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Analysis of the efficiency of Hong Kong REITs market based on Hurst exponent

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  • Liu, Jian
  • Cheng, Cheng
  • Yang, Xianglin
  • Yan, Lizhao
  • Lai, Yongzeng

Abstract

At present, as China promotes the virtuous circle of housing leasing market, Real Estate Investment Trusts (REITs) has become an important investment and financing tool. In this paper, Hurst exponent is used to examine the efficiency of Hong Kong REITs market in China, and time-varying Hurst exponent is used to explore the dynamic changes of its efficiency. The empirical results of the Hong Kong REITs market show that the Hong Kong REITs market has not yet reached weak efficiency, and it is basically in a state of inefficiency from November 25 2005 to October 10, 2018, with only three times approximate to weak-form efficiency, but the duration is very short. Furthermore, compared with the Hong Kong stock market and the real estate market, the degree of efficiency of the Hong Kong REITs market is the lowest. Finally, on this basis, some countermeasures and suggestions for the development of China’s REITs market are put forward. This paper not only enriches the study of REITs market, but also provides the relevant basis for investors to make investment decisions.

Suggested Citation

  • Liu, Jian & Cheng, Cheng & Yang, Xianglin & Yan, Lizhao & Lai, Yongzeng, 2019. "Analysis of the efficiency of Hong Kong REITs market based on Hurst exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    • Handle: RePEc:eee:phsmap:v:534:y:2019:i:c:s0378437119311720
    DOI: 10.1016/j.physa.2019.122035
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    as
    1. John Cotter & Simon Stevenson, 2008. "Modeling Long Memory in REITs," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 36(3), pages 533-554, September.
    2. Hassler, Uwe & Wolters, Jurgen, 1995. "Long Memory in Inflation Rates: International Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 37-45, January.
    3. Fenghua Wen & Xin Yang & Wei‐Xing Zhou, 2019. "Tail dependence networks of global stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(1), pages 558-567, January.
    4. Sukpitak, Jessada & Hengpunya, Varagorn, 2016. "The influence of trading volume on market efficiency: The DCCA approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 259-265.
    5. Schindler, Felix & Rottke, Nico & Füss, Roland, 2009. "Testing the predictability and efficiency of securitized real estate markets," ZEW Discussion Papers 09-054, ZEW - Leibniz Centre for European Economic Research.
    6. Robert T. Kleiman & James E. Payne & Anandi P. Sahu, 2002. "Random Walks and Market Efficiency: Evidence from International Real Estate Markets," Journal of Real Estate Research, American Real Estate Society, vol. 24(3), pages 279-298.
    7. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    8. Kim Hin David Ho & Shea Jean Tay, 2016. "REIT market efficiency through a binomial option pricing tree approach," Journal of Property Investment & Finance, Emerald Group Publishing Limited, vol. 34(5), pages 496-520, August.
    9. Greene, Myron T. & Fielitz, Bruce D., 1977. "Long-term dependence in common stock returns," Journal of Financial Economics, Elsevier, vol. 4(3), pages 339-349, May.
    10. Jensen, Michael C., 1978. "Some anomalous evidence regarding market efficiency," Journal of Financial Economics, Elsevier, vol. 6(2-3), pages 95-101.
    11. Couillard, Michel & Davison, Matt, 2005. "A comment on measuring the Hurst exponent of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 348(C), pages 404-418.
    12. Sensoy, A., 2013. "Generalized Hurst exponent approach to efficiency in MENA markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 5019-5026.
    13. Serletis, Apostolos & Rosenberg, Aryeh Adam, 2007. "The Hurst exponent in energy futures prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 325-332.
    14. Schindler, Felix, 2010. "Market efficiency in the emerging securitized real estate markets," ZEW Discussion Papers 10-033, ZEW - Leibniz Centre for European Economic Research.
    15. Jin, Xiaoye, 2016. "The impact of 2008 financial crisis on the efficiency and contagion of Asian stock markets: A Hurst exponent approach," Finance Research Letters, Elsevier, vol. 17(C), pages 167-175.
    16. Sánchez Granero, M.A. & Trinidad Segovia, J.E. & García Pérez, J., 2008. "Some comments on Hurst exponent and the long memory processes on capital markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(22), pages 5543-5551.
    17. repec:arz:wpaper:eres2010-138 is not listed on IDEAS
    18. Jorge Belaire-Franch & Stanley McGreal & Kwaku K. Opong & James R. Webb, 2007. "A Nonparametric Variance-Ratio Test of the Behavior of U.K. Real Estate and Construction Indices," International Real Estate Review, Global Social Science Institute, vol. 10(2), pages 94-112.
    19. repec:clg:wpaper:2007-02 is not listed on IDEAS
    20. Liu, Hong & Wang, Chang & Tian, Meiyu & Wen, Fenghua, 2019. "Analysis of regional difference decomposition of changes in energy consumption in China during 1995–2015," Energy, Elsevier, vol. 171(C), pages 1139-1149.
    21. Kian‐Ping Lim & Robert Brooks, 2011. "The Evolution Of Stock Market Efficiency Over Time: A Survey Of The Empirical Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 69-108, February.
    22. Assaf, Ata, 2015. "Long memory and level shifts in REITs returns and volatility," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 172-182.
    23. Jian Zhou & Jin Man Lee, 2013. "Adaptive market hypothesis: evidence from the REIT market," Applied Financial Economics, Taylor & Francis Journals, vol. 23(21), pages 1649-1662, November.
    24. Hiremath, Gourishankar S. & Narayan, Seema, 2016. "Testing the adaptive market hypothesis and its determinants for the Indian stock markets," Finance Research Letters, Elsevier, vol. 19(C), pages 173-180.
    25. Edward Nelling & Joseph Gyourko, 1998. "The Predictability of Equity REIT Returns," Journal of Real Estate Research, American Real Estate Society, vol. 16(3), pages 251-268.
    26. Shea, Gary S, 1991. "Uncertainty and Implied Variance Bounds in Long-Memory Models of the Interest Rate Term Structure," Empirical Economics, Springer, vol. 16(3), pages 287-312.
    27. Xiao, Jihong & Hu, Chunyan & Ouyang, Guangda & Wen, Fenghua, 2019. "Impacts of oil implied volatility shocks on stock implied volatility in China: Empirical evidence from a quantile regression approach," Energy Economics, Elsevier, vol. 80(C), pages 297-309.
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