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The momentum effect on Chinese real estate stocks: Evidence from firm performance levels

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  • Lee, Jen-Sin
  • Huang, Gow-Liang
  • Kuo, Chin-Tai
  • Lee, Liang-Chien

Abstract

This paper investigates the momentum effects under different firm performance levels for Chinese real estate stocks using quantile regression with a dummy variable estimator. This paper finds that regardless of the momentum horizon, the momentum effects are positive under high-performing individual stocks, but they are negative under low-performing individual stocks. While prior literature only finds that this asymmetric phenomenon appears under different market states, and the findings on different horizons are inconsistent. Furthermore, this paper finds that the positive (negative) momentum effect under high (low) firm performance levels is stronger than that under bullish (bearish) markets. This implies that superior (inferior) fundamental business performance and bullish (bearish) markets can cause the stock prices to go up (down); however, the effect of the former is stronger than that of the latter. Moreover, this paper finds that the relation between future returns and past turnover ratios is positively correlated under high-performing stocks, but negatively correlated under low-performing stocks. Based on the above findings, this paper regards past turnover ratios as a leading indicator of stock returns and suggests two profitable investment portfolios which are superior to the average returns of real estate stocks.

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  • Lee, Jen-Sin & Huang, Gow-Liang & Kuo, Chin-Tai & Lee, Liang-Chien, 2012. "The momentum effect on Chinese real estate stocks: Evidence from firm performance levels," Economic Modelling, Elsevier, vol. 29(6), pages 2392-2406.
  • Handle: RePEc:eee:ecmode:v:29:y:2012:i:6:p:2392-2406
    DOI: 10.1016/j.econmod.2012.06.023
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    3. Zhang, Wei & Wang, Guanying & Wang, Xingchun & Xiong, Xiong & Lei, Xuan, 2018. "Profitability of reversal strategies: A modified version of the Carhart model in China," Economic Modelling, Elsevier, vol. 69(C), pages 26-37.
    4. Mo, Guoli & Tan, Chunzhi & Zhang, Weiguo & Liu, Fang, 2019. "International portfolio of stock indices with spatiotemporal correlations: Can investors still benefit from portfolio, when and where?," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 168-183.
    5. Sekrafi Habib & Snoussi Abdelmonen & Mili Khaled, 2020. "The Effect of Corruption on the Environmental Quality in African Countries: a Panel Quantile Regression Analysis," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 11(2), pages 788-804, June.
    6. Zhang, Yue-Jun & Jin, Yan-Lin & Chevallier, Julien & Shen, Bo, 2016. "The effect of corruption on carbon dioxide emissions in APEC countries: A panel quantile regression analysis," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 220-227.
    7. Gong, Pu & Weng, Yingliang, 2016. "Value-at-Risk forecasts by a spatiotemporal model in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 441(C), pages 173-191.
    8. You, Wan-Hai & Zhu, Hui-Ming & Yu, Keming & Peng, Cheng, 2015. "Democracy, Financial Openness, and Global Carbon Dioxide Emissions: Heterogeneity Across Existing Emission Levels," World Development, Elsevier, vol. 66(C), pages 189-207.

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    More about this item

    Keywords

    Real estate stocks; Momentum effects; Firm performance levels; Turnover ratios; Quantile regression;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance

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