Variance risk in commodity markets

We analyze the variance risk of commodity markets. We construct synthetic variance swaps and find significantly negative realized variance swap payoffs in most markets. We find evidence of commonalities among the realized payoffs of commodity variance swaps. We also document comovements between the realized payoffs of commodity, equity and bond variance swaps. Similar results hold for expected variance swap payoffs. Furthermore, we show that both realized and expected commodity variance swap payoffs are distinct from the realized and expected commodity futures returns, indicating that variance risk is unspanned by commodity futures.     

Limits to arbitrage and hedging: Evidence from commodity markets

We build an equilibrium model of commodity markets in which speculators are capital constrained, and commodity producers have hedging demands for commodity futures. Increases in producers' hedging demand or speculators' capital constraints increase hedging costs via price-pressure on futures. These in turn affect producers' equilibrium hedging and supply decision inducing a link between a financial friction in the futures market and the commodity spot prices. Consistent with the model, measures of producers' propensity to hedge forecasts futures returns and spot prices in oil and gas market data from 1979 to 2010. The component of the commodity futures risk premium associated with producer hedging demand rises when speculative activity reduces. We conclude that limits to financial arbitrage generate limits to hedging by producers, and affect equilibrium commodity supply and prices.     

Sources of Systematic Risk in Futures and Spot Markets: A Study of Market Integration

This article explains the implications of asset market integration for the decision making process of market participants and tests the integration between futures and spot markets. Integration is investigated with respect to the hypothesis that the sources of systematic risk in futures and spot markets command identical risk premia. While the futures and the spot markets for currencies and equities are integrated, we present new evidence that the futures and commodity spot markets are segmented. Such results are of primary importance to investors who use asset pricing models to adjust the risk-return trade-off of their portfolio and evaluate portfolio performance.     

商品期货投资收益问题研究

按照持有期货合约的部位,将商品期货交易者细分为：标的商品生产商、加工商和投机者。在满足终期效用最大化的条件下,通过联立商品期货、现货和证券市场,推导出一个商品期货投资收益模型,证明了商品期货投资收益由期货市场的系统性风险溢价和非系统性风险溢价两部分组成,并解释了“持有期成本套利”、“现货一期货溢价”和“资本资产定价”三种理论适用于确定商品期货投资收益的前提条件。根据国内商品期货市场与证券市场之间存在负相关性的实证结论,说明发展商品基金、减少证券一商品期货市场跨市场投资的交易成本等措施有利于我国资本市场的发展和完善。     

Does the stock market drive herd behavior in commodity futures markets?

This paper contributes to the debate on commodity financialization by extending tests of herd behavior to commodity futures markets. Utilizing a regime-switching model, we test the presence of herd behavior in a number of commodity sectors including energy, metals, grains and livestock during the low and high market volatility states. We find significant evidence of herd behavior in grains only during the high volatility state. We also find that large price movements in the energy and metal sectors significantly contribute to herd behavior in the market for grains. Finally, we find no significant effect of the stock market on herd behavior in the commodity futures market. Our findings in general do not support the much debated commodity financialization hypothesis.     

Factor pricing in commodity futures and the role of liquidity

This paper empirically investigates the pricing factors and their associated risk premiums of commodity futures. Existing pricing factors in equity and bond markets, including market premium and term structure, are tested in commodity futures markets. Hedging pressure in commodity futures markets and momentum effects is also considered. This study combines these factors to discuss their importance in explaining commodity future returns, while the literature has studied these factors separately. One of the important pricing factors in equity and bond markets is liquidity, but its role as a pricing factor in commodity futures markets has not yet been studied. To our knowledge, this research is the first to study liquidity as a pricing factor in commodity futures. The risk premiums of two momentum factors and speculators’ hedging pressure range from 2% to 3% per month and are greater than the risk premiums of roll yield (0.8%) and liquidity (0.5%). The result of a significant liquidity premium suggests that liquidity is priced in commodity futures.     

Financialization and de-financialization of commodity futures: A quantile regression approach

This study employs a quantile regression approach to examine the financialization of commodity futures. We confirm a strong degree of dependence in energy commodities from 2004 to 2013, with moderate effects in metals and lesser magnitudes in agriculture. Our findings show a strengthening in the financialization of energy commodities during the 2008–2009 global financial crisis, while there were weaker effects in agriculture and a decoupling or de-financialization in metal markets. The findings reveal the de-financialization of metals and agricultural markets from 2014 to 2017, after the 2013 closure of commodity trading units on Wall Street. Overall, our findings cast doubt on the diversification benefits of energy-dominated commodity indices after 2013. We argue the impact of financialization on commodity futures markets is more permanent than previously thought.     

