Abstract
This study examines the co-movement and causality relationship between prices of crude oil, precious metals, and agricultural commodities. We use a novel approach called wavelet coherence analysis, which allows the measurement of co-movements in the time–frequency space based on the daily prices of commodities. We decompose data from September 1986 to September 2017 into 12 levels and 5 subperiods to find more generalized and convincing results. We confirm that commodity prices are in-phase and co-move. Particularly, the coherence is the largest in the long term and rises sharply in the mid-term during the crisis period. The heterogeneous directions of arrows provide strong evidence that the causality relationship between commodity prices varies over time for different frequencies. We find that the mixed commodities portfolio can provide diversification benefits in the mid-term horizons. The findings of this study can guide investors who want to benefit from diversification while investing in commodity markets.
| Original language | English |
|---|---|
| Journal | Empirical Economics |
| DOIs | |
| Publication status | Accepted/In press - Jan 1 2018 |
| Externally published | Yes |
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Keywords
- Agricultural commodities
- Crude oil
- Precious metals
- Sharp ratio
- Wavelet coherence analysis
ASJC Scopus subject areas
- Statistics and Probability
- Mathematics (miscellaneous)
- Social Sciences (miscellaneous)
- Economics and Econometrics
Cite this
Co-movements in commodity markets and implications in diversification benefits. / Cai, Xiao Jing; Fang, Zheng; Chang, Youngho; Tian, Shuairu; Hamori, Shigeyuki.
In: Empirical Economics, 01.01.2018.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Co-movements in commodity markets and implications in diversification benefits
AU - Cai, Xiao Jing
AU - Fang, Zheng
AU - Chang, Youngho
AU - Tian, Shuairu
AU - Hamori, Shigeyuki
PY - 2018/1/1
Y1 - 2018/1/1
N2 - This study examines the co-movement and causality relationship between prices of crude oil, precious metals, and agricultural commodities. We use a novel approach called wavelet coherence analysis, which allows the measurement of co-movements in the time–frequency space based on the daily prices of commodities. We decompose data from September 1986 to September 2017 into 12 levels and 5 subperiods to find more generalized and convincing results. We confirm that commodity prices are in-phase and co-move. Particularly, the coherence is the largest in the long term and rises sharply in the mid-term during the crisis period. The heterogeneous directions of arrows provide strong evidence that the causality relationship between commodity prices varies over time for different frequencies. We find that the mixed commodities portfolio can provide diversification benefits in the mid-term horizons. The findings of this study can guide investors who want to benefit from diversification while investing in commodity markets.
AB - This study examines the co-movement and causality relationship between prices of crude oil, precious metals, and agricultural commodities. We use a novel approach called wavelet coherence analysis, which allows the measurement of co-movements in the time–frequency space based on the daily prices of commodities. We decompose data from September 1986 to September 2017 into 12 levels and 5 subperiods to find more generalized and convincing results. We confirm that commodity prices are in-phase and co-move. Particularly, the coherence is the largest in the long term and rises sharply in the mid-term during the crisis period. The heterogeneous directions of arrows provide strong evidence that the causality relationship between commodity prices varies over time for different frequencies. We find that the mixed commodities portfolio can provide diversification benefits in the mid-term horizons. The findings of this study can guide investors who want to benefit from diversification while investing in commodity markets.
KW - Agricultural commodities
KW - Crude oil
KW - Precious metals
KW - Sharp ratio
KW - Wavelet coherence analysis
UR - http://www.scopus.com/inward/record.url?scp=85053475151&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85053475151&partnerID=8YFLogxK
U2 - 10.1007/s00181-018-1551-3
DO - 10.1007/s00181-018-1551-3
M3 - Article
AN - SCOPUS:85053475151
JO - Empirical Economics
JF - Empirical Economics
SN - 0377-7332
ER -