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Bubbles, shocks and elementary technical trading strategies

  • Fry, John
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In this paper we provide a unifying framework for a set of seemingly disparate models for bubbles, shocks and elementary technical trading strategies in financial markets. Markets operate by balancing intrinsic levels of risk and return. This seemingly simple observation is commonly over-looked by academics and practitioners alike. Our model shares its origins in statistical physics with others. However, under our approach, changes in market regime can be explicitly shown to represent a phase transition from random to deterministic behaviour in prices. This structure leads to an improved physical and econometric model. We develop models for bubbles, shocks and elementary technical analysis strategies. We apply our model to real-estate bubbles and to the on-going Eurozone crisis. We close by comparing the results of our mathematical model with the results of qualitative analyses from the finance literature.

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File URL: http://mpra.ub.uni-muenchen.de/47052/1/MPRA_paper_47052.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 47052.

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Date of creation: 15 May 2013
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Handle: RePEc:pra:mprapa:47052
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  7. Zhou, Wei-Xing & Sornette, Didier, 2008. "Analysis of the real estate market in Las Vegas: Bubble, seasonal patterns, and prediction of the CSW indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(1), pages 243-260.
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  9. Fabrizio Lillo & Rosario N. Mantegna, 2001. "Power law relaxation in a complex system: Omori law after a financial market crash," Papers cond-mat/0111257, arXiv.org, revised Jun 2003.
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  11. Walid, Chkili & Chaker, Aloui & Masood, Omar & Fry, John, 2011. "Stock market volatility and exchange rates in emerging countries: A Markov-state switching approach," Emerging Markets Review, Elsevier, vol. 12(3), pages 272-292, September.
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  17. Lui, Yu-Hon & Mole, David, 1998. "The use of fundamental and technical analyses by foreign exchange dealers: Hong Kong evidence," Journal of International Money and Finance, Elsevier, vol. 17(3), pages 535-545, June.
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  19. Sornette, D & Helmstetter, A, 2003. "Endogenous versus exogenous shocks in systems with memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 318(3), pages 577-591.
  20. Jiang, Zhi-Qiang & Zhou, Wei-Xing & Sornette, Didier & Woodard, Ryan & Bastiaensen, Ken & Cauwels, Peter, 2010. "Bubble diagnosis and prediction of the 2005-2007 and 2008-2009 Chinese stock market bubbles," Journal of Economic Behavior & Organization, Elsevier, vol. 74(3), pages 149-162, June.
  21. George Chang & James Feigenbaum, 2006. "A Bayesian analysis of log-periodic precursors to financial crashes," Quantitative Finance, Taylor & Francis Journals, vol. 6(1), pages 15-36.
  22. Heping Pan & Didier Sornette & Kenneth Kortanek, 2006. "Intelligent finance—an emerging direction," Quantitative Finance, Taylor & Francis Journals, vol. 6(4), pages 273-277.
  23. Andrew Lo & Harry Mamaysky & Jiang Wang, 1999. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Computing in Economics and Finance 1999 402, Society for Computational Economics.
  24. De Paoli, Bianca & Zabczyk, Pawel, 2009. "Why do risk premia vary over time? A theoretical investigation under habit formation," Bank of England working papers 361, Bank of England.
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  26. Jeong-Ryeol Kurz-Kim, 2012. "Early warning indicator for financial crashes using the log periodic power law," Applied Economics Letters, Taylor & Francis Journals, vol. 19(15), pages 1465-1469, October.
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