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London Calling: Nonlinear Mean Reversion across National Stock Markets

Hyeongwoo Kim () and Jintae Kim

No auwp2014-13, Auburn Economics Working Paper Series from Department of Economics, Auburn University

Abstract: This paper revisits empirical evidence of mean reversion of relative stock prices in international stock markets. We implement a strand of univariate and panel unit root tests for linear and nonlinear models of 18 national stock indices during the period 1969 to 2012. Our major findings are as follows. First, we find little evidence of linear mean reversion irrespective of the choice of a reference country. Employing panel tests yields the same conclusion once the cross-section dependence is controlled. Second, we find strong evidence of nonlinear mean reversion when the UK serves as a reference country, calling attention to the stock index in the UK. Choosing the US as a reference yields very weak evidence of nonlinear stationarity. Third, via extensive Monte Carlo simulations, we demonstrate a potential pitfall in using panel unit root tests with cross-section dependence when a stationary common factor dominates nonstationary idiosyncratic components in small samples.

Keywords: Unit Root Test; Exponential Smooth Transition Autoregressive (ESTAR) Unit Root Test; Nonlinear Panel unit root test; Panel Analysis of Nonstationarity in Idiosyncratic and Common Components (PANIC) (search for similar items in EconPapers)
JEL-codes: C22 G10 G15 (search for similar items in EconPapers)
Date: 2014-11
New Economics Papers: this item is included in nep-ecm and nep-fmk
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Related works:
Journal Article: London calling: Nonlinear mean reversion across national stock markets (2018) Downloads
Working Paper: London Calling: Nonlinear Mean Reversion across National Stock Markets (2018) Downloads
Working Paper: London Calling: Nonlinear Mean Reversion across National Stock Markets (2017) Downloads
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