Mean reversion in Asia-Pacific stock prices: New evidence from quantile unit root tests

PurposeThere are several studies that investigate evidence for mean reversion in stock prices. However, there is no consensus as to whether stock prices are mean reverting or random walk (unit root) processes. The goal of this paper is to re‐examine mean reversion in stock prices.Design/methodology/approachThe authors use five different panel unit root tests, namely the Im, Pesaran and Shin t‐bar test statistic, the Levin and Lin test, the Im, Lee, and Tieslau Lagrangian multiplier test statistic, the seemingly unrelated regression test, and the multivariate augmented Dickey Fuller test advocated by Taylor and Sarno.FindingsThe main finding is that there is no mean reversion of stock prices, consistent with the efficient market hypothesis.Research limitations/implicationsOne issue not considered by this study is the role of structural breaks. It may be the case that the efficient market hypothesis is contingent on structural breaks in stock prices. Future studies should model structural breaks.Practical implicationsThe findings have implications for econometric modelling, in particular forecasting.Originality/valueThis paper adds to the scarce literature on the mean reverting property of stock prices based on panel data; thus, it should be useful for researchers.

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Mean reversion versus random walk in G7 stock prices evidence from multiple trend break unit root tests

Journal of International Financial Markets Institutions and Money ◽

10.1016/j.intfin.2005.10.002 ◽

2007 ◽

Vol 17 (2) ◽

pp. 152-166 ◽

Cited By ~ 30

Author(s):

Paresh Kumar Narayan ◽

Russell Smyth

Keyword(s):

Random Walk ◽

Unit Root ◽

Stock Prices ◽

Mean Reversion ◽

Unit Root Tests

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An Extended Class of Unit Root Tests for Relative Stock Prices

SSRN Electronic Journal ◽

10.2139/ssrn.2534991 ◽

2014 ◽

Author(s):

Shlomo Zilca

Keyword(s):

Unit Root ◽

Stock Prices ◽

Unit Root Tests ◽

Extended Class

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UNIT ROOT TEST WITH HIGH-FREQUENCY DATA

Econometric Theory ◽

10.1017/s0266466621000098 ◽

2021 ◽

pp. 1-59

Author(s):

Sébastien Laurent ◽

Shuping Shi

Keyword(s):

Random Walk ◽

Unit Root ◽

High Frequency ◽

Asset Prices ◽

Composite Index ◽

Mean Reversion ◽

Unit Root Tests ◽

High Frequency Data ◽

Frequency Data ◽

Intraday Data

Deviations of asset prices from the random walk dynamic imply the predictability of asset returns and thus have important implications for portfolio construction and risk management. This paper proposes a real-time monitoring device for such deviations using intraday high-frequency data. The proposed procedures are based on unit root tests with in-fill asymptotics but extended to take the empirical features of high-frequency financial data (particularly jumps) into consideration. We derive the limiting distributions of the tests under both the null hypothesis of a random walk with jumps and the alternative of mean reversion/explosiveness with jumps. The limiting results show that ignoring the presence of jumps could potentially lead to severe size distortions of both the standard left-sided (against mean reversion) and right-sided (against explosiveness) unit root tests. The simulation results reveal satisfactory performance of the proposed tests even with data from a relatively short time span. As an illustration, we apply the procedure to the Nasdaq composite index at the 10-minute frequency over two periods: around the peak of the dot-com bubble and during the 2015–2106 stock market sell-off. We find strong evidence of explosiveness in asset prices in late 1999 and mean reversion in late 2015. We also show that accounting for jumps when testing the random walk hypothesis on intraday data is empirically relevant and that ignoring jumps can lead to different conclusions.

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