Abstract
Understanding the mechanism of financial crises is an important issue, especially in a time of profound economic difficulty world-wide. To gain insights into how economic crises develop, we examine the exposure network associated with Fannie Mae/Freddie Mac, Lehman Brothers, and American International Group, and show that the losses associated with them can be modeled by an Omori-law-like distribution for earthquake aftershocks. Under certain conditions, Omori’s law leads to Pareto distribution. Positive Pareto incomes, together with Omori’s law, motivate us to examine whether distributions of negative incomes during crises may also be modeled by Pareto distributions. We find that during crises, negative incomes not only may indeed be modeled as Pareto-like distributions, but actually have heavier tails than those for positive incomes. As a result, entropy flow associated with losses or negative incomes provides an excellent technique for predicting economic downturns.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Aziz, J., Caramazza, F., Salgado, R.: Currency crises. In: Search of common elements. IMF Working Paper, vol. 67. International Monetary Fund, Washington, DC (2000)
BBC, Financial crises: Lessons from history (2007), http://news.bbc.co.uk/2/hi/business/6958091.stm
Jorge, A.C.-L., Chen, Z.H.: A theoretical model of financial crisis. Review of International Economics 10, 53 (2002)
Kindleberger, C.: Manias, panics, and crashes: A history of financial crises, 3rd edn. Wiley, New York (1996)
Ozkan-Gunay, E.N., Ozkan, M.: Prediction of bank failures in emerging financial markets: an ANN approach. The Journal of Risk Finance 8, 465 (2007)
Yeh, Y.H., Woidtke, T.: Commitment or entrenchment? Controlling shareholders and board composition. Journal of Banking & Finance 29, 1857 (2005)
Niemiraa, M.P., Saaty, T.L.: An Analytic Network Process model for financial-crisis forecasting. International Journal of Forecasting 20, 573 (2004)
Gao, J.B., Cao, Y.H., Tung, W.W., Hu, J.: Multiscale Analysis of Complex Time Series — Integration of Chaos and Random Fractal Theory, and Beyond, pp. 38–40. Wiley, Hoboken (2007)
Albert, R., Jeong, H., Barabasi, A.-L.: Error and attack tolerance of complex networks. Nature 406, 378–482 (2000)
Utsu, T., Ogata, Y., Matsu’ura, R.S.: The centenary of the Omori formula for a decay law of aftershock activity. J. Phys. Earth 43, 1–33 (1995)
Lillo, F., Mantegna, R.N.: Power-law relaxation in a complex system: Omori law after a financial market crash. Phys. Rev. E 68, 016119 (2003)
Weber, P., Wang, F., Vodenska-Chitkushev, I., Havlin, S., Stanley, H.E.: Relation between volatility correlations in financial markets and Omori processes occurring on all scales. Phys. Rev. E 76, 016109 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Gao, J., Hu, J. (2013). Financial Crisis, Omori’s Law, and Negative Entropy Flow. In: Greenberg, A.M., Kennedy, W.G., Bos, N.D. (eds) Social Computing, Behavioral-Cultural Modeling and Prediction. SBP 2013. Lecture Notes in Computer Science, vol 7812. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37210-0_49
Download citation
DOI: https://doi.org/10.1007/978-3-642-37210-0_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37209-4
Online ISBN: 978-3-642-37210-0
eBook Packages: Computer ScienceComputer Science (R0)