Macroeconomic attention, economic policy uncertainty, and stock volatility predictability

被引:33
|
作者
Ma, Feng [1 ]
Guo, Yangli [1 ]
Chevallier, Julien [2 ,3 ]
Huang, Dengshi [1 ]
机构
[1] Southwest Jiaotong Univ, Sch Econ & Management, Chengdu, Peoples R China
[2] IPAG Business Sch, IPAG Lab, 184 Blvd St Germain, F-75006 Paris, France
[3] Univ Paris 8 LED, 2 rue Liberte, F-93526 St Denis, France
关键词
Stock return volatility predictability; Macroeconomic attention indices; Category-specific EPU indices; sPCA; PCA; PLS; MARKET VOLATILITY; RETURN PREDICTABILITY; RISK PREMIUM; LONG-RUN; SAMPLE; TESTS; OIL; PREDICTION; SENTIMENT; G7;
D O I
10.1016/j.irfa.2022.102339
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
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 (F-t(All)) has the strongest short-term forecasting ability, whereas the MAI show the most substantial forecasting ability in long-term forecasting.
引用
收藏
页数:23
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