This paper investigates an agent-based market model with a focus on social effects on agent behavior and market dynamics. To simulate these effects, widely used social network topologies from previous research were incorporated into the model. In this framework, agents select one belief from a set of possible beliefs, including fundamentalism, trend chasing, and interrupting strategies. Belief updating occurs based on two main factors: the historical performance of each agent’s own belief and the influence of other agents’ beliefs within the network. To formalize this process, a novel opinion formation model was developed, capturing the dynamic interactions among heterogeneous agents. The diversity of agent decisions generates market heterogeneity, reflecting realistic trading behavior. Simulation results demonstrate that returns across all social network topologies replicate key stylized facts observed in real financial markets. Furthermore, the findings highlight the significant impact of social interactions on price formation and market statistics, emphasizing the role of network structure in shaping market behavior. The proposed agent-based framework provides valuable insights into how individual decision-making and social influence jointly contribute to complex market phenomena, offering a robust tool for analyzing the interplay between agent heterogeneity, social effects, and emergent market properties.
Conte, R., & Paolucci, M. (2014). On agent-based modeling and computational social science. Frontiers in Psychology, 5, 668. https://doi.org/10.3389/fpsyg.2014.00668
Sornette, D. (2014). Physics and financial economics (1776–2014): Puzzles, Ising and agent-based models. Reports on Progress in Physics, 77(6), 062001. https://doi.org/10.1088/0034-4885/77/6/062001
Chen, S. H., Chang, C. L., & Du, Y. R. (2012). Agent-based economic models and econometrics. The Knowledge Engineering Review, 27(2), 187–219. https://doi.org/10.1017/S0269888912000136
Chakraborti, A., Toke, I. M., Patriarca, M., & Abergel, F. (2011). Econophysics review: II. Agent-based models. Quantitative Finance, 11(7), 1013–1041. https://doi.org/10.1080/14697688.2010.539249
Samanidou, E., Zschischang, E., Stauffer, D., & Lux, T. (2007). Agent-based models of financial markets. Reports on Progress in Physics, 70(3), 409–450. https://doi.org/10.1088/0034-4885/70/3/R03
Arthur, W. B. (2018). Asset pricing under endogenous expectations in an artificial stock market. In The economy as an evolving complex system II (pp. 31–60). CRC Press. https://doi.org/10.1201/9780429496639-2
Martinez-Jaramillo, S., & Tsang, E. P. (2009). A heterogeneous, endogenous and coevolutionary GP-based financial market. IEEE Transactions on Evolutionary Computation, 13(1), 33–55. https://doi.org/10.1109/TEVC.2008.2011401
Brock, W. A., & Hommes, C. H. (1997). A rational route to randomness. Econometrica, 65(5), 1059–1095. https://doi.org/10.2307/2171879
Brock, W. A., & Hommes, C. H. (1998). Heterogeneous beliefs and routes to chaos in a simple asset pricing model. Journal of Economic Dynamics and Control, 22(8–9), 1235–1274. https://doi.org/10.1016/S0165-1889(98)00011-6
Lux, T. (1995). Herd behaviour, bubbles and crashes. The Economic Journal, 105(431), 881–896. https://doi.org/10.2307/2235156
Lux, T. (1998). The socio-economic dynamics of speculative markets: Interacting agents, chaos, and the fat tails of return distributions. Journal of Economic Behavior & Organization, 33(2), 143–165. https://doi.org/10.1016/S0167-2681(97)00088-7
Kirman, A. (1991). Epidemics of opinion and speculative bubbles in financial markets. In Money and Financial Markets (pp. 17–31).
Kirman, A. (1993). Ants, rationality, and recruitment. The Quarterly Journal of Economics, 108(1), 137–156. https://doi.org/10.2307/2118498
Westerhoff, F. H. (2008). The use of agent-based financial market models to test the effectiveness of regulatory policies. Jahrbücher für Nationalökonomie und Statistik, 228(2–3), 195–227. https://doi.org/10.1515/jbnst-2008-2-305
Yeh, C. H., & Yang, C. Y. (2015). Social networks and asset price dynamics. IEEE Transactions on Evolutionary Computation, 19(3), 387–399. https://doi.org/10.1109/TEVC.2014.2322121
Alfarano, S., & Milaković, M. (2009). Network structure and N-dependence in agent-based herding models. Journal of Economic Dynamics and Control, 33(1), 78–92. https://doi.org/10.1016/j.jedc.2008.05.003
Panchenko, V., Gerasymchuk, S., & Pavlov, O. V. (2013). Asset price dynamics with heterogeneous beliefs and local network interactions. Journal of Economic Dynamics and Control, 37(12), 2623–2642. https://doi.org/10.1016/j.jedc.2013.06.015
Westerhoff, F. (2010). An agent-based macroeconomic model with interacting firms, socio-economic opinion formation and optimistic/pessimistic sales expectations. New Journal of Physics, 12(7), 075035. https://doi.org/10.1088/1367-2630/12/7/075035
Newman, M. E., & Watts, D. J. (1999). Scaling and percolation in the small-world network model. Physical Review E, 60(6), 7332–7342. https://doi.org/10.1103/PhysRevE.60.7332
Albert, R., Jeong, H., & Barabási, A. L. (1999). Internet: Diameter of the world-wide web. Nature, 401(6749), 130–131. https://doi.org/10.1038/43601
Schmitt, N., & Westerhoff, F. (2017). Heterogeneity, spontaneous coordination and extreme events within large-scale and small-scale agent-based financial market models. Journal of Evolutionary Economics, 27(5), 1041–1070. https://doi.org/10.1007/s00191-017-0504-x
Ariakia,H. , Ramezani,M. and Rajabzadeh Ghatari,A. (2021). An Agent-Based Market Simulation with Social Effects. Transactions on Data Analysis in Social Science, 3(1), 23-29. doi: 10.47176/TDASS/2021.23
MLA
Ariakia,H. , , Ramezani,M. , and Rajabzadeh Ghatari,A. . "An Agent-Based Market Simulation with Social Effects", Transactions on Data Analysis in Social Science, 3, 1, 2021, 23-29. doi: 10.47176/TDASS/2021.23
HARVARD
Ariakia H., Ramezani M., Rajabzadeh Ghatari A. (2021). 'An Agent-Based Market Simulation with Social Effects', Transactions on Data Analysis in Social Science, 3(1), pp. 23-29. doi: 10.47176/TDASS/2021.23
CHICAGO
H. Ariakia, M. Ramezani and A. Rajabzadeh Ghatari, "An Agent-Based Market Simulation with Social Effects," Transactions on Data Analysis in Social Science, 3 1 (2021): 23-29, doi: 10.47176/TDASS/2021.23
VANCOUVER
Ariakia H., Ramezani M., Rajabzadeh Ghatari A. An Agent-Based Market Simulation with Social Effects. TDASS, 2021; 3(1): 23-29. doi: 10.47176/TDASS/2021.23