strategies efficiency is performed based on 12-, 24-, 36-, 48- and 60- month return rates set at the end of 6-month reporting periods. The analysis covered only domestic open-end active asset allocation investment funds included in this group following the definition accepted by Analizy Online investing assets in financial instruments issued by entities, officially seated in Poland or outside Poland and valuating participation units in PLN, which have been operating for at least 24 months from the day of 30th June 2012.

scholarly journals STRUCTURALLY DYNAMIC SPIN MARKET NETWORKS

2007 ◽  
Vol 18 (08) ◽  
pp. 1361-1374 ◽  
Author(s):  
DENIS HORVÁTH ◽  
ZOLTÁN KUSCSIK
Keyword(s):  
Complex Network ◽  
Stock Price ◽  
Small World ◽  
Stationary Regime ◽  
Volatility Clustering ◽  
Agent Based ◽  
Scale Free ◽  
Dynamic Spin ◽  
Feedback Connections ◽  
Market Networks

The agent-based model of stock price dynamics on a directed evolving complex network is suggested and studied by direct simulation. The stationary regime is maintained as a result of the balance between the extremal dynamics, adaptivity of strategic variables and reconnection rules. The inherent structure of node agent "brain" is modeled by a recursive neural network with local and global inputs and feedback connections. For specific parametric combination the complex network displays small-world phenomenon combined with scale-free behavior. The identification of a local leader (network hub, agent whose strategies are frequently adapted by its neighbors) is carried out by repeated random walk process through network. The simulations show empirically relevant dynamics of price returns and volatility clustering. The additional emerging aspects of stylized market statistics are Zipfian distributions of fitness.

Small-world networks and synchronisation in an agent-based model of civil violence

Global Crime ◽  
2019 ◽  
Vol 20 (3-4) ◽  
pp. 161-195
Author(s):  
Maria Fonoberova ◽  
Igor Mezić ◽  
Jadranka Mezić ◽  
James Hogg ◽  
Jason Gravel
Keyword(s):  
Small World ◽  
Small World Networks ◽  
Agent Based Model ◽  
Agent Based ◽  
Civil Violence

scholarly journals Modular hierarchical and power-law small-world networks bear structural optima for minimal first passage times and cover time

2019 ◽  
Vol 7 (6) ◽  
pp. 865-895 ◽  
Author(s):  
Benjamin F Maier ◽  
Cristián Huepe ◽  
Dirk Brockmann
Keyword(s):  
First Passage Time ◽  
Small World ◽  
Passage Time ◽  
Optimal Structure ◽  
Small World Networks ◽  
Cover Time ◽  
First Passage ◽  
Connection Probability ◽  
Network Topologies ◽  
Random Connectivity

Abstract Networks that are organized as a hierarchy of modules have been the subject of much research, mainly focusing on algorithms that can extract this community structure from data. The question of why modular hierarchical (MH) organizations are so ubiquitous in nature, however, has received less attention. One hypothesis is that MH topologies may provide an optimal structure for certain dynamical processes. We revisit a MH network model that interpolates, using a single parameter, between two known network topologies: from strong hierarchical modularity to an Erdős–Rényi random connectivity structure. We show that this model displays a similar small-world effect as the Kleinberg model, where the connection probability between nodes decays algebraically with distance. We find that there is an optimal structure, in both models, for which the pair-averaged first passage time (FPT) and mean cover time of a discrete-time random walk are minimal, and provide a heuristic explanation for this effect. Finally, we show that analytic predictions for the pair-averaged FPT based on an effective medium approximation fail to reproduce these minima, which implies that their presence is due to a network structure effect.

EPIDEMIOLOGY MODEL ON SHORTCUT AND SMALL WORLD NETWORKS

2009 ◽  
Vol 23 (10) ◽  
pp. 1249-1262 ◽  
Author(s):  
O. SHANKER ◽  
TAD HOGG
Keyword(s):  
Social Networks ◽  
Sensor Network ◽  
Computer Networks ◽  
Network Topology ◽  
Small World ◽  
Social Contagion ◽  
Small World Network ◽  
Small World Networks ◽  
Model Dependence ◽  
Human Animal

We show that the behavior of an epidemiology model depends sensitively on the shortcut density in the shortcut network. This is consistent with an earlier work on other processes on the shortcut network. We analytically study the reason for the sensitivity. The shortcut network is similar to the small world network, and it has the advantage that the model dependence on the shortcut density can be analytically studied. The model would be relevant to the spread of diseases in human, animal, plant or other populations, to the spread of viruses in computer networks, or to the spread of social contagion in social networks. It would also be relevant in understanding the variations in the load on routers connecting different computer networks, as the network topology gets extended by the addition of new links, and in analyzing the placement of certain special sensors in a sensor network laid out in a non-random way with some shortcut links.

Cartels as Small World Networks: Evidence from Graphite Electrode Cartel

2017 ◽  
Vol 16 (1) ◽  
pp. 27-61 ◽  
Author(s):  
Carlos J. Ponce ◽  
Flavia Roldán
Keyword(s):  
Social Networks ◽  
Conceptual Framework ◽  
Statistical Methods ◽  
Graphite Electrode ◽  
Small World ◽  
Small World Networks ◽  
Life Period

Abstract This article contributes to understanding the organization of collusive agreements by studying the inner-workings of the graphite electrode cartel. For this purpose: (i) we construct a database that comprises 49 meetings between 24 cartel members during the life period of the agreement, and (ii) we develop a conceptual framework that captures the affiliation of cartel members to meetings. Using statistical methods of social networks, we find that the cartel is organized around a few highly connected sub-networks that are close to each other.

Using Stranger Small World Networks for E-Marketing in Academia

2014 ◽  
pp. 192-230
Author(s):  
Shalin Hai-Jew
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Small World ◽  
Small World Networks ◽  
Crowd Sourcing ◽  
Virtual Collaboration ◽  
Development Team ◽  
Learning And Collaboration

In an institution of higher education, there are a number of projects that provide opportunities for online learning and collaboration. The success of a project often requires the participation of registered students, crowd-sourcing partners, Website visitors, and other types of virtual collaboration. To this end, many development teams use various forms of outreach to publicize the online degree, online credit course, short course, collaborative project, or call for project proposals (publication project). A common form of outreach involves the affordances of Social Web 2.0 connectivity: electronic marketing or e-marketing. The analysis of stranger small world networks enhances the efficacy of e-marketing endeavors by helping to identify individuals and social networks that may have a vested interest in a project; targeted outreach may enhance the low response rates from traditional “cold calls” and “break the ice” between people who may benefit from a bridge between each other’s social networks. Social network analysis may be applied to marketing to stranger social networks by helping a development team see which individuals and groups to target and what strategies to use—to expand the ties and capabilities of the development team and the university beyond known and familiar groups. This chapter includes some takeaway insights from the applied Social Network Analysis (SNA) and electronic SNA.

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