中国大宗商品期货市场定价机制研究

大宗商品期货市场是我国资本市场的重要组成部分,其定价有效性关系到投资者套期保值和价格发现等功能的实现。本文对国际前沿研究中常用的定价因子进行全面系统梳理,并对这些因子对我国商品期货合约收益率的解释和预测能力进行检验。在此基础上,本文构建了适用于我国大宗商品期货市场的包含市场、基差以及基差动量的三因子定价模型。进一步研究表明,基于大宗商品存储理论和现货存货数据构建的投资组合收益率可以被本文三因子模型有效解释,验证了经典的存储理论在我国的适用性。此外,本文对基差与基差动量两个重要因子的经济学意义进行了阐释。本文研究为进一步厘清大宗商品期货市场定价机制提供了一定参考。     

Investor structure and the informational efficiency of commodity futures prices

This article investigates the impact of the trading positions of hedgers (i.e., producers, merchants, processors, or users of a commodity), speculators (i.e., commodity pool operators, trading advisors, or hedge funds), and swap dealers on the price formation process in the agricultural, metal, and energy futures markets. The hedgers' relative positions exert negative impacts on price efficiency in commodity futures markets. Hedgers are less likely to be information motivated, so their trading delays the price formation process. However, speculators' positions have positive impacts on price efficiency because speculators correct pricing errors. This study also offers evidence that the role of swap dealers, similar to speculators in futures markets, is to provide liquidity and cross-market arbitrage. These findings highlight the role of producers, hedge funds, and swap dealers in price formation processes in commodity futures—information that is beneficial to academics, practitioners, and regulators.     

Speculators,commodities and cross-market linkages

We use a unique, non-public dataset of trader positions in 17 U.S. commodity futures markets to provide novel evidence on those markets' financialization in the past decade. We then show that the correlation between the rates of return on investible commodity and equity indices rises amid greater participation by speculators generally, hedge funds especially, and hedge funds that hold positions in both equity and commodity futures markets in particular. We find no such relationship for commodity swap dealers, including index traders (CITs). The predictive power of hedge fund positions is weaker in periods of generalized financial market stress. Our results support the notion that who trades helps predict the joint distribution of commodity and equity returns. We find qualitatively similar but statistically weaker results using a proxy for hedge fund activity based on publicly available data.     

Impact of speculation and economic uncertainty on commodity markets

We examine the interactions between commodity futures returns and five driving factors (financial speculation, exchange rate, stock market dynamics, implied volatility for the US equity market, and economic policy uncertainty). Nonlinear causality tests are implemented after controlling for cointegration and conditional heteroscedasticity in the data over the period May 1990 – April 2014. Our results show strong evidence of unidirectional linear causality from commodity returns to excess speculation for the majority of the considered commodities, in particular for agriculture commodities. This evidence casts doubt on the claim that speculation is driving food prices. We also find unidirectional linear causality from energy futures markets to exchange rates and strong evidence of nonlinear causal dependence between commodity futures returns, on the one hand, and stock market returns and implied volatility, on the other hand. Overall, the new evidence found in this paper can be utilized for policy and investment decision-making.     

Capturing the risk premium of commodity futures: The role of hedging pressure

We construct long–short factor mimicking portfolios that capture the hedging pressure risk premium of commodity futures. We consider single sorts based on the open interests of hedgers or speculators, as well as double sorts based on both positions. The long–short hedging pressure portfolios are priced cross-sectionally and present Sharpe ratios that systematically exceed those of long-only benchmarks. Further tests show that the hedging pressure risk premiums rise with the volatility of commodity futures markets and that the predictive power of hedging pressure over cross-sectional commodity futures returns is different from the previously documented forecasting power of past returns and the slope of the term structure.     

Does economic policy uncertainty drive nonlinear risk spillover in the commodity futures market?

We propose the rolling tail-event driven network technique (RTENET) to measure the dynamic nonlinear tail risk spillover of 20 US commodity futures. In addition, we investigate the effect of economic policy uncertainty (EPU) on risk spillover based on quantile-on-quantile regression (QQR). We find that the risk spillover effect increases sharply and that the market is tightly connected when EPU is at a high level. Crude oil, silver and corn, the three greatest risk transmitters in the system, need more attention. More importantly, the effect of EPU on the risk spillover of the commodity futures market is asymmetric and heterogeneous. When the risk spillover falls within extremely high quantiles, a significant positive effect of EPU is observed. In addition, grain and soft crops are more sensitive to EPU. Our findings provide a reference for policy-makers and investors to manage commodity futures markets in different uncertainty periods.     

