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Macroeconomic attention, economic policy uncertainty, and stock volatility predictability

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  • Ma, Feng
  • Guo, Yangli
  • Chevallier, Julien
  • Huang, Dengshi

Abstract

This study adopts the newly constructed macroeconomic attention indices (MAI) and category-specific economic policy uncertainty (EPU) indices to predict stock volatility. Principal component analysis (PCA), scaled PCA (sPCA), and partial least squares (PLS) are used to extract the principal components from indicators. The results show that the combination of MAI and EPU indices can obtain additional information for predicting stock market volatility. In addition, the comprehensive index containing all indicator information (FtAll) has the strongest short-term forecasting ability, whereas the MAI show the most substantial forecasting ability in long-term forecasting.

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  • Ma, Feng & Guo, Yangli & Chevallier, Julien & Huang, Dengshi, 2022. "Macroeconomic attention, economic policy uncertainty, and stock volatility predictability," International Review of Financial Analysis, Elsevier, vol. 84(C).
    • Handle: RePEc:eee:finana:v:84:y:2022:i:c:s1057521922002897
    DOI: 10.1016/j.irfa.2022.102339
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