Journal of Commodity Markets最新文献

The threat of short-term supply disruptions may matter for commodity prices, although their magnitude is hard to detect, for example due to anticipation, storage and to the relatively short duration of disruption events. This article explores global commodity returns for copper around labor strikes in Chile mines between 1910 and 2010. In the five days around strikes, copper display cumulative abnormal returns (CAR) close to 200 basis points (bps). Consistent with the threat of supply disruptions, the effect comes almost fully from strikes at larger mines (CAR≈ 500 bps). Moreover, the price-increasing effect of strikes is stronger when copper inventories are scarce, as measured by the interest-adjusted basis. Despite strikes being transitory events, we also find a mirroring appreciation of the USD/CLP commodity currency.

This study provides a thorough analysis of the dynamics of volatility and dependence among seven international equity and 20 commodity markets across different sectors, highlighting the hedging role played by the latter. We explain volatility using a specification that distinguishes between the short and long terms. At the same time, the dependence structure is modeled through a time-varying conditional factor copula model, which can be split into commodity sectors such that there is homogeneous dependence within each sector. The dynamic of both models is captured through a score-driven specification. Moreover, we solve the risk-averse portfolio selection to determine the existence of diversification benefits when constructing portfolios comprising commodities and stock markets. The main results of the study show that the dependence between the commodity and equity markets is variable over time. The best strategy in the minimum variance portfolio is obtained by incorporating a mix of commodities into the stock market portfolio, especially industrial metals. Furthermore, the factor copula approach is the best specification in terms of the Sharpe ratio independent of portfolio settings.

In this paper, by using the time-varying parameter vector autoregression model (TVP-VAR) with the asymmetric connectedness indicator and network diagrams, we investigate the dynamic and asymmetric return connectedness in the global “Carbon-Energy-Stock” system, including carbon markets and stock markets of the three largest economies, namely the United States, European Union and China, and fossil energies of crude oil and natural gas under exogenous shocks. Our study shows that (i) the risk spillover level of the global system has significantly increased after the outbreak of two exogenous events, the COVID-19 pandemic and the Russo-Ukrainian war, and the global shock from the COVID-19 pandemic has more widespread and greater impact on the system than the geopolitical shock from the Russo-Ukrainian war, (ii) the global “Carbon-Energy-Stock” system is more sensitive to negative information on price returns than positive information, and the asymmetry of the connectedness is much larger when the system is active and in the presence of exogenous shocks, (iii) risks in the global “Carbon-Energy-Stock” system usually transformed from stock markets, especially the stock markets of the United States and European Union, to the carbon markets. These findings provide valuable guidance and have economic implications for both investors and policymakers worldwide.

Hedging in grain futures markets offers market participants the opportunity to mitigate the price risk in spot markets by taking offsetting positions in futures. The performance of a traditional minimum variance hedge ratio (MVHR) relies on the correlation between the spot and futures price changes. During 2005–2010, delivery-location cash prices for several crops decoupled from the prices for their related expiring futures contracts—raising concerns over the hedging effectiveness of these contracts. We investigate how short hedgers, like farmers, performed during periods with and without convergence in corn, soybean, and wheat markets. We show that, ex post, MVHR, often does not minimize the variance of wheat producers’ profits during nonconvergence when compared to a range of other hedging choices. We also find that the performance of MVHR weakens during years with low carryover. We further assess hedging performance of MVHR and other hedge ratios in achieving higher net selling prices, and find that nonconvergence particularly impairs their performance in the wheat market where the nonconvergence anomaly was the most prominent. Taken together, our results raise questions on the role of futures markets as risk management tools during nonconvergence episodes regardless of how the hedge ratio is chosen.

The financialization of commodity markets is a well-documented phenomenon spurred by the massive growth of institutional funds directed into commodity indices from the mid-2000s. More recent research suggests that a subsequent era of de-financialization has coincided with the retreat of institutional investors. This paper uses a latent factor model to examine the dynamic impact of commodity market financialization on spot currency, commodity and equity market linkages, focusing on countries with ‘commodity currencies’. The financialization period is characterized by increased interdependence of non-oil and oil commodity markets with each other and with other asset markets, implying reduced diversification potential. We find that commodity markets have become more highly interconnected with currency and equity markets of the large commodity exporters over the most recent sub-sample. We suggest that apparent de-financialization may be attributable to contagion effects from global crisis events, including the Great Recession and the European Debt Crisis of 2012.

