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Detecting log-periodicity in a regime-switching model of stock returns

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Author Info
George Chang
James Feigenbaum

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Abstract

Log-periodic precursors have been identified before most and perhaps all financial crashes of the Twentieth Century, but efforts to statistically validate the leading model of log-periodicity, the Johansen-Ledoit-Sornette (JLS) model, have generally failed. The main feature of this model is that log-harmonic fluctuations in financial prices are driven by similar fluctuations in expected daily returns. Here we search more broadly for evidence of any log-periodic variation in expected daily returns by estimating a regime-switching model of stock returns in which the mean return fluctuates between a high and a low value. We find such evidence prior to the two largest drawdowns in the S&P 500 since 1950. However, if we estimate a log-harmonic specification for the stock index for the same time periods, fixing the frequency and critical time according to the results of the regime-switching model, the parameters do not satisfy restrictions imposed by the JLS model.

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File URL: http://www.informaworld.com/openurl?genre=article&doi=10.1080/14697680701689620&magic=repec&7C&7C8674ECAB8BB840C6AD35DC6213A474B5
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Publisher Info
Article provided by Taylor and Francis Journals in its journal Quantitative Finance.

Volume (Year): 8 (2008)
Issue (Month): 7 ()
Pages: 723-738
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Handle: RePEc:taf:quantf:v:8:y:2008:i:7:p:723-738

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Related research
Keywords: Asset pricing; Bayesian analysis; Log-periodicity; Econophysics; Regime-switching;

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