Replicating financial market dynamics with a simple self-organized critical lattice model
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- Bak, P. & Paczuski, M. & Shubik, M., 1997.
"Price variations in a stock market with many agents,"
Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 246(3), pages 430-453.
- P. Bak & M. Paczuski & Martin Shubik, 1996. "Price Variations in a Stock Market with Many Agents," Cowles Foundation Discussion Papers 1132, Cowles Foundation for Research in Economics, Yale University.
- P. Bak & M. Paczuski & M. Shubik, 1996. "Price Variations in a Stock Market with Many Agents," Working Papers 96-09-075, Santa Fe Institute.
- Ausloos, Marcel & Clippe, Paulette & Pȩkalski, Andrzej, 2004. "Evolution of economic entities under heterogeneous political/environmental conditions within a Bak–Sneppen-like dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 332(C), pages 394-402.
- Tobias Rydén & Timo Teräsvirta & Stefan Åsbrink, 1998.
"Stylized facts of daily return series and the hidden Markov model,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(3), pages 217-244.
- Rydén, Tobias & Teräsvirta, Timo & Åsbrink, Stefan, 1996. "Stylized Facts of Daily Return Series and the Hidden Markov Model," SSE/EFI Working Paper Series in Economics and Finance 117, Stockholm School of Economics.
- Asger Lunde & Peter R. Hansen, 2005.
"A forecast comparison of volatility models: does anything beat a GARCH(1,1)?,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 873-889.
- Asger Lunde & Peter Reinhard Hansen, 2001. "A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?," Working Papers 2001-04, Brown University, Department of Economics.
- Bollerslev, Tim, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
- Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- Stauffer, Dietrich & Sornette, Didier, 1999. "Self-organized percolation model for stock market fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 271(3), pages 496-506.
- repec:adr:anecst:y:1995:i:40:p:04 is not listed on IDEAS
- Rama CONT & Jean-Philippe BOUCHAUD, 1997. "Herd behavior and aggregate fluctuations in financial markets," Finance 9712008, University Library of Munich, Germany, revised 06 Jan 1998.
- Rama Cont & Jean-Philippe Bouchaud, 1997. "Herd behavior and aggregate fluctuations in financial markets," Science & Finance (CFM) working paper archive 500028, Science & Finance, Capital Fund Management.
- Dupoyet, B. & Fiebig, H.R. & Musgrove, D.P., 2010. "Gauge invariant lattice quantum field theory: Implications for statistical properties of high frequency financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(1), pages 107-116.
- C. W. J. Granger & Zhuanxin Ding, 1995. "Some Properties of Absolute Return: An Alternative Measure of Risk," Annals of Economics and Statistics, GENES, issue 40, pages 67-91.
- Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
- Bartolozzi, M. & Leinweber, D.B. & Thomas, A.W., 2006. "Symbiosis in the Bak–Sneppen model for biological evolution with economic applications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 365(2), pages 499-508.
- Levy, Haim & Levy, Moshe & Solomon, Sorin, 2000. "Microscopic Simulation of Financial Markets," Elsevier Monographs, Elsevier, edition 1, number 9780124458901.
- Kirill Ilinski, 1997. "Physics of Finance," Papers hep-th/9710148, arXiv.org.
- Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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NEP fields
This paper has been announced in the following NEP Reports:- NEP-CBA-2010-11-06 (Central Banking)
- NEP-FMK-2010-11-06 (Financial Markets)
- NEP-MST-2010-11-06 (Market Microstructure)
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