Abstract
We present a nonlinear structural stock market model which is a nonlinear deterministic process buffeted by dynamic noise. The market is composed of two typical trader types, the rational fundamentalists believing that the price of an asset is determined solely by its fundamental value and the boundedly rational noise traders governed by greed and fear. The interaction among heterogeneous investors determines the dynamics and the statistical properties of the system. We find the model is able to generate time series that exhibit dynamical and statistical properties closely resembling those of the S&P500 index, such as volatility clustering, fat tails (leptokurtosis), autocorrelation in square and absolute return, larger amplitude, crashes and bubbles. We also investigate the nonlinear dependence structure in our data. The results indicate that the GARCH-type model cannot completely account for all nonlinearity in our simulated market, which is thus consistent with the results from real markets. It seems that the nonlinear structural model is more powerful to give a satisfied explanation to market behavior than the traditional stochastic approach.
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References
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, 1235–1274 (1998)
Hommes, C.H., Manzan, S.: Comments on Testing for nonlinear structure and chaos in economic time series. Journal of Macroeconomic 28, 169–174 (2006)
Gaunersdorfer, A.: Endogenous fluctuations in a simple asset pricing model with heterogeneous agents. Journal of Economic Dynamics and Control 24, 799–831 (2000)
Malliaris, A.G., Stein, J.L.: Methodological issues in asset pricing: random walk or chaotic dynamics. Journal of Banking and Finance 23, 1605–1635 (1999)
Shiller, R.J.: The irrationality of markets. The Journal of Psychology and Financial Markets 3, 87–93 (2002)
Westerhoff, F.: Greed, fear and stock market dynamics. Physica A 343, 635–642 (2004)
Grassberger, P., Procaccia, I.: Characterization of strange attractors. Physical Review Letters 50, 346–349 (1983)
Brock, W.A., Dechert, W.D., Scheinkman, J.A., LeBaron, B.: A test for independence based on the correlation dimension. Econometric Reviews 15, 197–235 (1996)
Hsieh, D.A.: Chaos and nonlinear dynamics: application to financial markets. Journal of Finance 46, 1839–1877 (1991)
Kyrtsou, C., Terraza, M.: Stochastic chaos or ARCH effects in stock series? A comparative study. International Review of Financial Analysis 11, 407–431 (2002)
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© 2008 Springer-Verlag Berlin Heidelberg
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Li, H., Shang, W., Wang, S. (2008). Heterogeneity and Endogenous Nonlinearity in an Artificial Stock Model. In: Bubak, M., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds) Computational Science – ICCS 2008. ICCS 2008. Lecture Notes in Computer Science, vol 5102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69387-1_47
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DOI: https://doi.org/10.1007/978-3-540-69387-1_47
Publisher Name: Springer, Berlin, Heidelberg
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