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Asymmetric Stationarity in National Stock Market Indices: An MTAR Analysis

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  • James K. Self

    (Indiana University–Bloomington)

Abstract

A procedure is developed using a momentum threshold autoregressive model and asymmetric stationarity tests designed to identify periods of asymmetric stationary divergences from nonstationary paths in time series and is applied to major national stock indices. The results reveal the existence of asymmetric stationary periods in each of these indices. These results suggest an explanation for the counterintuitive positive forecasting results of technical traders for various time periods. We explore this possibility further by using a representative moving average technical trading strategy and find significantly different results (higher returns) when information from the procedure is incorporated into a trading rule.

Suggested Citation

  • James K. Self, 2006. "Asymmetric Stationarity in National Stock Market Indices: An MTAR Analysis," The Journal of Business, University of Chicago Press, vol. 79(6), pages 3153-3174, November.
  • Handle: RePEc:ucp:jnlbus:v:79:y:2006:i:6:p:3153-3174
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    References listed on IDEAS

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    1. repec:rmk:rmkjrc:v:4:y:2017:i:1:p:51-69 is not listed on IDEAS
    2. Kwang-il Choe & Joshua Krausz & Kiseok Nam, 2011. "Technical trading rules for nonlinear dynamics of stock returns: evidence from the G-7 stock markets," Review of Quantitative Finance and Accounting, Springer, vol. 36(3), pages 323-353, April.
    3. Joshua Krausz & Sa-Young Lee & Kiseok Nam, 2009. "Profitability of Nonlinear Dynamics Under Technical Trading Rules: Evidence from Pacific Basin Stock Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 45(4), pages 13-35, July.
    4. Adämmer, Philipp & Bohl, Martin T., 2015. "Speculative bubbles in agricultural prices," The Quarterly Review of Economics and Finance, Elsevier, vol. 55(C), pages 67-76.
    5. Hui, Eddie Chi-Man & Wang, Ziyou, 2015. "Can we predict the property cycle? A study of securitized property market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 426(C), pages 72-87.
    6. Joshua Krausz & Sa-Young Lee & Kiseok Nam, 2009. "Profitability of Nonlinear Dynamics Under Technical Trading Rules: Evidence from Pacific Basin Stock Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 45(4), pages 13-35, July.

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