This study, set against the backdrop of escalating trade tensions between China and the United States, examines the impact of soybean tariff adjustments on the abnormal asymmetric behavior in the futures market. By employing specialized analytical methods that capture market volatility asymmetry...

This paper presents the first formal comparison of Value at risk (VaR) forecasting performance across various high-frequency volatility models and conventional benchmarks using daily data in the crude oil futures market. Our analysis reveals the following key findings:(1) High-frequency data...

Soybeans play a critical role in China's food system and hold significant importance in ensuring national food security. This study explores the correlation between soybean futures prices and international soybean import prices. It employs a time-series model to analyse the volatility of the...

Commodity prices are expected to decline by about 7 percent overall this year, reflecting subdued global economic activity, elevated trade tensions and policy uncertainty, ample global supply of oil, and weather-related supply shocks. In 2026, commodity prices are forecast to fall by a further 7...

This study uses Baidu News data and introduces a novel proxy for the rate of information flow to examine its relationship with return volatility in Chinese commodity futures and to test two competing hypotheses. We examine the contemporaneous relationships using correlation coefficient analysis,...

Amid the growing debate over how cryptocurrencies are reshaping global finance, this study explores the nexus between Bitcoin, Brent Crude Oil, Gold and the U.S. Dollar Index. We used a time-varying vector autoregressive (tvVAR) model to examine the connection among these four assets during the...

In this study, we investigate the return propagation mechanism, hedging effectiveness, and portfolio performance across several common agricultural commodities, crude oil, and S&P 500 index, ranging from July 2000 to June 2024 by using a time-varying parameter vector autoregression (TVP-VAR)...

We develop an indirect inference approach relying on a linear supply and demand model serving as an auxiliary model to provide the first full empirical test of the rational expectations commodity storage model. We build a rich storage model that incorporates a supply response and four structural...

A robust model for natural gas prices should simultaneously capture the observed prices of both futures and options. While incorporating a seasonal factor in the convenience yield of the spot price effectively replicates forward curves, it proves insufficient for accurately modelling the options...

This study leverages the Log-Periodic Power Law Singularity (LPPLS) confidence indicator to effectively identify bubbles in agricultural commodity markets. We analyze five major grain price indices reported by the International Grains Council (IGC) from January 2000 to April 2023, successfully...

Understanding the determinants of central bank digital currencies (CBDCs) is crucial for ensuring financial stability, fostering innovation, and framing effective policies associated with the digitalization of currency. Therefore, we study how financial markets and safe haven assets can affect...

Commodity prices are set to fall sharply this year, by about 12 percent overall, as weakening global economic growth weighs on demand. In 2026, commodity prices are projected to reach a six-year low. Oil prices are expected to exert substantial downward pressure on the aggregate commodity index...

We investigate linkages between three different markets: renewable energy (represented by a range of renewable energy ETFs); traditional energy (represented by crude oil ETF); and common stocks (represented by the S&P 500 Index ETF). We use daily data from 2008 to 2021. The econometric framework...

This paper presents a novel 5-factor model for agricultural commodity risk premiums, an approach not explored in previous research. The model is applied to the specific cases of corn, soybeans, and wheat. Calibration is achieved using a Kalman filter and maximum likelihood, with data from...

This paper examines the dynamic relationships between speculative activities, commodity returns, and macroeconomic conditions across five sectors compassing 29 commodities. Using weekly data spanning from January 2000 to July 2023, we construct comprehensive measures of commodity market...

Research has often attributed commodity futures contracts (CFC) adoption in agriculture to structural factors, such as farm size and education, linking low uptake to economies of scale and learning costs. We challenge this perspective by investigating psychological dimensions of farmers'...