Macroeconomic attention, economic policy uncertainty, and stock volatility predictability

Feng Ma, Yangli Guo, Julien Chevallier and Dengshi Huang

International Review of Financial Analysis, 2022, vol. 84, issue C

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.

Keywords: Stock return volatility predictability; Macroeconomic attention indices; Category-specific EPU indices; sPCA; PCA; PLS (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (21)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:84:y:2022:i:c:s1057521922002897

DOI: 10.1016/j.irfa.2022.102339

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