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Financial stress and returns predictability: Fresh evidence from China

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  • Xu, Yongan
  • Liang, Chao
  • Wang, Jianqiong

Abstract

Our paper examines the implication of the China financial stress index (CNFSI) constructed by Park and Mercado (2014) on asset pricing. First, the CNFSI has a significant negative relationship with subsequent stock market returns, the statistics of in-sample R2 and out-of-sample ROS2 estimated by the predictive regression model are 5.078% and 5.881%, respectively. Second, from the statistical evidence, the predictive effect of the CNFSI is significantly better than that of popular macroeconomic variables and other existing financial stress indices for both in- and out-of-sample periods. Third, according to the results of a long-horizon analysis, the CNFSI has better predictive power for returns during bull markets than during bear markets. Finally, these interesting results are verified by a set of robustness tests.

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  • Xu, Yongan & Liang, Chao & Wang, Jianqiong, 2023. "Financial stress and returns predictability: Fresh evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 78(C).
    • Handle: RePEc:eee:pacfin:v:78:y:2023:i:c:s0927538x2300046x
    DOI: 10.1016/j.pacfin.2023.101980
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    as
    1. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    2. Dai, Zhifeng & Zhu, Huan, 2020. "Stock return predictability from a mixed model perspective," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
    3. Yan, Wu & Powell, John G. & Shi, Jing & Xu, Wei, 2007. "Chinese stock market cyclical regimes: 1991-2006," Economics Letters, Elsevier, vol. 97(3), pages 235-239, December.
    4. Zhi Da & Joseph Engelberg & Pengjie Gao, 2015. "Editor's Choice The Sum of All FEARS Investor Sentiment and Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 28(1), pages 1-32.
    5. Kandel, Shmuel & Stambaugh, Robert F, 1996. "On the Predictability of Stock Returns: An Asset-Allocation Perspective," Journal of Finance, American Finance Association, vol. 51(2), pages 385-424, June.
    6. Hubrich, Kirstin & Tetlow, Robert J., 2015. "Financial stress and economic dynamics: The transmission of crises," Journal of Monetary Economics, Elsevier, vol. 70(C), pages 100-115.
    7. Illing, Mark & Liu, Ying, 2006. "Measuring financial stress in a developed country: An application to Canada," Journal of Financial Stability, Elsevier, vol. 2(3), pages 243-265, October.
    8. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    9. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    10. Gupta, Rangan & Hammoudeh, Shawkat & Modise, Mampho P. & Nguyen, Duc Khuong, 2014. "Can economic uncertainty, financial stress and consumer sentiments predict U.S. equity premium?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 367-378.
    11. Fama, Eugene F. & French, Kenneth R., 1988. "Dividend yields and expected stock returns," Journal of Financial Economics, Elsevier, vol. 22(1), pages 3-25, October.
    12. Zhang, Yaojie & Wei, Yu & Ma, Feng & Yi, Yongsheng, 2019. "Economic constraints and stock return predictability: A new approach," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 1-9.
    13. Tsiakas, Ilias & Li, Jiahan & Zhang, Haibin, 2020. "Equity premium prediction and the state of the economy," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 75-95.
    14. Mr. Subir Lall & Mr. Roberto Cardarelli & Mr. Selim A Elekdag, 2009. "Financial Stress, Downturns, and Recoveries," IMF Working Papers 2009/100, International Monetary Fund.
    15. Park, Cyn-Young & Mercado, Rogelio V., 2014. "Determinants of financial stress in emerging market economies," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 199-224.
    16. Wang, Yudong & Liu, Li & Ma, Feng & Diao, Xundi, 2018. "Momentum of return predictability," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 141-156.
    17. Xu, Yongan & Liang, Chao & Li, Yan & Huynh, Toan L.D., 2022. "News sentiment and stock return: Evidence from managers’ news coverages," Finance Research Letters, Elsevier, vol. 48(C).
    18. Mr. Stephan Danninger & Ms. Irina Tytell & Mr. Ravi Balakrishnan & Mr. Selim A Elekdag, 2009. "The Transmission of Financial Stress from Advanced to Emerging Economies," IMF Working Papers 2009/133, International Monetary Fund.
    19. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    20. Craig S. Hakkio & William R. Keeton, 2009. "Financial stress: what is it, how can it be measured, and why does it matter?," Economic Review, Federal Reserve Bank of Kansas City, vol. 94(Q II), pages 5-50.
