Modeling and Forecasting Natural Gas Futures Prices Dynamics: An Integrated Approach

Oleksandr Castello () and Marina Resta ()
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Oleksandr Castello: University of Genova, School of Social Sciences, Department of Economics and Business Studies
Marina Resta: University of Genova, School of Social Sciences, Department of Economics and Business Studies

A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2022, pp 146-150 from Springer

Abstract: Abstract We explore and test the capabilities of B-Splines and Dynamic De Rezende-Ferreira five–factor model to replicate the main dynamics and stylized facts of futures curves in the Natural Gas Futures market. Furthermore, we discuss the joint use of these models with a Nonlinear Autoregressive Neural Network for parameters fine–tuning to forecast futures curves. The simulation study highlighted the effectiveness of the proposed framework; empirical results show that the joint use of B–Splines and neural networks provides highest overall performances on the Natural Gas futures market.

Keywords: Natural Gas; Futures term structure; De Rezende–Ferreira model; B–Spline; Artificial Neural Networks (ANN); Nonlinear Autoregressive Neural Networks (NAR–NN) (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-99638-3_24

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DOI: 10.1007/978-3-030-99638-3_24

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