Displaying 10 of 599 results for "Ian M Hamilton" clear search
In this paper, we explore the dynamic of stock prices over time by developing an agent-based market. The developed artificial market comprises of heterogeneous agents occupied with various behaviors and trading strategies. To be specific, the agents in the market may expose to overconfidence, conservatism or loss aversion biases. Additionally, they may employ fundamental, technical, adaptive (neural network) strategies or simply being arbitrary agents (zero intelligence agents). The market has property of direct interaction. The environment takes the form of network structure, namely, it takes the manifestation of scale-free network. The information will flow between the agents through the linkages that connect them. Furthermore, the tax imposed by the regulator is investigated. The model is subjected to goodness of fit to the empirical observations of the S\&P500. The fitting of the model is refined by calibrating the model parameters through heuristic approach, particularly, scatter search. Conclusively, the parameters are validated against normality, absence of correlations, volatility cluster and leverage effect using statistical tests.
I’m a Senior Fellow at Fors Marsh who has a PhD in Industrial-Organizational Psychology and a PStat accreditation by the American Statistical Association.
Career Progression; Job Characteristics; Occupational Stress and Health
Doing research on how the flood insurance system in the UK should be structured in the future to make it resilient for environmental change.
Gary Polhill did a degree in Artificial Intelligence and a PhD in Neural Networks before spending 18 months in industry as a professional programmer. Since 1997 he has been working at the Institute on agent-based modelling of human-natural systems, and has worked on various international and interdisciplinary projects using agent-based modelling to study agricultural systems, lifestyles, and transitions to more sustainable ways of living. In 2016, he was elected President of the European Social Simulation Association, and was The James Hutton Institute’s 2017 Science Challenge Leader on Developing Technical and Social Innovations that Support Sustainable and Resilient Communities.
I haven’t research now.
Farzaneh Davari is a social science researcher who has worked in many diverse fields, including agriculture, conflict, health, and human rights, just to name a few. Currently, she is a Ph.D. candidate in Computational Social Science, focusing on social-ecological complex systems and applying computational science and Agent-Based Modeling to understand resilience procedure through self-organizing and learning. Meanwhile, she is a designer and instructor of the online graduate level course of Decision-making in Complex Environments in Virginia Tech.
Social-ecological complex system, resilience-building, conflictual environment
My field of interests concerns two axes:
First, epistemology of computational modeling and simulation of complex systems. I am particularly interested in a sociological inquiry about social implication of knowledge derived from complex systems’ study.
Second, assessing the possibilities and limits of studying social complexity with complex systems tools, particularly, agent-based modeling and simulation.
Displaying 10 of 599 results for "Ian M Hamilton" clear search