Transaction tax, heterogeneous traders and market volatility

Kybernetes ◽  
2015 ◽  
Vol 44 (5) ◽  
pp. 757-770
Author(s):  
Hongquan LI ◽  
Gang Cheng ◽  
Shouyang Wang
Keyword(s):  
Agent Based Modeling ◽  
Market Volatility ◽  
Market Model ◽  
Comprehensive Understanding ◽  
Adaptive Agents ◽  
Content Type ◽  
Agent Based ◽  
Securities Transaction Tax ◽  
Market Stabilization ◽  
Transaction Tax

Purpose – The securities transaction tax (STT) has been theoretically considered as an important regulation device for decades. However, its role and effectiveness in financial markets is still not well understood both theoretically and empirically. By use of agent-based modeling method, the purpose of this paper is to present a new artificial stock market model with self-adaptive agents, which allows the assessment of the impacts from various levels of STTs in distinctive market environments and thus a comprehensive understanding of the effects of STTs is achieved. Design/methodology/approach – In the model, agents are allowed to employ the strategies used by the following five types of investors: contrarians, random traders, momentum traders, fundamentalists and exit strategy holders. Specifically, the authors start with the investigation of the dynamics of a tax free benchmark market; then the patterns of market behaviors and the behaviors of various types of investors are discussed with different levels of STTs in markets with mild and high fluctuations. Findings – The simulation results consistently show that a moderate transaction tax does contribute to market stabilization in terms of reducing market volatility while with a price of mild decrease of market efficiency and liquidity. The findings suggest that a balance between market stability and efficiency could be reached if regulatory authorities introduce STTs to markets discreetly. Originality/value – This paper enriches the comprehensive understanding of the effects of STT, and gives good explanation about the controversy between Tobin’s proponents and anti-Tobin group.

scholarly journals Agent-Based Modeling Demonstrates How Local Chemotactic Behavior Can Shape Biofilm Architecture

mSphere ◽  
2019 ◽  
Vol 4 (3) ◽  
Author(s):  
Emily G. Sweeney ◽  
Andrew Nishida ◽  
Alexandra Weston ◽  
Maria S. Bañuelos ◽  
Kristin Potter ◽  
...  
Keyword(s):  
Helicobacter Pylori ◽  
Three Dimensional ◽  
Structural Features ◽  
Agent Based Modeling ◽  
Emergent Properties ◽  
Cellular Interactions ◽  
Biofilm Growth ◽  
Content Type ◽  
Agent Based ◽  
H Pylori

ABSTRACTBacteria are often found living in aggregated multicellular communities known as biofilms. Biofilms are three-dimensional structures that confer distinct physical and biological properties to the collective of cells living within them. We used agent-based modeling to explore whether local cellular interactions were sufficient to give rise to global structural features of biofilms. Specifically, we asked whether chemorepulsion from a self-produced quorum-sensing molecule, autoinducer-2 (AI-2), was sufficient to recapitulate biofilm growth and cellular organization observed for biofilms ofHelicobacter pylori, a common bacterial resident of human stomachs. To carry out this modeling, we modified an existing platform, Individual-based Dynamics of Microbial Communities Simulator (iDynoMiCS), to incorporate three-dimensional chemotaxis, planktonic cells that could join or leave the biofilm structure, and cellular production of AI-2. We simulated biofilm growth of previously characterizedH. pyloristrains with various AI-2 production and sensing capacities. Using biologically plausible parameters, we were able to recapitulate both the variation in biofilm mass and cellular distributions observed with these strains. Specifically, the strains that were competent to chemotax away from AI-2 produced smaller and more heterogeneously spaced biofilms, whereas the AI-2 chemotaxis-defective strains produced larger and more homogeneously spaced biofilms. The model also provided new insights into the cellular demographics contributing to the biofilm patterning of each strain. Our analysis supports the idea that cellular interactions at small spatial and temporal scales are sufficient to give rise to larger-scale emergent properties of biofilms.IMPORTANCEMost bacteria exist in aggregated, three-dimensional structures called biofilms. Although biofilms play important ecological roles in natural and engineered settings, they can also pose societal problems, for example, when they grow in plumbing systems or on medical implants. Understanding the processes that promote the growth and disassembly of biofilms could lead to better strategies to manage these structures. We had previously shown thatHelicobacter pyloribacteria are repulsed by high concentrations of a self-produced molecule, AI-2, and thatH. pylorimutants deficient in AI-2 sensing form larger and more homogeneously spaced biofilms. Here, we used computer simulations of biofilm formation to show that localH. pyloribehavior of repulsion from high AI-2 could explain the overall architecture ofH. pyloribiofilms. Our findings demonstrate that it is possible to change global biofilm organization by manipulating local cell behaviors, which suggests that simple strategies targeting cells at local scales could be useful for controlling biofilms in industrial and medical settings.

