Skip to main content
SpringerLink
Log in

An Asynchronous Double Auction Market to Study the Formation of Financial Bubbles and Crashes

  • Research Paper
  • Published:
New Generation Computing Aims and scope Submit manuscript

Abstract

Stock market is a complex system composed from heterogeneous traders with highly non-linear interactions from which emerge a phenomenon of speculative bubble. To understand the role of heterogeneous behaviors of traders and interactions between them in the emergence of bubbles, we propose an agent-based model of double auction market, with asynchronous time management, where traders act asynchronously and take different times to make decisions. The market is populated by heterogeneous traders. In addition to fundamentalist, noise, and technical (chartist) traders, we propose a hybrid trader, which can switch between technical (chartist) and fundamentalist strategies integrating panicking behavior. We find that when market is populated by a majority of hybrid traders, we observe quite realistic bubble formation characterized by a boom phase when hybrid traders switch to technical behavior, followed by a relatively shorter burst phase when hybrid traders return to fundamentalist strategy and change to panicked state. The aim is to design agents which act asynchronously, with simple behaviors, but complex enough to produce realistic price dynamics, which provide a basis for developing agents with sophisticated decision-making processes.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Notes

  1. The notation \(a\sim \mathcal {U} (x,y)\) expresses that a is a uniformly selected in [x, y].

  2. Exp.2 and Exp.3 are the particular experiments performed to analyze the liquidity, while the rest of experiments aims at comparing price dynamics with fundamental value.

  3. In experimental economics, time is divided into periods; in each period, the fundamental value has a fixed value. In our model, time is not divided into periods, therefore, to calculate Boom and Burst durations, we divide the time of each experiment to 150 periods, and we use the median of fundamental values in each period.

References

  1. Amblard, F., Phan, D.: Modélisation et simulation multi-agents. Hermes Lavoisier, Paris (2006)

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

  3. Barlevy, G.: Economic theory and asset bubbles. Econ. Perspect. 31(3) (2007)

  4. Bernanke, B.S.: The Federal Reserve and the financial crisis. Princeton University Press (2013)

  5. Bessembinder, H., Venkataraman, K.: Bid-ask spreads: measuring trade execution costs in financial markets. Encycl. Quant. Finance (2009)

  6. Blanchard, O.J., Watson, M.W.: Bubbles, rational expectations and financial markets (1982)

  7. Boer, K., Kaymak, U., Spiering, J.: From discrete-time models to continuous-time, asynchronous modeling of financial markets. Comput. Intell. 23(2), 142–161 (2007)

    Article  MathSciNet  Google Scholar 

  8. Boer-Sorban, K.: Agent-based simulation of financial markets: a modular, continuous-time approach. Number EPS-2008-119-LIS. Erasmus Research Institute of Management (ERIM) (2008)

  9. Chacko, G., Jurek, J.W., Stafford, E.: Pricing liquidity: the quantity structure of immediacy prices. Division of Research, Harvard Business School (2006)

  10. Chen, S.-H., Chang, C.-L., Du, Y.-R.: Agent-based economic models and econometrics. Knowl. Eng. Rev. 27(02), 187–219 (2012)

    Article  Google Scholar 

  11. Cui, B., Wang, H., Ye, K., Yan, J.: Intelligent agent-assisted adaptive order simulation system in the artificial stock market. Expert Syst. Appl. 39(10), 8890–8898 (2012)

    Article  Google Scholar 

  12. Deck, C., Porter, D., Smith, V.: Double bubbles in assets markets with multiple generations. J. Behav. Finance 15(2), 79–88 (2014)

    Article  Google Scholar 

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

  14. Derveeuw, J., Beaufils, B., Mathieu, P., and Brandouy, O.: Testing double auction as a component within a generic market model architecture. In: Artificial Markets Modeling, pp. 47–61. Springer (2007)

  15. Diba, B.T., Grossman, H.I.: Rational inflationary bubbles. J. Monet. Econ. 21(1), 35–46 (1988)

    Article  Google Scholar 

  16. Fama, E.F.: Efficient capital markets: a review of theory and empirical work. J Finance 25(2), 383–417 (1970)

    Article  Google Scholar 

  17. Frankel, J.A., Froot, K.: Chartists, fundamentalists and the demand for dollars. NBER Working Paper, (R1655) (1991)

  18. Füllbrunn, S., Neugebauer, T.: Margin trading bans in experimental asset markets. Technical report, Jena Economic Research Papers (2012)

  19. Giardina, I., Bouchaud, J.-P.: Bubbles, crashes and intermittency in agent based market models. Eur. Phys. J. B Condens. Matter Complex Syst. 31(3), 421–437 (2003)

    Article  MathSciNet  Google Scholar 

  20. Gravereau, J., Trauman, J.: Crises financières. Economica (2001)

  21. Haruvy, E., Noussair, C.N.: The effect of short selling on bubbles and crashes in experimental spot asset markets. J. Finance 61(3), 1119–1157 (2006)

    Article  Google Scholar 

  22. Izumi, K., Okatsu, T.: An artificial market analysis of exchange rate dynamics. In: Evolutionary Programming, pp. 27–36. Citeseer (1996)

