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...

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...

This paper aims to investigate the sensitivity of the gas market: Russian Natural Gas and Liquefied Gas, to other commodity categories. It sheds light on the Russian-Ukrainian crisis by using an Autoregressive Distributed Lag model on daily prices of Russian Natural Gas, Liquefied Natural Gas,...

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 analyzes three forecasting methods for commodity spot prices and applies them to copper prices. The first method uses futures prices from either LME or COMEX. The second method uses analysts' consensus expectations, reported by Bloomberg. The third method jointly uses futures and...

This paper investigates tail-risk transmission and asymmetric dependence in commodity markets using an asymmetric fuzzy vine copula framework applied to gold, crude oil, natural gas, and silver from 1 January 2015 to 1 January 2025, extracted from Yahoo Finance. Bootstrap-based trapezoidal fuzzy...

We Examine the Comovement between China's Commodity Futures and World Crude Oil Prices Based on Their Daily Return Series. Using a Dynamic Time-Varying Approach, We Combine the Generalized Autoregressive Score (Gas) Model with the Copula Approach, Allowing for Asymmetry and Tail Dependence. Our...

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...

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...