Macroeconomic attention and commodity market volatility

In this paper, we empirically examine the relationship between the novel macroeconomic attention indices (MAI) and commodity market volatility. In-sample analysis indicates that MAI contribute significantly to the volatility fluctuations in commodity markets. In addition, we employ dimension reducti...

Full description

Saved in:
Bibliographic Details
Published in:Empirical economics 2024-11, Vol.67 (5), p.1967-2007
Main Authors: Stavroula, Fameliti, Vasiliki, Skintzi
Format: Article
Language:English
Subjects:
Attention
Commodities
Commodity markets
Commodity prices
Crude oil
Econometrics
Economic indicators
Economic theory
Economic Theory/Quantitative Economics/Mathematical Methods
Economics
Economics and Finance
Finance
Forecasting
Gold
Insurance
International finance
Investments
Investor behavior
Macroeconomics
Management
Predictions
Robustness
Securities markets
Statistics for Business
Uncertainty
Volatility
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, we empirically examine the relationship between the novel macroeconomic attention indices (MAI) and commodity market volatility. In-sample analysis indicates that MAI contribute significantly to the volatility fluctuations in commodity markets. In addition, we employ dimension reduction techniques, shrinkage methods, and combination models in an out-of-sample exercise to assess the predictive ability of MAI, alongside a variety of economic predictors including uncertainty measures, and global as well as US economic indicators. Our empirical results demonstrate the superior predictive ability of the elastic net and LASSO models incorporating MAI together with macroeconomic and uncertainty indicators. This empirical finding is reinforced through a series of robustness checks. However, dimension reduction methods exhibit superior performance in longer forecast horizons. Finally, MAI are more informative for commodity volatility forecasting during economic expansions and non-crisis periods. Our study offers new insights on commodity volatility forecasting.
ISSN:0377-7332
1435-8921
DOI:10.1007/s00181-024-02613-z