Characterization of large price variations in financial markets
Statistics of drawdowns (loss from the last local maximum to the next local minimum) plays an important role in risk assessment of investment strategies. As they incorporate higher (> two) order correlations, they offer a better measure of real market risks than the variance or other cumulants of daily (or some other fixed time scale) of returns. Previous results have shown that the vast majority of drawdowns occurring on the major financial markets have a distribution which is well represented by a stretched exponential, while the largest drawdowns are occurring with a significantly larger rate than predicted by the bulk of the distribution and should thus be characterized as outliers (Eur. Phys. J. B 1 (1998) 141; J. Risk 2001). In the present analysis, the definition of drawdowns is generalized to coarse-grained drawdowns or so-called ε-drawdowns and a link between such ε-outliers and preceding log-periodic power law bubbles previously identified (Quantitative Finance 1 (2001) 452) is established.
Volume (Year): 324 (2003)
Issue (Month): 1 ()
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- D. Sornette & A. Johansen, 2001. "Significance of log-periodic precursors to financial crashes," Papers cond-mat/0106520, arXiv.org.
- Fabrizio Lillo & Rosario N. Mantegna, 2000. "Symmetry alteration of ensemble return distribution in crash and rally days of financial markets," Papers cond-mat/0002438, arXiv.org.
- D. Sornette & A. Johansen, 2001. "Significance of log-periodic precursors to financial crashes," Quantitative Finance, Taylor & Francis Journals, vol. 1(4), pages 452-471.
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- Anders Johansen & Didier Sornette, 1999. "Critical Crashes," Papers cond-mat/9901035, arXiv.org.
- Anders Johansen & Didier Sornette, 2000. "The Nasdaq crash of April 2000: Yet another example of log-periodicity in a speculative bubble ending in a crash," Papers cond-mat/0004263, arXiv.org, revised May 2000.
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