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

George Chang and James Feigenbaum ()

Quantitative Finance, 2008, vol. 8, issue 7, 723-738

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.

Keywords: Asset pricing; Bayesian analysis; Log-periodicity; Econophysics; Regime-switching (search for similar items in EconPapers)
Date: 2008
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DOI: 10.1080/14697680701689620

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