Computational Model Library

Multi Asset Variable Network Stock Market Model (1.0.0)

The behavior of financial markets has, and continues, to frustrate investors and academics. With the advent of new approaches, including a complex systems framework, the search for an explanation as to how and why markets behavior as they do has greatly expanded. The use of agent-based models (ABMs) and the inclusion of network science has played an important role in increasing the relevance of the complex systems. Through the use of an artificial stock market utilizing an Ising model based agent-based model, this model is able to provide significant insight into the mechanisms that drive the returns in financial markets, including periods of elevated prices and excess volatility. In particular, the thesis demonstrates the following: the network topology that investors form; along with the dividend payout ratio of a stock significantly impact the behavior of the market. The model also investigates the impact of introducing multiple risky assets, something that has been absent in any previous models. By successfully addressing these issues this thesis has helped refine and shape a variety of further research tasks.

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Release Notes

Associated Publications

MARKET FLUCTUATIONS EXPLAINED BY DIVIDENDS AND INVESTOR NETWORKS
https://doi.org/10.1142/S0219525917500072

Introducing a Multi-Asset Stock Market to Test the Power of Investor Networks
http://jasss.soc.surrey.ac.uk/20/4/13.html

This release is out-of-date. The latest version is 1.1.0

Multi Asset Variable Network Stock Market Model 1.0.0

The behavior of financial markets has, and continues, to frustrate investors and academics. With the advent of new approaches, including a complex systems framework, the search for an explanation as to how and why markets behavior as they do has greatly expanded. The use of agent-based models (ABMs) and the inclusion of network science has played an important role in increasing the relevance of the complex systems. Through the use of an artificial stock market utilizing an Ising model based agent-based model, this model is able to provide significant insight into the mechanisms that drive the returns in financial markets, including periods of elevated prices and excess volatility. In particular, the thesis demonstrates the following: the network topology that investors form; along with the dividend payout ratio of a stock significantly impact the behavior of the market. The model also investigates the impact of introducing multiple risky assets, something that has been absent in any previous models. By successfully addressing these issues this thesis has helped refine and shape a variety of further research tasks.

Version Submitter First published Last modified Status
1.1.0 Matthew Oldham Tue Oct 10 17:50:03 2017 Tue Feb 20 13:34:39 2018 Published
1.0.0 Matthew Oldham Mon Sep 12 18:10:04 2016 Sat Feb 24 07:24:26 2018 Published

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