What does futures market interest tell us about the macroeconomy and asset prices?

Economists have traditionally viewed futures prices as fully informative about future economic activity and asset prices. We argue that open interest could be more informative than futures prices in the presence of hedging demand and limited risk absorption capacity in futures markets. We find that movements in open interest are highly pro-cyclical, correlated with both macroeconomic activity and movements in asset prices. Movements in commodity market interest predict commodity returns, bond returns, and movements in the short rate even after controlling for other known predictors. To a lesser degree, movements in open interest predict returns in currency, bond, and stock markets.     

Trend-following trading strategies in commodity futures: A re-examination

This paper examines the performance of trend-following trading strategies in commodity futures markets using a monthly dataset spanning 48 years and 28 markets. We find that all parameterizations of the dual moving average crossover and channel strategies that we implement yield positive mean excess returns net of transactions costs in at least 22 of the 28 markets. When we pool our results across markets, we show that all of the trading rules earn hugely significant positive returns that prevail over most subperiods of the data as well. These results are robust with respect to the set of commodities the trading rules are implemented with, distributional assumptions, data-mining adjustments and transactions costs, and help resolve divergent evidence in the extant literature regarding the performance of momentum and pure trend-following strategies that is otherwise difficult to explain.     

On the diversification benefits of commodities from the perspective of euro investors

This paper investigates the diversification contribution of several commodities to a portfolio of traditional assets from the perspective of a euro investor. The approach applied in our analysis has high informational content as it differentiates between the sources of the diversification benefits in a statistically significant way. The results indicate that the diversification contribution varies greatly amongst the different commodities. Industrial metals, agriculturals and livestock contribute to the reduction of risk, while energy and precious metals contribute to both the reduction of the level of risk and to the improvement of return. The differentiation between bull and bear markets reveals that investors can enhance the portfolio performance by changing exposure into individual commodities. Investors can benefit from the diversification gains through financial instruments as the diversification gains hold both in the sample of physical commodity and commodity futures. Overall, the results confirm that commodities are valuable investments from the perspective of diversification.     

Explain systemic risk of commodity futures market by dynamic network

Since inflation of commodities is becoming more and more severe recently caused by many macro events, such as COVID-19 and Russian-Ukrainian conflict, systemic risk of commodity futures market is getting more attention from academic and industrial areas. Instead of using external factors to explain this risk as previous researches, we explain it by internal topology and structures of commodity futures market. This method helps us understand its key driving factors and their different impact to Chinese and international commodity futures markets.     

A Model of Financialization of Commodities

We analyze how institutional investors entering commodity futures markets, referred to as the financialization of commodities, affect commodity prices. Institutional investors care about their performance relative to a commodity index. We find that all commodity futures prices, volatilities, and correlations go up with financialization, but more so for index futures than for nonindex futures. The equity‐commodity correlations also increase. We demonstrate how financial markets transmit shocks not only to futures prices but also to commodity spot prices and inventories. Spot prices go up with financialization, and shocks to any index commodity spill over to all storable commodity prices.     

Returns to Speculators and the Theory of Normal Backwardation

A nonparametric statistical procedure is employed to examine the returns to speculators in wheat, corn, and soybeans futures markets. We find that the theory of normal backwardation is supported. Moreover, the presence of the risk premiums to speculators tends to be more prominent in recent years than in earlier years. We also find that large wheat speculators as a whole possessed some superior forecasting ability. The evidence is inconsistent with the hypothesis that commodity futures prices are unbiased estimates of the corresponding future spot prices.     

Macroeconomic impacts on commodity prices: China vs. the United States

This study compares the macroeconomic impacts of China and the United States on international commodity markets using a factor-augmented vector auto-regression (FAVAR) model with latent factors extracted from a rich data set that includes various macroeconomic and financial indicators at monthly frequency. The main results suggest that whether or not the Chinese demand cause commodity prices to soar depends. Macroeconomic factors of China do have significant impact on commodity markets, but the impacts of the United States outperform those of China in terms of the size of coefficients and their level of significance, as well as the direction and magnitude of directional return spillovers. Moreover, the effects of these factors on individual commodity futures are not a universal phenomenon. Therefore, there is no systematic evidence of a relationship between strong growth in the emerging economy and the boom in commodity futures prices, either statistically or economically.