    21. Stambaugh, Robert F. & Yu, Jianfeng & Yuan, Yu, 2012. "The short of it: Investor sentiment and anomalies," Journal of Financial Economics, Elsevier, vol. 104(2), pages 288-302.
    22. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," The Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.
    23. Ravi Balakrishnan & Stephan Danninger & Selim Elekdag & Irina Tytell, 2011. "The Transmission of Financial Stress from Advanced to Emerging Economies," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(0), pages 40-68, May.
    24. Jiang, Fuwei & Lee, Joshua & Martin, Xiumin & Zhou, Guofu, 2019. "Manager sentiment and stock returns," Journal of Financial Economics, Elsevier, vol. 132(1), pages 126-149.
    25. Feng Ma & Xinjie Lu & Ke Yang & Yaojie Zhang, 2019. "Volatility forecasting: long memory, regime switching and heteroscedasticity," Applied Economics, Taylor & Francis Journals, vol. 51(38), pages 4151-4163, August.
    26. Zhang, Yaojie & Lei, Likun & Wei, Yu, 2020. "Forecasting the Chinese stock market volatility with international market volatilities: The role of regime switching," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    27. Dashan Huang & Fuwei Jiang & Jun Tu & Guofu Zhou, 2015. "Investor Sentiment Aligned: A Powerful Predictor of Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 791-837.
    28. Liang, Chao & Xu, Yongan & Wang, Jianqiong & Yang, Mo, 2022. "Whether dimensionality reduction techniques can improve the ability of sentiment proxies to predict stock market returns," International Review of Financial Analysis, Elsevier, vol. 82(C).
    29. Tzu-Lun Huang, 2019. "The Chinese Media Effect in Bull and Bear Markets," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 20(3), pages 369-383, July.
    30. Narayan, Paresh Kumar & Liu, Ruipeng, 2018. "A new GARCH model with higher moments for stock return predictability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 56(C), pages 93-103.
    31. Wei, Yu & Zhang, Yaojie & Wang, Yudong, 2022. "Information connectedness of international crude oil futures: Evidence from SC, WTI, and Brent," International Review of Financial Analysis, Elsevier, vol. 81(C).
    32. Lodge, David & Soudan, Michel, 2019. "Credit, financial conditions and the business cycle in China," Working Paper Series 2244, European Central Bank.
    33. Linda Allen & Turan G. Bali & Yi Tang, 2012. "Does Systemic Risk in the Financial Sector Predict Future Economic Downturns?," The Review of Financial Studies, Society for Financial Studies, vol. 25(10), pages 3000-3036.
    34. Adrian R. Pagan & Kirill A. Sossounov, 2003. "A simple framework for analysing bull and bear markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 23-46.
    35. Dovern, Jonas & van Roye, Björn, 2014. "International transmission and business-cycle effects of financial stress," Journal of Financial Stability, Elsevier, vol. 13(C), pages 1-17.
    36. Yongan Xu & Jianqiong Wang & Zhonglu Chen & Chao Liang, 2023. "Sentiment indices and stock returns: Evidence from China," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 1063-1080, January.
    37. Liang, Chao & Tang, Linchun & Li, Yan & Wei, Yu, 2020. "Which sentiment index is more informative to forecast stock market volatility? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 71(C).
    38. Das, Debojyoti & Kannadhasan, M. & Bhattacharyya, Malay, 2019. "Do the emerging stock markets react to international economic policy uncertainty, geopolitical risk and financial stress alike?," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 1-19.
    39. Wang, Yudong & Wei, Yu & Wu, Chongfeng & Yin, Libo, 2018. "Oil and the short-term predictability of stock return volatility," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 90-104.
    40. Dong, Dayong & Yue, Sishi & Cao, Jiawei, 2020. "Site visit information content and return predictability: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    41. Alan J. Hanna & John D. Turner & Clive B. Walker, 2020. "News media and investor sentiment during bull and bear markets," The European Journal of Finance, Taylor & Francis Journals, vol. 26(14), pages 1377-1395, September.
    42. Gian Paulo Soave, 2020. "Financial conditions and the business cycles in emerging markets," Applied Economics Letters, Taylor & Francis Journals, vol. 27(20), pages 1652-1658, November.
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    More about this item

    Keywords

    Financial stress; Chinese stock market; Stock return; Forecasting;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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