This paper examines the connectedness between Bitcoin and commodity volatilities, including oil, wheat, and corn, during the period Oct. 2013-Jun. 2018, using time- and frequency-domain frameworks. The time-domain framework's results show that the connectedness is 23.49%, indicating a low level...

The aim of this study is to test the ability of the yield curve on US government bonds to forecast the future evolution in the prices of commodities often used in as raw materials. We consider the monthly prices of nine commodities for more than 30 years. Our findings, confirmed by several...

We explore optimal hedge ratios and hedging effectiveness for the German electricity market. Given the increasing attention that wavelets received in the financial market, we concentrate on the investigation of the relationship, covariance/coherence evolution and hedge ratio analysis, on a...

This paper proposes a novel approach, based on convolutional neural network (CNN) models, that forecasts the short-term crude oil futures prices with good performance. In our study, we confirm that artificial intelligence (AI)-based deep-learning approaches can provide more accurate forecasts of...

This study examines the price transmission between cotton prices in U.S., Indian, and Chinese futures markets. We focus on studying the long-run price movements using cointegration and alternate causality tests. The empirical results indicate the following: (a) the U.S. cotton futures market...

Since the collapse of the Metallgesellschaft AG due to hedging losses in 1993, energy practitioners have been concerned with the ability to hedge long-dated linear and non-linear oil liabilities with short-dated futures and options. This paper identifies a model-free non-parametric approach to...