Narrow Results

This paper adopts the visibility graph (VG) methodology to analyze the dynamic behavior of West Texas Intermediate (WTI), Brent and Shanghai (SC) crude oil futures during the COVID-19 pandemic and Russia–Ukraine conflict. Utilizing daily and high-frequency data, our study reveals a clear power-law decay in VG degree distributions and highlights pronounced clustering tendencies within crude oil futures VGs. We also uncover an inverse correlation between clustering coefficients and node degrees, further identifying that all VGs adhere not only to the small-world property but also exhibit intricate assortative mixing. Through the time-varying characteristics of VGs, we observe that WTI and Brent demonstrate aligned behaviors, while the SC market, with its unique trading mechanisms, deviates. Notably, the five-minute assortativity coefficient provides deep insights into the markets reactions to these global challenges, underscoring the distinct sensitivity of each market.

The fluctuation characteristics of the correlations between China and the US agricultural futures markets have attracted extensive attention from academic circles and government departments. As the main factor that affects the agricultural futures price, the impact of international crude oil futures price on the correlations of the Sino-US agricultural futures markets is also worth discussing. Therefore, this paper adopts the multifractal detrended cross-correlation analysis (MF-X-DFA) and multifractal detrended partial cross-correlation analysis (MF-DPXA) to explore the fluctuation characteristics of cross-correlations for China and the US agricultural futures markets before and after removing the West Texas Intermediate (WTI) crude oil futures price as well as the impact on the cross-correlations. The results show that the fluctuation characteristics of the cross-correlations and partial cross-correlations between the corresponding varieties of China and the US agricultural futures markets as well as among the varieties within the markets are multifractal. The cross-correlation behaviors and the cross-market risks are all affected to varying degrees by the West Texas Intermediate (WTI) crude oil futures. The West Texas Intermediate (WTI) crude oil futures weaken the cross-market risk of the Sino-US soybean futures, while strengthening the cross-market risk of the Sino-US corn and wheat futures. In addition, the impact of the West Texas Intermediate (WTI) crude oil futures on the cross-market risks among China agricultural futures is greater than those among the US corresponding agricultural futures.

This paper investigates the asymmetric cointegration between possible domestic determinants of crude oil futures prices during the COVID-19 pandemic period. We perform comparative analysis of West Texas Intermediate (WTI) and newly-launched Shanghai crude oil futures (SC) via the Quantile Autoregressive Distributed Lag (QARDL) model. The empirical results show the long- and short-run impacts of stock markets, interest rate, coronavirus panic and corn futures on WTI futures prices, while economic policy uncertainty is a driver for the long-run WTI price dynamics. However, the influence of stock market, interest rate and COVID-19 panic on SC is significant in the short term. There also exists short- and long-run positive responses of China’s crude oil futures to corn prices. Overall, the impacts of domestic price drivers are heterogeneous across market circumstances (bullish, bearish and normal) and countries. These empirical evidences provide practical implications for investors and policymakers.

Due to increasing speculation, crude oil futures are now becoming one of the highest traded commodities. This paper studies the relationship between trading volume and serial correlation in crude oil futures returns using high frequency data. We find that volume can positively predict the serial correlation in the short run (within an hour) but negatively predict the serial correlation in the midterm. The trading volume is not able to consistently predict serial correlation in the long run (more than a day). The results from our empirical studies are robust to a variety of controls and our study gives a new insight in the relation between volume and serial correlation of crude oil futures returns.

The fall of crude oil futures into extreme negative prices has raised concerns globally. On the one hand, although the negative price mechanism facilitates market price discovery to some extent, in the delivery month it can trigger serious consequences such as abnormal market price fluctuations due to insufficient liquidity, which creates extreme market injustice and raises suspicion of manipulation. On the other hand, the reckless change of programs, which allow negative prices, lacks necessary legitimacy at the procedural level. Market participants who have been treated unfairly should actively defend their rights, and United States regulators and the Chicago Mercantile Exchange Group Inc. (CME) should explain to the market with thorough investigations and credible conclusions. The negative oil price incident is a profound warning and lesson for financial institutions and regulators in China.

This chapter presents an overview of energy futures markets. A brief description of the history and emergence of energy futures markets is provided along with the current status of energy futures markets on global exchanges. The two leading energy exchanges in the world are the NYMEX (owned by CME Group) and ICE Futures Europe (a subsidiary of ICE). This chapter also discusses characteristics of successful and unsuccessful energy futures contracts, the types of energy futures and options, along with hedging examples, and price and return behavior in energy futures markets (i.e., backwardation, contango, mean reversion, and seasonality).