This paper investigates the performance of nine commonly discussed market anomalies in the Chinese commodity market. By studying a data sample from 2005 to 2020, we find the common risk factors associated with term structure and momentum anomalies effectively explain the cross-sectional excess returns and generate profitable sorting portfolios. Meanwhile, we empirically demonstrate that the term structure and momentum risk factors significantly crash during periods of high market stress, although they bring overall good outperformance in out-of-sample. We attribute these crashes to high time-varying volatility. Inspired by the augmented momentum crash strategy of Daniel and Moskowitz (2016), we construct augmented term structure and momentum risk factors to improve their performances in the Chinese commodity futures market. The out-of-sample Sharpe ratios of the term structure and momentum risk factors increase from 0.75 to 1.08 and from 0.66 to 0.77, respectively. In particular, both risk factors exhibit over 100% increments in out-of-sample Sharpe ratios during bear markets.

Crude oil intraday return curves collected from commodity futures markets often appear to be serially uncorrelated and long-range conditionally heteroscedastic. We model this stylised feature with a newly proposed functional GARCH-X model and use it to forecast crude oil intraday volatility. The predicted intraday volatility provides important economic implications in crude oil commodity futures markets in both intraday risk management and utility benefits improvements. The functional GARCH-X model provides a remarkable correction to modelling crude oil volatility in terms of an in-sample fitting, although its out-of-sample performances in forecasting intraday risk measures do not appear to be significantly superior to that of the existing functional GARCH(1,1) model. However, the FGARCH-X model, with its flexibility to capture long-range dependence and potential seasonality, does confer substantial economic benefits by embedding inter-daily volatility forecasts. Methodologically, we show that the new model has a well-behaved stationary solution, and we also address the inherent and critical issues associated with the estimation of functional volatility models by introducing novel data-driven, non-negative and predictive basis functions in the estimation process.

Despite the important impact of commodity terms-of-trade (CTOT) on GDP growth, child mortality rates and public debt, little is known about its determinants. Using data from 178 countries (grouped according to their commodity export-import structure) over the period 1962 to 2020, we examine the short-and long-run effects of global economic activity, OECD and emerging markets growth, the exchange rate of U.S. dollar, stock price volatility and real interest rates on CTOT growth. We demonstrate their typical asymmetric effect on exporters and importers, and show, for example, that the exchange rate of the U.S. dollar also exhibits opposite effects over the short and long run due to inelastic commodity demand. We find that the growth of emerging market economies provides the most universal and consistent effect across all of our subsamples (i.e., energy and non-energy exporters and importers) - this latter point underscores the contemporary global importance of developing countries' growth.

This paper investigates the possibility of psychological barriers in the price dynamics of seven types of coffee varieties over a twenty-year period. When prices are expressed in hundreds of cents, barriers surrounding the round number prices ending in 00 are confirmed for the high quality coffees. The dynamics of coffee price returns differ before and after breaches of hypothesised barriers. Using a novel model selection method based on multiple testing, there is further confirmation of price barriers insofar as positive and negative climate anomalies affect coffee price proximity to barriers.

The paper aims to explore the presence of connectedness between oil price changes and stock returns of oil & gas sector. The analysis, adopting the connectedness approach developed by and the frequency connectedness developed by demonstrates a high level of connectedness, especially during the extreme economic meltdown. The short-term (1–5 days) level of total connectedness is substantially higher than the medium-term (5–30 days) and long-term levels (30–262 days). In addition, when examining the impact of the sectors' financial characteristics on the extent of the connectedness, we found that sectors with greater solvency position (lower debt to asset ratio and higher interest coverage) are less connected with the oil price changes. The impact of sector's solvency position on connectedness (between stock return and oil prices) is even more obvious for financially more open markets. Also, change in oil prices have a less impact on the returns of sectors with higher profitability ratios. The paper, therefore, brings several implications to both policy makers and investors.