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...

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...

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 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...

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...

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...

The aim of this study is to enhance the understanding of volatility dynamics in commodity returns, such as gold and cocoa, as well as the financial market index S&P500. It provides a comprehensive overview of each model's efficacy in capturing volatility clustering, asymmetry, and long-term...

This study examines market and future-level sentiment in the Chinese agricultural futures market, distinguishing between contagious and idiosyncratic sentiment. Our analysis reveals that agricultural future-level sentiment is significantly affected by market-level sentiment and domestic stock...

Reported news events frequently influence the pricing dynamics of oil-based commodities. We analyze almost 900 oil-related events from 1987 to 2022, categorizing them based on recurring characteristics. We quantify dynamic connectedness among energy commodities and apply a novel...

The oil and gas industry’s early 2000’s fracking and horizontal drilling revolution realigned the industry and larger economies. This study uses New Growth Theory to evaluate innovation across an industry with various integrated but distinct upstream, midstream, and downstream units. Two...

The objective of this study is to examine the return interconnectedness and asymmetric spillover effects in global commodity futures markets, with a focus on the impact of contagion. A competent asymmetric time-varying parameter vector autoregressive (TVP-VAR) model was employed for highly...