Use of a sonification system for science learning by people who are blind

2016 ◽  
Vol 10 (4) ◽  
pp. 187-198 ◽  
Author(s):  
Orly Lahav ◽  
Nuha Chagab ◽  
Vadim Talis
Keyword(s):  
Complex Systems ◽  
Conceptual Knowledge ◽  
Science Curriculum ◽  
Low Cost ◽  
Agent Based Modeling ◽  
Learning System ◽  
Learning Ability ◽  
Content Type ◽  
Agent Based ◽  
K 12

Purpose The purpose of this paper is to examine a central need of students who are blind: the ability to access science curriculum content. Design/methodology/approach Agent-based modeling is a relatively new computational modeling paradigm that models complex dynamic systems. NetLogo is a widely used agent-based modeling language that enables exploration and construction of models of complex systems by programming and running the rules and behaviors. Sonification of variables and events in an agent-based NetLogo computer model of gas in a container is used to convey phenomena information. This study examined mainly two research topics: the scientific conceptual knowledge and systems reasoning that were learned as a result of interaction with the listen-to-complexity (L2C) environment as appeared in answers to the pre- and post-tests and the learning topics of kinetic molecular theory of gas in chemistry that was learned as a result of interaction with the L2C environment. The case study research focused on A., a woman who is adventitiously blind, for eight sessions. Findings The participant successfully completed all curricular assignments; her scientific conceptual knowledge and systems reasoning became more specific and aligned with scientific knowledge. Practical implications A practical implication of further studies is that they are likely to have an impact on the accessibility of learning materials, especially in science education for students who are blind, as equal access to low-cost learning environments that are equivalent to those used by sighted users would support their inclusion in the K-12 academic curriculum. Originality/value The innovative and low-cost learning system that is used in this research is based on transmittal of visual information of dynamic and complex systems, providing perceptual compensation by harnessing auditory feedback. For the first time the L2C system is based on sound that represents a dynamic rather than a static array. In this study, the authors explore how a combination of several auditory representations may affect cognitive learning ability.

Facilitating organizational learning through agent-based modeling and simulation experimentation

2016 ◽  
Vol 23 (6) ◽  
pp. 429-443 ◽  
Author(s):  
Saša Baškarada ◽  
Arvind Chandran ◽  
Mina Shokr ◽  
Christopher Stewart
Keyword(s):  
Organizational Learning ◽  
Modeling And Simulation ◽  
Agent Based Modeling ◽  
Knowledge Generation ◽  
Generation Process ◽  
Complex Environments ◽  
Content Type ◽  
Agent Based ◽  
Internal Knowledge

Purpose In addition to requiring high absorptive capacity, contemporary organizations operating in highly dynamic and complex environments also require the ability to create knowledge internally, within the organization. While the organizational learning (OL) literature has produced a plethora of theories and frameworks, there has been relatively little empirical research on specific mechanisms for internal knowledge generation. Accordingly, this paper aims to answer calls for more research on mechanisms for internal generation of organizational knowledge. Design/methodology/approach This paper is an in-depth case study in the Australian Defence Organisation (ADO). Findings The paper presents a cyclical eight-stage knowledge generation process and demonstrates how agent-based modeling and simulation (ABMS) may be used to facilitate OL. Originality/value By detailing an in-depth case study of an ABMS mechanism for internal knowledge generation in the ADO, this paper provides a novel and relevant contribution to the OL literature.

scholarly journals Investigating dynamics of COVID-19 spread and containment with agent-based modeling

