2019
DOI: 10.1111/obes.12334
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What Drives Commodity Returns? Market, Sector or Idiosyncratic Factors?

Abstract: This paper examines the relationship between 43 commodity returns using a dynamic factor model with time varying stochastic volatility. The dynamic factor model decomposes each commodity return into a common (market), sector‐specific and commodity‐specific component. It enables the variance attributed to each component to be estimated at each point in time. We find the return variation explained by the common factor has increased substantially for the recent period and is statistically significant for the vast… Show more

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Cited by 11 publications
(11 citation statements)
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“…For the multivariate regressions, we further estimate the contribution of each variable to the variance of the dependent variable. Following Ma et al (2019), we adopt Shapley's (1953) concept to estimate the exact contribution of each explanatory variable to the regression R-square. In addition to the single contribution of each macroeconomic factor, we further estimate the contributions of two groups: (i)…”
Section: Contributions Of Macroeconomic Factorsmentioning
confidence: 99%
“…For the multivariate regressions, we further estimate the contribution of each variable to the variance of the dependent variable. Following Ma et al (2019), we adopt Shapley's (1953) concept to estimate the exact contribution of each explanatory variable to the regression R-square. In addition to the single contribution of each macroeconomic factor, we further estimate the contributions of two groups: (i)…”
Section: Contributions Of Macroeconomic Factorsmentioning
confidence: 99%
“…Specifically, whereas Japan also experienced increasing mean reversion around the mid‐1980s, its mean reversion is strongest around the mid‐1990s right after the collapse of its asset price bubbles. Canada, however, experienced its strongest mean reversion between the early to mid‐2000s, which seems to correspond well to the rising global commodity prices during that period (see, for example, Ma, Vivian and Wohar, 2020) and makes sense given a strong association between its currency and commodities (see, e.g. Chen and Rogoff, 2003).…”
Section: Empirical Analysismentioning
confidence: 87%
“…The respective coefficients, , are sizable and statistically distinguishable from zero at the 0.01 level. Similarly, Ma et al (2020) demonstrate a negative link between the US trade-weighted exchange rate and a common factor of commodity returns. Balcilar et al (2014) point out that swings in the US dollar exchange rate reveal shifts in investors’ risk appetite, since they could lure investors into or drive them away from the USD-denominated investment assets.…”
Section: Empirical Evidencementioning
confidence: 93%