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Certainty of uncertainty for asset pricing

Author

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  • Jiang, Fuwei
  • Kang, Jie
  • Meng, Lingchao

Abstract

Uncertainty is known to be crucial in asset pricing, yet evidence from a comprehensive analysis of various uncertainty measures remains sparse. By machine learning, we construct a novel economic uncertainty index derived from a heterogeneous range of uncertainty measures and investigate its predictability of stock returns. Our composite uncertainty index exhibits robust in- and out-of-sample predictability of stock market returns over the one- to 12-month horizon. The predictive power stems from the volatility-orthogonal components of individual uncertainty measures and becomes more pronounced during high uncertainty and high sentiment periods. The predictability of our economic uncertainty index aligns with theoretical frameworks linking uncertainty to future investment, cash flows, and market expectations.

Suggested Citation

  • Jiang, Fuwei & Kang, Jie & Meng, Lingchao, 2024. "Certainty of uncertainty for asset pricing," Journal of Empirical Finance, Elsevier, vol. 78(C).
    • Handle: RePEc:eee:empfin:v:78:y:2024:i:c:s0927539824000367
    DOI: 10.1016/j.jempfin.2024.101501
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    Keywords

    Economic uncertainty; Asset pricing; Return predictability; Machine learning; Market expectation;
    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
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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