  23. Kaldor, N.: Speculation and economic stability. Rev. Econ. Stud. 7(1), 1–27 (1939)

    Article  Google Scholar 

  24. Karino, Y., Kawagoe, T.: Bubble and crash in the artificial financial market. In: Artificial Economics, pp. 159–170. Springer (2009)

  25. Kindleberger, C.P., Aliber, R.Z.: Manias, panics and crashes: a history of financial crises. Palgrave Macmillan (2011)

  26. Kobayashi, S., Hashimoto, T.: Analysis of random agents for improving market liquidity using ar-tificial stock market. In: Proceedings of The Fourth Conference of The European Social Simulation Association (ESSA 4th07), pp. 315–317 (2007)

  27. Kumar, P., Amritha, T., Gowtham Ram, S., Hari Krishna, S., Karthika, M., Mohandas, V.: A survey of agent based artificial stock markets (continuous session models). Int. Res. J. Finance Econ. 64, 126–139 (2011)

    Google Scholar 

  28. Kumar, P., Jha, A., Gautham, T., Mohan, J., Rama Subramanian, A., Mohandas, V.: A survey of call market (discrete) agent based artificial stock markets. Int. J. Comput. Sci. Eng. 2(09), 3025–3032 (2010)

    Google Scholar 

  29. Lugovskyy, V., Puzzello, D., Tucker, S., Williams, A.: Asset-holdings caps and bubbles in experimental asset markets. J. Econ. Behav. Organ. 107, 781–797 (2014)

    Article  Google Scholar 

  30. Lux, T., Marchesi, M.: Scaling and criticality in a stochastic multi-agent model of a financial market. Nature 397(6719), 498–500 (1999)

    Article  Google Scholar 

  31. Martinez, S., Tsang, E.P.: An heterogeneous, endogenous and coevolutionary gp-based financial market. Evol. Comput. IEEE Trans. 13(1), 33–55 (2009)

    Article  Google Scholar 

  32. Mizuta, T., Izumi, K., Yoshimura, S.: Price variation limits and financial market bubbles: artificial market simulations with agents’ learning process. In: Computational Intelligence for Financial Engineering & Economics (CIFEr), 2013 IEEE Conference, pp. 1–7. IEEE (2013)

  33. Mizuta, T., Kosugi, S., Kusumoto, T., Matsumoto, W., Izumi, K., Yagi, I., Yoshimura, S.: Effects of price regulations and dark pools on financial market stability: an investigation by multiagent simulations. Intell. Syst. Account. Finance Manag. (2015)

  34. Muchnik, L., Solomon, S.: Markov nets and the netlab platform: application to continuous double auction. In: Complexity hints for economic policy, pp. 157–180. Springer (2007)

  35. Orléan, A.: L’auto-référence dans la théorie keynésienne de la spéculation. Cahiers d’économie politique/Papers in Political Economy, pp. 229–242 (1988)

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

    Article  MATH  Google Scholar 

  37. Sewell, M.: Characterization of financial time series. Research Note. University College London (2011)

  38. Smith, V.L., Suchanek, G.L., Williams, A.W.: Bubbles, crashes, and endogenous expectations in experimental spot asset markets. Econometrica, pp. 1119–1151 (1988)

  39. Stöckl, T., Huber, J., Kirchler, M.: Bubble measures in experimental asset markets. Exp. Econ. 13(3), 284–298 (2010)

    Article  MATH  Google Scholar 

  40. Tan, J.P., David, M.: Study of property market in johor: an investigation of property bubble phenomenon (2012)

  41. Thurner, S., Farmer, J.D., Geanakoplos, J.: Leverage causes fat tails and clustered volatility. Quant. Finance 12(5), 695–707 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  42. Vigfusson, R.: Switching between chartists and fundamentalists: a markov regime-switching approach (1996)

  43. Wang, P., Wen, Y.: Speculative bubbles and financial crises. Am. Econ. J. Macroecon. 4(3), 184–221 (2012)

    Article  Google Scholar 

  44. Westerhoff, F.H.: The use of agent-based financial market models to test the effectiveness of regulatory policies. Jahrbücher für Nationalökonomie und Statistik, pp. 195–227 (2008)

  45. Zovko, I.I.: Topics in market microstructure. Amsterdam University Press (2008)

Download references

Author information

Authors and Affiliations

  1. MISC Laboratory, Computer Science Department, University of Constantine 2, Constantine, Algeria

    Sadek Benhammada & Salim Chikhi

  2. UMR 5505 CNRS-IRIT, Universit Toulouse 1 Capitole, Toulouse, France

    Frédéric Amblard

Authors
  1. Sadek Benhammada
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Frédéric Amblard
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Salim Chikhi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sadek Benhammada.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Benhammada, S., Amblard, F. & Chikhi, S. An Asynchronous Double Auction Market to Study the Formation of Financial Bubbles and Crashes. New Gener. Comput. 35, 129–156 (2017). https://doi.org/10.1007/s00354-017-0010-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00354-017-0010-6

Keywords

Search

Navigation