Journal of Commodity Markets最新文献

This paper conducts a large-scale multi-country longitudinal study and examines the extent that firms are exposed to commodity price risk in 23 OECD countries. An industry analysis reveals that all industries are significantly exposed to commodity price movements ranging between 8 and 10% except for the energy sector where 38% of firms being significantly exposed. Investigating the determinants of commodity price exposure, we report that firm size is negatively associated with commodity exposure, while the fraction of R&D expenses, leverage, country GDP, and sophistication of the financial derivatives markets are positively related to commodity price exposure.

This paper studies the spread of Brent-WTI futures prices using a no-arbitrage term structure model with one common and two latent idiosyncratic risk factors. We document more negative risk premia for WTI than for Brent, and the differences are more pronounced at longer maturities. The expectation of future spot price dominates the risk premium in determining the term structure of Brent-WTI futures spread, especially at short maturities. The common risk premia in both markets are negative and similar, while their corresponding idiosyncratic risk premia have opposite signs. The common risk prices of WTI and Brent are generally related to the US crude commercial stock, inflation, economic uncertainty, and hedging pressure; however, idiosyncratic risk prices are more related to their corresponding local production, short rate, and the term structure factors. The variance decomposition indicates that the idiosyncratic factors account for a considerable part at longer forecast horizons in both markets.

The paper examines the frequency-based interlinkages between stock indices and precious metals at extreme and median quantiles. It employs the quantile cross-spectral approach (Baruník and Kley, 2019) and the novel frequency quantile connectedness analysis (Chatziantoniou et al., 2021) to a sample of stocks and precious metals returns. The results show that the interdependence between equity indices and precious metals markets is contingent on the state of the market (bear, bull, or normal) and the horizon of frequency domains. Of all precious metals, the diversification benefits from gold, followed by silver, are consistently the highest for SP500 and STOXX50 and the least with palladium in most cases. The same holds when we investigate the diversification potential of precious metals for industrial sectors in the US and UK. A quantile frequency connectedness approach reveals that the diversification potential of precious metals diminishes in the long frequency horizon as coherence with stock indices becomes highly positive. The connectedness between stock indices and precious metals is high during market extremities but dampens as the market attains stability. At the same time, connectedness increases during periods of financial turmoil across all frequencies. We also document a change in the diversification role of precious metals during COVID-19.

We develop a theoretical framework and propose a relevant empirical analysis of the soybean-complex prices’ cointegration relationships in a high-frequency setting. We allow for heterogeneous expectations among traders on the multi-asset price dynamics and characterize the resulting market behaviour. We demonstrate that the asset prices’ autoregressive matrix rank and the speed of reversion towards the long-term equilibrium are related to the market realized and potential liquidity, unlike the cointegrating vector. Our empirical application to the soybean complex, where we control for volatility, supports our theoretical results when the price idleness of the different assets is properly accounted for. Our analysis further suggests that the presence of cointegration among assets is related to the time of day and the contract maturities traded at a given time.

This study examines the spillovers from Crude Oil price fluctuations to sovereign credit risk, proxied by CDS spreads for 16 oil exporters and importers belonging to G20. Besides measuring shocks from Crude Oil to sovereign risk, it also examined the system-wide impacts of CDS shocks to understand their magnified impacts within a system. Furthermore, the study finds the channels that have the potential to act as a carrier of shocks from Crude Oil to sovereign risk considering four country-specific and two global factors. Our study deployed Generalized Impulse Response Functions and Generalized Forecast Error Variance Decomposition for being independent of ordering. Additionally, DCC-GARCH has been applied to test the robustness of the results. Our results highlight higher spillovers to oil-exporting countries from Crude Oil when compared to oil importers, irrespective of their development stage. Interestingly, developed countries are severely impacted by net system-wide shocks from developing and oil-exporting countries. Moreover, Global factors play a dominant role in carrying the shocks from Crude Oil to sovereign risk of countries. Stock market indices are important among important domestic factors that act as carriers of shocks, and VIX is robust amongst global variables. Our results are valuable to Regulators, policymakers, portfolio managers, banks, and financial institutions for proactively planning their respective policies.

The derivative accounting standard requires hedging to satisfy the 80–125 rule to be eligible to apply the hedge accounting treatment. This means the hedging relationship should achieve hedging effectiveness within the 80%–125% level to qualify for hedge accounting. The appropriateness of this screening criterion is questioned in the existing literature, and there is hardly any empirical evidence to justify the suitability of this threshold level of hedge effectiveness. By applying meta-analysis methodology for 1699 hedge ratios collected from previous academic studies in commodity futures hedging, we show that the average optimal hedge ratio in commodity futures hedging in the academic literature mostly overlaps with the 80–125 threshold.

In this paper, we explore whether falls in commodity prices can explain the simultaneous occurrence of currency crises in emerging and developing countries. For our empirical analysis, we use a panel of 104 emerging and developing countries, covering the period 1970–2018. Our empirical investigation starts with an event study analysis, which reveals that currency crises in commodity dependent countries are preceded by commodity price growth 2 to 4 percentage points below normal. A second analysis, inspired by the literature on early warning systems, confirms this findings by showing that commodity price fluctuations are a key predictor of currency crises in commodity dependent countries. In addition, using Poisson regression analysis, we find that a 10% decrease in global commodity price indices leads to a rise of about 7% in the number of currency crises hitting commodity exporting countries.

In this study, we examine whether the key findings in Tang and Xiong (2012) hold in the more recent sample years after their publication. We also explore the impact of financialization on different aspects of commodity futures markets in more detail. Our analysis shows that financialization leads to a significant increase of the correlation between the commodity and stock market returns. This return correlation structure change is robust to different commodity and stock market return computation methods, and is persistent for the more recent post-Tang-and-Xiong-(2012) subsample period. We find that after financialization, the importance of non-commercial traders elevates, the pairwise correlation between the indexed commodity futures increases, and the basis becomes more negative on commodity futures markets.

Several common properties shared by cryptocurrencies and precious metals, such as safe haven, hedge and diversification for risk assets, have been widely discussed since Bitcoin was created in 2008. However, no studies have explored whether cryptocurrency market uncertainties can help to explain and forecast volatilities in precious metal markets. By using the GARCH-MIDAS model incorporating cryptocurrency policy and price uncertainty, as well as several other commonly used uncertainty measures, this paper compares the in-sample impacts and out-of-sample predictive abilities of these uncertainties on volatility forecasts of COMEX gold and silver futures markets. The in-sample results demonstrate the significant impacts of cryptocurrency uncertainty on the volatilities of precious metal futures markets, and the out-of-sample evidence further confirms the superior predictive power of cryptocurrency uncertainty on volatility forecasting of the precious metal market. Our conclusions are robust through various model evaluation approaches based not only on predicting errors but also on forecasting directions across different forecasting time horizons.

This paper takes a cross-country and cross-sector perspective to investigate the drivers of commodity momentum strategies. Commodity momentum strategies deployed in the U.S. and Chinese markets generate positive average returns with non-negligible correlations, but their premia are primarily local, and their return characteristics are distinct. A prevalent sector effect explains a significant fraction of momentum profits in both markets, suggesting that long-short commodity futures momentum may be riskier than previously thought. Overall, our findings suggest commodity momentum is more consistent with a risk-based explanation in U.S. markets whereas risk alone is difficult to capture the premia in China.