Aiming to study pricing of long-dated commodity derivatives, this paper presents a class of models within the Heath, Jarrow, and Morton (1992) framework for commodity futures prices that incorporates stochastic volatility and stochastic interest rate and allows a correlation structure between...

Does modelling stochastic interest rates, beyond stochastic volatility, improve pricing performanceon long-dated commodity derivatives? To answer this question, we consider futuresprice models for commodity derivatives that allow for stochastic volatility and stochastic interestrates and 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...