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Stock Market Predictability and Industrial Metal Returns

Author

Listed:
  • Ben Jacobsen

    (TIAS School for Business and Society, 5000 LE Tilburg, Netherlands)

  • Ben R. Marshall

    (School of Economics and Finance, Massey University, Palmerston North 422, New Zealand)

  • Nuttawat Visaltanachoti

    (School of Economics and Finance, Massey University, Palmerston North 422, New Zealand)

Abstract

Price movements in industrial metals such as copper and aluminum predict stock returns. Increasing industrial metal prices are good news for equity markets in recessions and bad news in expansions. A one-standard-deviation increase in industrial metal returns predicts a price drop of one and a half percent in monthly stock market returns in expansions and an increase of around a half percent during recessions. The predictability is distinct to and compares favorably with that from more established predictors.

Suggested Citation

  • Ben Jacobsen & Ben R. Marshall & Nuttawat Visaltanachoti, 2019. "Stock Market Predictability and Industrial Metal Returns," Management Science, INFORMS, vol. 65(7), pages 3026-3042, July.
  • Handle: RePEc:inm:ormnsc:v:65:y:2019:i:7:p:3026-3042
    DOI: 10.1287/mnsc.2017.2933
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    Cited by:

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    7. Yahya, Muhammad & Ghosh, Sajal & Kanjilal, Kakali & Dutta, Anupam & Uddin, Gazi Salah, 2020. "Evaluation of cross-quantile dependence and causality between non-ferrous metals and clean energy indexes," Energy, Elsevier, vol. 202(C).
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    9. Liu, Guangqiang & Guo, Xiaozhu, 2022. "Forecasting stock market volatility using commodity futures volatility information," Resources Policy, Elsevier, vol. 75(C).
    10. Julia S. Mehlitz & Benjamin R. Auer, 2021. "Time‐varying dynamics of expected shortfall in commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(6), pages 895-925, June.
    11. Xianfeng Hao & Yudong Wang, 2023. "Cloud cover and expected oil returns," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-10, December.
    12. Mengxi He & Yudong Wang & Yaojie Zhang, 2023. "The predictability of iron ore futures prices: A product‐material lead–lag effect," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(9), pages 1289-1304, September.
    13. Fabian Hollstein & Marcel Prokopczuk & Christoph Würsig, 2020. "Volatility term structures in commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(4), pages 527-555, April.
    14. Crespo-Cuaresma, Jesus & Fortin, Ines & Hlouskova, Jaroslava & Obersteiner, Michael, 2021. "Regime-dependent commodity price dynamics: A predictive analysis," IHS Working Paper Series 28, Institute for Advanced Studies.
    15. , & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," CEPR Discussion Papers 16357, C.E.P.R. Discussion Papers.
    16. Huang, Dashan & Li, Jiangyuan & Wang, Liyao, 2021. "Are disagreements agreeable? Evidence from information aggregation," Journal of Financial Economics, Elsevier, vol. 141(1), pages 83-101.
    17. Ana Monteiro & Nuno Silva & Helder Sebastião, 2023. "Industry return lead-lag relationships between the US and other major countries," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-48, December.
    18. Rakesh Shahani & Utkarsh Singhal, 2023. "Do efficient commodity markets co-move: evidence from Indian base metals market," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 36(3), pages 413-425, September.
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    20. Xiao, Jihong & Wang, Yudong, 2022. "Good oil volatility, bad oil volatility, and stock return predictability," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 953-966.

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