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Forecasting US stock market returns by the aggressive stock-selection opportunity

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  • Li, Yan
  • Liang, Chao
  • Huynh, Toan Luu Duc

Abstract

We propose a measurement of aggressive stock-selection opportunity based on positive alphas and idiosyncratic volatilities of cross-section stocks, and examine the role of aggressive stock-selection opportunity in predicting stock market returns. For the US stock market, we find that the change of aggressive stock-selection opportunity has a significant and negative coefficient for predicting future one-month market returns. The out-of-sample results also show the change of aggressive stock-selection opportunity improves the return forecasting performance and increases investors’ economic values. In particular, the predictive information of the change of aggressive stock-selection opportunity is independent of traditional macroeconomic predictors. The economic channel evidence shows that the change of aggressive stock-selection opportunity increases future market volatility and then results in lower market returns.

Suggested Citation

  • Li, Yan & Liang, Chao & Huynh, Toan Luu Duc, 2022. "Forecasting US stock market returns by the aggressive stock-selection opportunity," Finance Research Letters, Elsevier, vol. 50(C).
    • Handle: RePEc:eee:finlet:v:50:y:2022:i:c:s1544612322005025
    DOI: 10.1016/j.frl.2022.103323
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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. Guo, Hui, 2006. "Time-varying risk premia and the cross section of stock returns," Journal of Banking & Finance, Elsevier, vol. 30(7), pages 2087-2107, July.
    3. Suk Joon Byun & Bart Frijns & Tai‐Yong Roh, 2018. "A comprehensive look at the return predictability of variance risk premia," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(4), pages 425-445, April.
    4. 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.
    5. Wang, Yudong & Diao, Xundi & Pan, Zhiyuan & Wu, Chongfeng, 2019. "Heterogeneous beliefs and aggregate market volatility revisited: New evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 55(C), pages 127-141.
    6. 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.
    7. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    8. Bollerslev, Tim & Marrone, James & Xu, Lai & Zhou, Hao, 2014. "Stock Return Predictability and Variance Risk Premia: Statistical Inference and International Evidence," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(3), pages 633-661, June.
    9. Amit Goyal & Ivo Welch, 2003. "Predicting the Equity Premium with Dividend Ratios," Management Science, INFORMS, vol. 49(5), pages 639-654, May.
    10. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    11. He, Mengxi & Zhang, Yaojie & Wen, Danyan & Wang, Yudong, 2021. "Forecasting crude oil prices: A scaled PCA approach," Energy Economics, Elsevier, vol. 97(C).
    12. Jin, Xiaoye, 2017. "Time-varying return-volatility relation in international stock markets," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 157-173.
    13. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    14. Liu, Li & Ma, Feng & Wang, Yudong, 2015. "Forecasting excess stock returns with crude oil market data," Energy Economics, Elsevier, vol. 48(C), pages 316-324.
    15. John Y. Campbell & Tuomo Vuolteenaho, 2004. "Bad Beta, Good Beta," American Economic Review, American Economic Association, vol. 94(5), pages 1249-1275, December.
    16. 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.
    17. Lewellen, Jonathan, 2004. "Predicting returns with financial ratios," Journal of Financial Economics, Elsevier, vol. 74(2), pages 209-235, November.
    18. Bekaert, Geert & Wu, Guojun, 2000. "Asymmetric Volatility and Risk in Equity Markets," The Review of Financial Studies, Society for Financial Studies, vol. 13(1), pages 1-42.
    19. 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.
    20. Wang, Yudong & Ma, Feng & Wei, Yu & Wu, Chongfeng, 2016. "Forecasting realized volatility in a changing world: A dynamic model averaging approach," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 136-149.
    21. Zhang, Yaojie & Ma, Feng & Liao, Yin, 2020. "Forecasting global equity market volatilities," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1454-1475.
    22. Wang, Yudong & Pan, Zhiyuan & Liu, Li & Wu, Chongfeng, 2019. "Oil price increases and the predictability of equity premium," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 43-58.
    23. Wang, Xunxiao, 2020. "Frequency dynamics of volatility spillovers among crude oil and international stock markets: The role of the interest rate," Energy Economics, Elsevier, vol. 91(C).
    24. Mark W. Watson & James H. Stock, 2004. "Combination forecasts of output growth in a seven-country data set," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(6), pages 405-430.
    25. Anderson, Robert M. & Bianchi, Stephen W. & Goldberg, Lisa R., 2012. "Will My Risk Parity Strategy Outperform?," Department of Economics, Working Paper Series qt23t2s950, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    26. Jiang, George J. & Zaynutdinova, Gulnara R. & Zhang, Huacheng, 2021. "Stock-selection timing," Journal of Banking & Finance, Elsevier, vol. 125(C).
    27. Dai, Zhifeng & Zhou, Huiting & Kang, Jie & Wen, Fenghua, 2021. "The skewness of oil price returns and equity premium predictability," Energy Economics, Elsevier, vol. 94(C).
    28. Jian Chen & Fuwei Jiang & Guoshi Tong, 2017. "Economic policy uncertainty in China and stock market expected returns," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 57(5), pages 1265-1286, December.
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    More about this item

    Keywords

    Stock-selection opportunity; Aggressive stock-selection opportunity; Stock market returns; Forecasting returns;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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