Abstract
In recent years, there has been rising interest in a field called behavioral finance, which incorporates psychological methods in analysing investor behavior. The aim of this chapter is to study the technical and the fundamental investing strategy of financial market participants dealing with assets. The motivation of the presented research is to simulate the financial market in the form of agent-based model and to investigate various impacts of risk and transaction costs on its stability. Computational social science involves the use of agent based modeling and simulation to study complex social systems. It is related to a variety of other simulation techniques, including discrete event simulation and distributed artificial intelligence or Multi-Agent Systems (MAS). In practice, each agent has only partial knowledge of other agents and each agent makes its own decisions based on the partial knowledge about other agents in the system. For purposes of this chapter, a MAS will be implemented as a simulation framework in JADE development platform. The hypothesis was that transaction costs introduction will stabilize the financial market. The results obtained show that in the case of risk involvement into the system the hypothesis can be fulfilled only partially.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Sharpe, W.F.: Capital asset prices: a theory of market equilibrium under condition of risk. J. Financ. 19, 425–442 (1964)
Shiller, R.J.: Irrational Exuberance. Princeton University Press, Princeton (2000)
Shleifer, A.: Inefficient Markets. Oxford University Press, Oxford (2000)
Tversky, A., Kahneman, D.: Advances in prospect theory: cumulative representation of Uncertainty. J. Risk Uncertainty 5, 297–323 (1992)
Kaegi, M.: Risk analysis of information systems by agent-based modeling of business processes. Disertation, Swiss Federal Institute of Technology, Zurrich (2009)
Epstein, J.M., Axtell, R.: Growing Artificial Societies: Social Science from the Bottom Up. Brookings Institution Press, Washington, DC (1996). ISBN 0-262-55025-3
Law, A.M., Kelton, W.D.: Simulation Modeling and Analysis, 3rd edn. McGraw-Hill, New York (2000). ISBN 0070592926
Pritsker, A.A.B.: Introduction to Simulation and SLAM II. Wiley, New York (1995). ISBN 0470234571
Sallach, D.L., Macal, C.M.: Introduction: the simulation of social agents. Soc. Sci. Comput. Rev. 19(3), 15–29 (2001). Sage Publications, Thousand Oaks, CA
Tesfatsion, L.: Agent-based computational economics: growing economies from the bottom up. Artif. Life 8(1), 55–82 (2002). MIT Press, Cambridge, MA
Conzelmann, G., North, M., Boyd, G., Cirillo, R., Koritarov, V., Macal, Ch., Thimmapuram, P., Veselka, T.: Simulating strategic market behavior using an agent-based modeling approach. In: Result of a Power Market Analysis for the Midwestern United States, 6th IAEE European Energy Conference on Modelling in Energy Economics and Policy (2004)
Lote, R.: Agent based modeling of electronical markets to analyze the sustainability of mutual cooperation. Master Theses, Paper 13, School of the University of Massachusetts. Industrial Enginering and operations research (2007)
Hayek, F.A.: Individualism and Economic Order. Routledge and Kegan Paul Ltd., London (1949)
Macal, C.M., North, M.J.: Tutorial on agent-based modeling and simulation part 2: how to model with agents. In: Proceedings of the Winter Simulation Conference, pp. 73–83 (2006)
Holland, J.H.: Adaptation in Natural and Artificial Systems. The University of Michigan, Boston (1975)
Kochugovindan, S., Vriend, N.J.: is the study of complex adaptive systems going to solve the mystery of adam smith’s ‘invisible hand’? Indep. Rev. 3(1), 53–66 (1998)
Burian, J.: Multiagentní model transakčních nákladu na finančních trzích. VŠE Praha (2010)
Tobin, J.: A proposal for international monetary reform. East. Econ. J. 4, 153–159 (1978)
Tobin, J.: The antiglobalisation movement has highjacked my name. Spiegel, Jubilee Research, Hamburg. Available from http://archive.is/CdcBN (2001)
Spahn, P.B.: International financial flows and transactions taxes: survey and options. In: Working Paper WP/95/60. International Monetary Fund, Frankfurt/Main (1995)
Wrobel, M.G.: Financial transaction taxes: the international experience and the lessons for Canada. In: Working paper BP-419E. Government of Canada Publications, Ottawa (1996)
Campbell, J.Y., froot, K.A.: International experiences with securities transaction taxes. In: NBER Working Paper No. W4587, pp. 277–308. University of Chicago Press, Chicago (1993)
Umlauf, S.: Transaction taxes and the behavior of the Swedish stock market. J. Financ. Econ. 33(2), 227 (1993)
Kovacheva, R.: The EU Expects 57 Billion Euros a Year from a New Financial Tax. EU inside. Available from http://www.euinside.eu/en/news/the-eu-expects-57-billion-euros-a-year-by-a-new-bank-tax (2011)
Wilson, H.: Financial transaction tax would raise & #x20AC;10bn. The Telegraph, London. Available from http://www.telegraph.co.uk/finance/newsbysector/banksandfinance/9087264/Financial-transaction-tax-would-raise-10bn.html (2012)
Dietlein, G.: National approaches towards a financial transaction tax and their compatibility with European law. EC Tax Rev. 21(4), 207–211 (2012)
Westerhoff, F.: A simple agent-based financial market model: direct interactions and com- parisons of trading profits. In: Working Paper No. 61. BERG Working Paper Series on Government and Growth. Bamberg University (2009)
Šperka, R., Spišák, M.: Transaction costs influence on the stability of financial market: agent-based simulation. J. Bus. Econ. Manage. (Taylor & Francis, London, United Kingdom) 14(Suppl. 1), S1–S12 (2013)
Wooldridge, M.: MultiAgent Systems: An Introduction, 2nd edn. Wiley, Chichester (2009)
Bellifemine, F., Caire, G., Trucco, T.: Jade Programmer’s Guide, Java Agent Development Framework. Available from http://jade.tilab.com/doc/programmersguide.pdf (2010)
Acknowledgments
This work was supported by grant of Silesian University no. SGS/6/2013 “Advanced Modeling and Simulation of Economic Systems”.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Šperka, R. (2016). Asset Management Strategies: Risk and Transaction Costs in Simulation. In: Tweedale, J., Neves-Silva, R., Jain, L., Phillips-Wren, G., Watada, J., Howlett, R. (eds) Intelligent Decision Technology Support in Practice. Smart Innovation, Systems and Technologies, vol 42. Springer, Cham. https://doi.org/10.1007/978-3-319-21209-8_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-21209-8_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-21208-1
Online ISBN: 978-3-319-21209-8
eBook Packages: EngineeringEngineering (R0)