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Gain–loss asymmetry for emerging stock markets

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  • Karpio, Krzysztof
  • Załuska–Kotur, Magdalena A.
  • Orłowski, Arkadiusz

Abstract

Stock indexes for some European emerging markets are analyzed using an investment-horizon approach. Austrian ATX index and Dow Jones have been studied and compared with several emerging European markets. The optimal investment horizons are plotted as a function of an absolute return value. Gain–loss asymmetry, originally found for American DJIA index, is observed for all analyzed data. It is shown, that this asymmetry has different character for emerging and for established markets. For established markets, gain curve lies typically above loss curve, whereas in the case of emerging markets the situation is just the opposite. We propose a measure quantifying the gain–loss asymmetry that clearly exhibits a difference between emerging and established markets.

Suggested Citation

  • Karpio, Krzysztof & Załuska–Kotur, Magdalena A. & Orłowski, Arkadiusz, 2007. "Gain–loss asymmetry for emerging stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(2), pages 599-604.
    • Handle: RePEc:eee:phsmap:v:375:y:2007:i:2:p:599-604
    DOI: 10.1016/j.physa.2006.10.003
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    References listed on IDEAS

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    1. Johnson, Neil F. & Jefferies, Paul & Hui, Pak Ming, 2003. "Financial Market Complexity," OUP Catalogue, Oxford University Press, number 9780198526650, Decembrie.
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    Cited by:

    1. Zou, Yongjie & Li, Honggang, 2014. "Time spans between price maxima and price minima in stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 303-309.
    2. Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2008. "Multifractality in stock indexes: Fact or Fiction?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(14), pages 3605-3614.
    3. C. M. Rodr'iguez-Mart'inez & H. F. Coronel-Brizio & A. R. Hern'andez-Montoya, 2019. "A multi-scale symmetry analysis of uninterrupted trends returns of daily financial indices," Papers 1908.11204, arXiv.org.
    4. Ren, Fei & Guo, Liang & Zhou, Wei-Xing, 2009. "Statistical properties of volatility return intervals of Chinese stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(6), pages 881-890.
    5. Restocchi, Valerio & McGroarty, Frank & Gerding, Enrico, 2019. "The stylized facts of prediction markets: Analysis of price changes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 159-170.
    6. Niu, Hongli & Wang, Weiqing & Zhang, Junhuan, 2019. "Recurrence duration statistics and time-dependent intrinsic correlation analysis of trading volumes: A study of Chinese stock indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 838-854.
    7. Niu, Hongli & Wang, Jun, 2017. "Return volatility duration analysis of NYMEX energy futures and spot," Energy, Elsevier, vol. 140(P1), pages 837-849.
    8. Andrea Giuseppe Di Iura & Giulia Terenzi, 2021. "A Bayesian analysis of gain-loss asymmetry," Papers 2104.06044, arXiv.org.

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