Analyzing the Role of Noise Trader in Financial Markets through Agent-Based Modelling

2014 ◽  
Author(s):  
Hiroshi Takahashi
Keyword(s):  
Financial Markets ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Noise Trader

Role of Agent Based Financial Market Models in Global Product Development

2008 ◽  
Author(s):  
Mario E. Inchiosa ◽  
Bipin Chadha
Keyword(s):  
Product Development ◽  
Financial Markets ◽  
Firm Growth ◽  
Ad Hoc ◽  
Random Number Generator ◽  
Agent Based ◽  
Stock Traders ◽  
Heavy Tailed ◽  
Non Gaussian

This paper describes the need for understanding the role of financial markets in successful product development in the global context. Agent-based models distinguish themselves by their ability to generate many real world phenomena endogenously, rather than as a result of ad-hoc assumptions. We report on a model of global financial markets employing the following agents: countries, firms, stock traders, country banks, and a global bank. These agents interact with goods, credit, currency, and stock markets. The model endogenously generated quantitative and qualitative features of real economies, including skewed firm sizes, skewed country GNP’s, skewed stock trader portfolio values, and heavy-tailed non-Gaussian firm growth rate, exchange rate fluctuation, and stock return distributions. Multiple runs were performed with different random number generator seeds to investigate the stability or instability of the economies grown by the model. Both stable and unstable country economies were detected. The multiple runs also verified conclusions drawn from analyzing individual runs showing how small countries could be buffeted by fluctuations in larger countries. Such a model can be used by product development organizations to understand the impacts of their product development decisions in the context of dynamic and unpredictable financial markets.

scholarly journals The role of responsiveness in deployment policies: A quantitative, cross-country assessment using agent-based modelling

2020 ◽  
Vol 275 ◽  
pp. 115358
Author(s):  
Alejandro Nuñez-Jimenez ◽  
Christof Knoeri ◽  
Fabian Rottmann ◽  
Volker H. Hoffmann
Keyword(s):  
Agent Based ◽  
Agent Based Modelling ◽  
Cross Country

scholarly journals Maintenance of prior behaviour can enhance cultural selection

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bradley Walker ◽  
José Segovia Martín ◽  
Monica Tamariz ◽  
Nicolas Fay
Keyword(s):  
Cultural Evolution ◽  
Learning Strategy ◽  
Critical Evaluation ◽  
Experimental Studies ◽  
Population Level ◽  
Agent Based ◽  
Cultural Selection ◽  
Agent Based Modelling ◽  
Cultural Evolutionary

AbstractMany cultural phenomena evolve through a Darwinian process whereby adaptive variants are selected and spread at the expense of competing variants. While cultural evolutionary theory emphasises the importance of social learning to this process, experimental studies indicate that people’s dominant response is to maintain their prior behaviour. In addition, while payoff-biased learning is crucial to Darwinian cultural evolution, learner behaviour is not always guided by variant payoffs. Here, we use agent-based modelling to investigate the role of maintenance in Darwinian cultural evolution. We vary the degree to which learner behaviour is payoff-biased (i.e., based on critical evaluation of variant payoffs), and compare three uncritical (non-payoff-biased) strategies that are used alongside payoff-biased learning: copying others, innovating new variants, and maintaining prior variants. In line with previous research, we show that some level of payoff-biased learning is crucial for populations to converge on adaptive cultural variants. Importantly, when combined with payoff-biased learning, uncritical maintenance leads to stronger population-level adaptation than uncritical copying or innovation, highlighting the importance of maintenance to cultural selection. This advantage of maintenance as a default learning strategy may help explain why it is a common human behaviour.

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