Skip to main content

Network of Networks: A Meta-model for Simulated Financial Markets

  • Conference paper
  • First Online:
Complex Networks & Their Applications V (COMPLEX NETWORKS 2016 2016)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 693))

Included in the following conference series:

Abstract

We investigate the properties of a calibrated network structure of an agent-based model for a simulated financial market. A meta-model of a network of networks is introduced to capture the simulated market structure. The agent-based model consists of heterogeneous agents characterized by two-dimensional attributes that are investment behavior and investment strategy. The resulting groups of agents are viewed as subnetworks giving rise to a network of networks (NoN). The aggregation of activities of agents in a subnetwork trickles up to shape the aggregate activities of the NoN. The objective of introducing the NoN is to provide a testbed for complex models of simulated markets. Furthermore, we investigate the emergence of the market patterns in terms of prices, moments of returns, market capital, and wealth distributions. The investigation was performed for fully connected homogeneous agents. The results show a significant difference in the market emergence behaviors in terms of prices and returns, however, the market capitalization stays close to the calibrated financial market. Also, the deviation of wealth distributions was less than those in the heterogeneous market.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 329.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Alsulaiman, T., Khashanah, K.: Bounded rational heterogeneous agents in artificial stock markets: Literature review and research direction. International Journal of Social, Behavioral, Educational, Economic and Management Engineering 9, 2038–2057 (2015)

    Google Scholar 

  2. Arthur, W.B., Holland, J.H., LeBaron, B., Palmer, R.G., Tayler, P.: Asset pricing under endogenous expectations in an artificial stock market. Available at SSRN 2252 (1996)

    Google Scholar 

  3. Barabási, B.A.L., Bonabeau, E.: Scale-free. Scientific American (2003)

    Google Scholar 

  4. Bertella, M.A., Pires, F.R., Feng, L., Stanley, H.E.: Confidence and the stock market: An agent-based approach. PloS one 9(1), e83,488 (2014)

    Google Scholar 

  5. Brock, W.A., Hommes, C.H.: A rational route to randomness. Econometrica: Journal of the Econometric Society pp. 1059–1095 (1997)

    Google Scholar 

  6. Brock, W.A., Hommes, C.H.: Heterogeneous beliefs and routes to chaos in a simple asset pricing model. Journal of Economic dynamics and Control 22(8), 1235–1274 (1998)

    Google Scholar 

  7. Chan, N.T., LeBaron, B., Lo, A.W., Poggio, T., Yy, A.W.L., Zz, T.P.: Agent-based models of financial markets: A comparison with experimental markets. Citeseer (1999)

    Google Scholar 

  8. Derveeuw, J.: Market dynamics and agents behaviors: a computational approach. In: Artificial Economics, pp. 15–26. Springer (2006)

    Google Scholar 

  9. Donges, J.F., Schultz, H.C., Marwan, N., Zou, Y., Kurths, J.: Investigating the topology of interacting networks. The European Physical Journal B 84(4), 635–651 (2011)

    Google Scholar 

  10. Eppstein, D., Löffler, M., Strash, D.: Listing all maximal cliques in sparse graphs in nearoptimal time. In: International Symposium on Algorithms and Computation, pp. 403–414. Springer (2010)

    Google Scholar 

  11. Frankel, J.A., Froot, K.A.: Explaining the demand for dollars: International rates of return and the expectations of chartists and fundamentalists. Department of Economics, UCB (1986)

    Google Scholar 

  12. Freeman, L.C.: Centrality in social networks conceptual clarification. Social networks 1(3), 215–239 (1978)

    Google Scholar 

  13. Gao, J., Buldyrev, S.V., Havlin, S., Stanley, H.E.: Robustness of a network of networks. Physical Review Letters 107(19), 195,701 (2011)

    Google Scholar 

  14. Gode, D.K., Sunder, S.: Allocative efficiency of markets with zero-intelligence traders: Market as a partial substitute for individual rationality. Journal of political economy pp. 119–137 (1993)

    Google Scholar 

  15. Hommes, C.H.: Heterogeneous agent models in economics and finance. Handbook of computational economics 2, 1109–1186 (2006)

    Google Scholar 

  16. Kahneman, D., Tversky, A.: Prospect theory: An analysis of decision under risk. Econometrica: Journal of the econometric society pp. 263–291 (1979)

    Google Scholar 

  17. Khashanah, K., Alsulaiman, T.: Network theory and behavioral finance in a heterogeneous market environment. Complexity (2016)

    Google Scholar 

  18. Kim, G.r., Markowitz, H.M.: Investment rules, margin, and market volatility. The Journal of Portfolio Management 16(1), 45–52 (1989)

    Google Scholar 

  19. Kivelä, M., Arenas, A., Barthelemy, M., Gleeson, J.P., Moreno, Y., Porter, M.A.: Multilayer networks. Journal of complex networks 2(3), 203–271 (2014)

    Google Scholar 

  20. Laguna, M., Marti, R.: The optquest callable library. In: Optimization Software Class Libraries, pp. 193–218. Springer (2003)

    Google Scholar 

  21. Laguna, M., Marti, R.: Scatter search: methodology and implementations in C, vol. 24. Springer Science & Business Media (2012)

    Google Scholar 

  22. LeBaron, B.: Agent-based computational finance. Handbook of computational economics 2, 1187–1233 (2006)

    Google Scholar 

  23. Martinez-Jaramillo, S., Tsang, E.P.: An heterogeneous, endogenous and coevolutionary gp-based financial market. IEEE Transactions on Evolutionary Computation 13(1), 33–55 (2009)

    Google Scholar 

  24. Newman, M.E.: Assortative mixing in networks. Physical review letters 89(20), 208,701 (2002)

    Google Scholar 

  25. Newman, M.E.: Mixing patterns in networks. Physical Review E 67(2), 026,126 (2003)

    Google Scholar 

  26. Palmer, R.G., Arthur, W.B., Holland, J.H., LeBaron, B., Tayler, P.: Artificial economic life: a simple model of a stockmarket. Physica D: Nonlinear Phenomena 75(1), 264–274 (1994)

    Google Scholar 

  27. Panchenko, V., Gerasymchuk, S., Pavlov, O.V.: Asset price dynamics with heterogeneous beliefs and local network interactions. Journal of Economic Dynamics and Control 37(12), 2623–2642 (2013)

    Google Scholar 

  28. Takahashi, H., Terano, T.: Agent-based approach to investors’ behavior and asset price fluctuation in financial markets. Journal of artificial societies and social simulation 6(3) (2003)

    Google Scholar 

  29. Wang, Y., Xiao, G.: Effects of interconnections on epidemics in network of networks. In:Wireless Communications, Networking and Mobile Computing (WiCOM), 2011 7th International Conference on, pp. 1–4. IEEE (2011)

    Google Scholar 

  30. Wasserman, S., Faust, K.: Social network analysis: Methods and applications, vol. 8. Cambridge university press (1994)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Talal Alsulaiman .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Alsulaiman, T., Khashanah, K. (2017). Network of Networks: A Meta-model for Simulated Financial Markets. In: Cherifi, H., Gaito, S., Quattrociocchi, W., Sala, A. (eds) Complex Networks & Their Applications V. COMPLEX NETWORKS 2016 2016. Studies in Computational Intelligence, vol 693. Springer, Cham. https://doi.org/10.1007/978-3-319-50901-3_53

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-50901-3_53

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50900-6

  • Online ISBN: 978-3-319-50901-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics