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A closer look at return predictability of the US stock market: evidence from new panel variance ratio tests

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  • Jae H. Kim
  • Abul Shamsuddin

Abstract

This paper examines the return predictability of the US stock market using portfolios sorted by size, book-to-market ratio and industry. We use novel panel variance ratio tests, based on the wild bootstrap proposed in this paper, which exhibit desirable size and power properties in small samples. We have found evidence that stock returns have been highly predictable from 1964 to 1996, except for a period leading to the 1987 crash and its aftermath. After 1997, stock returns have been unpredictable overall. At a disaggregated level, we find evidence that large-cap portfolios have been priced more efficiently than small- or medium-cap portfolios; and that the stock returns from high-tech industries are far less predictable than those from non-high-tech industries.

Suggested Citation

  • Jae H. Kim & Abul Shamsuddin, 2015. "A closer look at return predictability of the US stock market: evidence from new panel variance ratio tests," Quantitative Finance, Taylor & Francis Journals, vol. 15(9), pages 1501-1514, September.
    • Handle: RePEc:taf:quantf:v:15:y:2015:i:9:p:1501-1514
    DOI: 10.1080/14697688.2014.1002419
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    Citations

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    Cited by:

    1. Rahman, Md. Lutfur & Lee, Doowon & Shamsuddin, Abul, 2017. "Time-varying return predictability in South Asian equity markets," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 179-200.
    2. Md Lutfur Rahman & Mahbub Khan & Samuel A. Vigne & Gazi Salah Uddin, 2021. "Equity return predictability, its determinants, and profitable trading strategies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 162-186, January.
    3. Awijen, Haithem & Ben Zaied, Younes & Ben Lahouel, Béchir & Khlifi, Foued, 2023. "Machine learning for US cross-industry return predictability under information uncertainty," Research in International Business and Finance, Elsevier, vol. 64(C).
    4. Charalampos Stasinakis & Georgios Sermpinis & Ioannis Psaradellis & Thanos Verousis, 2016. "Krill-Herd Support Vector Regression and heterogeneous autoregressive leverage: evidence from forecasting and trading commodities," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1901-1915, December.
    5. Eva Regnier, 2018. "Probability Forecasts Made at Multiple Lead Times," Management Science, INFORMS, vol. 64(5), pages 2407-2426, May.

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