2020 ◽  
Author(s):  
Amirarsalan Rajabi ◽  
Alexander V. Mantzaris ◽  
Ece C. Mutlu ◽  
Ivan Garibay
Keyword(s):  
Agent Based Modeling ◽  
Contact Tracing ◽  
Model Description ◽  
Test Bed ◽  
Comprehensive Understanding ◽  
Policy Makers ◽  
Agent Based ◽  
Epidemic Curve ◽  
Travel Restrictions ◽  
Travel Restriction

AbstractGovernments, policy makers and officials around the globe are trying to mitigate the effects and progress of the COVID-19 pandemic by making decisions which will save the most lives and impose the least costs. Making these decisions needs a comprehensive understanding about the dynamics by which the disease spreads. In this work, we propose an epidemic agent-based model that simulates the spread of the disease. We show that the model is able to generate an important aspect of the pandemic: multiple waves of infection. A key point in the model description is the aspect of ’fear’ which can govern how agents behave under different conditions. We also show that the model provides an appropriate test-bed to apply different containment strategies and this work presents the results of applying two such strategies: testing, contact tracing, and travel restriction. The results show that while both strategies could result in flattening the epidemic curve and significantly reduce the maximum number of infected individuals; testing should be applied along with tracing previous contacts of the tested individuals to be effective. The results show how the curve is flattened with testing partnered with contact tracing, and the imposition of travel restrictions.

scholarly journals Understanding Lactobacillus paracasei and Streptococcus oralis Biofilm Interactions through Agent-Based Modeling

mSphere ◽  
2021 ◽  
Author(s):  
Linda Archambault ◽  
Sherli Koshy-Chenthittayil ◽  
Angela Thompson ◽  
Anna Dongari-Bagtzoglou ◽  
Reinhard Laubenbacher ◽  
...  
Keyword(s):  
Biofilm Formation ◽  
Oral Candidiasis ◽  
Agent Based Modeling ◽  
Cell Models ◽  
Complex Environments ◽  
Inhibitory Effects ◽  
Content Type ◽  
Agent Based ◽  
Streptococcus Oralis

We previously discovered a role of the oral commensal Streptococcus oralis as an accessory pathogen. S. oralis increases the virulence of Candida albicans infections in murine oral candidiasis and epithelial cell models through mechanisms which promote the formation of tissue-damaging biofilms. Lactobacillus species have known inhibitory effects on biofilm formation of many microbes, including Streptococcus species. Agent-based modeling has great advantages as a means of exploring multifaceted relationships between organisms in complex environments such as biofilms.

Crowd-shipping for urban food rescue logistics

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anuj Mittal ◽  
Nilufer Oran Gibson ◽  
Caroline C. Krejci ◽  
Amy Ann Marusak
Keyword(s):  
Feedback Loop ◽  
Network Effects ◽  
Critical Mass ◽  
Dynamic Network ◽  
Adaptive Agents ◽  
Content Type ◽  
Agent Based ◽  
And Performance ◽  
Participation Decisions ◽  
Over Time

PurposeThe purpose of this research is to gain a better understanding of how a crowd-shipping platform can achieve a critical mass of senders and carrier crowd members to yield network effects that are necessary for the platform to grow and thrive. Specifically, this research studies the participation decisions of both senders and carriers over time and the impacts of the resulting feedback loop on platform growth and performance.Design/methodology/approachAn agent-based model is developed and used to study dynamic behavior and network effects within a simulated crowd-shipping platform. The model allows both carriers and senders to be represented as autonomous, heterogeneous and adaptive agents, whose decisions to participate in the platform impact the participation of other agents over time. Survey data inform the logic governing agent decisions and behaviors.FindingsThe feedback loop created by individual sender and carrier agents' participation decisions generates complex and dynamic network effects that are observable at the platform level. Experimental results demonstrate the importance of having sufficient crowd carriers available when the platform is initially launched, as well as ensuring that sender and carrier participation remains balanced as the platform grows over time.Research limitations/implicationsThe model successfully demonstrates the power of agent-based modeling (ABM) in analyzing network effects in crowd-shipping systems. However, the model has not yet been fully validated with data from a real-world crowd-shipping platform. Furthermore, the model's geographic scope is limited to a single census tract. Platform behavior will likely differ across geographic regions, with varying demographics and sender/carrier density.Practical implicationsThe modeling approach can be used to provide the manager of a volunteer-based crowd-shipping program for food rescue with insights on how to achieve a critical mass of participants, with an appropriate balance between the number of restaurant food donation delivery requests and the number of crowd-shippers available and willing to make those deliveries.Social implicationsThis research can help a crowd-shipping platform for urban food rescue to grow and become self-sustainable, thereby serving more food-insecure people.Originality/valueThe model represents both senders and the carrier crowd as autonomous, heterogeneous and adaptive agents, such that network effects resulting from their interactions can emerge and be observed over time. The model was designed to study a volunteer crowd-shipping platform for food rescue, with participant motivations driven by personal values and social factors, rather than monetary incentives.

