Certainty of uncertainty for asset pricing

Fuwei Jiang, Jie Kang and Lingchao Meng

Journal of Empirical Finance, 2024, vol. 78, issue C

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.

Keywords: Economic uncertainty; Asset pricing; Return predictability; Machine learning; Market expectation (search for similar items in EconPapers)
JEL-codes: G12 G14 G17 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:78:y:2024:i:c:s0927539824000367

DOI: 10.1016/j.jempfin.2024.101501

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