Journal of Commodity Markets最新文献

This paper studies the information inferred from the Carr and Wu’s (2020) formula based on a new option pricing framework in the United States Oil Fund (USO) options. We first document the term structure and dynamics of the risk-neutral variance and covariance rates which lead to a “U”-shaped implied volatility smile with a positive curvature. We then investigate the return predictability of the innovations in the risk-neutral variance and covariance rates ($DRNV$ and $DRNC$) and their term structures ($TRNV$ and $TRNC$) and find that $DRNC$ is a significant and robust predictor to forecast daily, weekly and monthly USO excess returns in both statistical and economic terms based on in-sample and out-of-sample tests.

Trading time seasonality reflects the seasonal behavior of futures prices with the same time of maturity. Hence, it differs from classical seasonality, which reflects seasonal behavior induced by the spot price observed for varying maturities. This type of seasonality is linked to the pricing kernel which in turn accounts for seasonal changes in preferences of agents and tied to risk aversion and thus the demand for hedging. In the present study we empirically examine trading time seasonality in yearly Nordic and German electricity futures contracts. Visual inspection of both average monthly futures prices and the futures backward curves provides strong indications of futures prices systematically varying over the trading year. On average both Nordic and German futures prices are lowest in first quarter and highest in third quarter trading months. This is confirmed by statistical tests of stochastic dominance. Exploiting this insight in a simple trading strategy induces positive and significant alphas in the sense of the capital asset pricing model. We relate the findings to potential seasonal risk preferences and hedging pressure in the electricity futures market.

In the last twenty years a large number of ethanol firms have established operations in the US. Ethanol, produced from corn, is blended with pure gasoline to produce fuel. Producers hold an option to turn off unprofitable plants. Blenders choose to substitute ethanol for gasoline at or beyond the mandate set by the government. We propose an equilibrium model for blenders and producers that accounts for government measures and for real optionality embedded in the industry. The model, driven by corn and gasoline prices, leads to analytical expressions for the price and output of ethanol, and to policy implications on the impacts of the mandate and blend credit. The model also leads to closed form valuation for an ethanol producer. Using data between 2000 and 2017 we confirm that, as in the model, ethanol was largely priced as the maximum of rescaled gasoline and corn prices. Historical output levels between the mandate and installed capacity were explained by our theory. Finally, the share price dynamics for the largest public ethanol producer in the US was consistent in some aspects with the value of a real option.

We analyze Chicago based daily wheat price volatility over more than 140 years using a novel data set of daily high and low futures prices starting in 1877. We identify five long-run regimes and find that volatility shifts between regimes are statistically more pronounced than fluctuations within regimes, even when conditioning on economic states. Historical volatility estimates derived from average commodity price data, a common practice in empirical studies, exhibit a regime-dependent upward bias between 0% and 22%. The magnitude of the bias and the importance of regimes potentially explain contradictory findings on volatility patterns in earlier studies.

This paper assesses the accuracy of several machine learning models’ predictions of the gold risk premium when using an extensive set of 186 predictors. We perform an out-of-sample evaluation and consider both statistical and portfolio metrics. Our results show that machine learning methods and forecast combinations have a limited ability to outperform the historical mean when predicting the gold risk premium. Slightly better results are obtained when predictors are used individually. More specifically, we find that several technical indicators (moving average and momentum series) have forecasting power during periods of expansion, while several business cycle variables and geopolitical risk variables help predict the gold risk premium during recessions. An economic evaluation accounting for transaction costs shows that investors using machine learning methods to estimate expected returns on gold should anticipate limited portfolio gains.

The pronounced inflow of financial capital from index investors over the last 15 years and the accompanying substantial fluctuations in commodity futures markets have aroused public and academic interest. A common accusation made in this context is that commodity index traders (CITs) negatively influence the quality of commodity futures markets and keep them far from fundamentally justified price levels. In this paper, we focus on quantifying market efficiency, and investigate empirically the suggested effect of CITs over the period from 1999 to 2019 for 34 commodity futures markets. In contrast to recent studies, we find empirical evidence that the financialization positively affected the market efficiency of indexed commodity futures markets. Consistently, we observe that the degree of commodity index trader activity is associated with higher degrees of informational efficiency.

This study assesses the tracking performance of several futures-backed commodity exchange-traded funds (ETFs), single commodity exchange-traded notes (ETNs), and commodity sector ETNs relevant to agricultural market participants. We decompose total tracking errors into managerial and arbitrage components. Our findings reveal that the arbitrage process is the primary driver of observed tracking errors. ETNs tend to exhibit much larger tracking errors than ETFs. The tracking performance was not substantially different across agricultural and energy ETFs nor across single commodity and commodity sector ETNs. Using a GARCH model, the study reveals greater persistence of tracking errors for ETNs than ETFs. Roll dates do not significantly affect the volatility of tracking errors. On the other hand, trading volume, lagged ETF price volatility, and broad market volatility may result in poorer ETF tracking performance.

We investigate the determinants of different traders’ trading positions in the gold futures market. With a threshold value determined endogenously by our model, we find that when the gold futures price falls below the threshold, money managers adopt positive feedback trading strategies while swap dealers adopt negative feedback trading strategies. When the futures price rises above the threshold, money managers turn to negative feedback trading and swap dealers reduce the intensity of their negative feedback. In addition, money managers and swap dealers play the transmitter role in trading spillovers to other traders, and their trading transmitter role weakens during periods with high gold prices.

High frequency crude oil option data is used to extract the higher order risk-neutral moments from the crude oil market. These risk-neutral moments include the variance, third central moment and the recently developed tail risk variation measures. We find it is beneficial to disaggregate these risk-neutral moments into their semi-moments, and to work with their log differences instead of the level. The log differences of the second and third semi-moments, and to a lesser extent, the log differences of the tail risk measures, are found to explain returns in the crude oil and S&P 500 futures at high frequency. We also provide evidence that the efficient market hypothesis holds at high frequency in these markets.

This study provides a literature review of academic research related to liquefied natural gas (LNG) hubs development and market integration. Studies show that Asian markets lack a transparent pricing benchmark which exists in North American and European markets. As a result, the formation of functional LNG market hubs in the Asia Pacific region will take time. Early research evidence suggests a strongly cointegrated relationship between LNG and crude oil. Concurring with more recent findings, we confirm that LNG's statistical relationship to both WTI and Brent ceases after the break dates of August 2008 and October 2015, respectively. Multiple initiatives are underway to facilitate development and price discovery for global LNG markets. However, the conclusions found within prior literature are dependent upon the sophistication of the estimation model and sample ranges employed.