On the contributions and the validation of an agent-based simulation model of innovation diffusion

2016 ◽  
Vol 50 (3/4) ◽  
pp. 647-657 ◽  
Author(s):  
Mohammad G. Nejad
Keyword(s):  
Simulation Modeling ◽  
Agent Based Modeling ◽  
Test Theory ◽  
Future Research ◽  
Agent Based Simulation ◽  
Content Type ◽  
Agent Based ◽  
Points Of View ◽  
Complex Phenomena ◽  
Specific Paper

Purpose This paper provides an overview of agent-based modeling and simulation (ABMS) and evaluates the questions that have been raised regarding the “assumptions and mechanisms used” by a well-cited paper that has used this methodology. Design/methodology/approach This work provides a review of agent-based simulation modeling and its capabilities to advance and test theory. The commentary then evaluates and addresses the raised questions and reservations. Findings Agent-based modeling offers unique capabilities that can be used to explore complex phenomena in business and marketing. Some of the raised reservations may be considered as directions for future research. However, the criticisms are for most part unsupported by existing research and do not undermine the contributions of the paper that is being discussed. Practical implications Given its relative novelty, reservations regarding agent-based simulation modeling are quite natural. Discussions like this one would bring together different points of view and lead to a better understanding of how using ABMS can benefit academia and industry. Originality/value This commentary is part of an intellectual dialogue that seeks to provide different points of view about agent-based simulation modeling using a specific paper as an example.

scholarly journals Improving agent-based models of diffusion

2016 ◽  
Vol 50 (3/4) ◽  
pp. 639-646 ◽  
Author(s):  
Robert East ◽  
Mark D. Uncles ◽  
Jenni Romaniuk ◽  
Wendy Lomax
Keyword(s):  
Design Methodology ◽  
Agent Based Modeling ◽  
Diffusion Modeling ◽  
Agent Based Models ◽  
Content Type ◽  
Agent Based ◽  
Made In

Purpose This paper aims to review the validation of assumptions made in agent-based modeling of diffusion and the sufficiency (completeness) of the mechanisms assumed to operate. Design/methodology/approach One well-cited paper is examined. Findings Evidence is presented that casts doubt on the assumptions and mechanisms used. A range of mechanisms is suggested that should be evaluated for inclusion in diffusion modeling. Originality/value The need for validation of assumptions has been stressed elsewhere but there has been a lack of examples. This paper provides examples. The stress on the sufficiency of the mechanisms used is new.

New developments in financial economics

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Thomas D. Willett
Keyword(s):  
Behavioral Finance ◽  
Financial Economics ◽  
Recent Literature ◽  
Agent Based Modeling ◽  
New Developments ◽  
Content Type ◽  
Agent Based ◽  
New Approaches ◽  
New Methodologies ◽  
Practical Implications

Purpose This study aims to critically review recent contributions to the methodology of financial economics and discuss how they relate to one another and directions for further research. Design/methodology/approach A critical review of recent literature on new methodologies for financial economics. Findings Recent books have made important contributions to the study of financial economics. They suggest new approaches that include an emphasis on radical uncertainty, adaptive markets, agent-based modeling and narrative economics, as well as extensions of behavioral finance to include concepts such as diagnostic expectations. Many of these contributions can be seen more as complements than substitutes and provide fruitful directions for further research. Efficient markets can be seen as holding under particular circumstances. A major them of most of these contributions is that the study of financial crises and other aspects of financial economics requires the use of multiple theories and approaches. No one approach will be sufficient. Research limitations/implications There are great opportunities for further research in financial economics making use of these new approaches. Practical implications These recent contributions can be quite useful for improved analysis by researchers, private participants in the financial sector and macroeconomic and regulatory officials. Originality/value Provides an introduction to these new approaches and highlights fruitful areas for their extensions and applications.

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