A Statistical Analysis of Log-Periodic Precursors to Financial Crashes

James Feigenbaum

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A Statistical Analysis of Log-Periodic Precursors to Financial Crashes

James Feigenbaum

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Abstract

Motivated by the hypothesis that financial crashes are macroscopic examples of critical phenomena associated with a discrete scaling symmetry, we reconsider the evidence of log-periodic precursors to financial crashes and test the prediction that log-periodic oscillations in a financial index are embedded in the mean function of this index. In particular, we examine the first differences of the logarithm of the S&P 500 prior to the October 87 crash and find the log-periodic component of this time series is not statistically significant if we exclude the last year of data before the crash. We also examine the claim that two separate mechanisms are responsible for draw downs in the S&P 500 and find the evidence supporting this claim to be unconvincing.

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James Feigenbaum. 2001-02-28. A Statistical Analysis of Log-Periodic Precursors to Financial Crashes. https://arxiv.org/abs/cond-mat/0101031

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