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.
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A Appendix: Figures
A Appendix: Figures
Term Structure of Natural Gas Futures Prices. Prices time-series of the natural gas futures contracts with expiration date from 1 (Mc1) to 12 (Mc12) months. The data spans 2732 trading days from August 19, 2010 to April 27, 2021.
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Castello, O., Resta, M. (2022). Modeling and Forecasting Natural Gas Futures Prices Dynamics: An Integrated Approach. In: Corazza, M., Perna, C., Pizzi, C., Sibillo, M. (eds) Mathematical and Statistical Methods for Actuarial Sciences and Finance. MAF 2022. Springer, Cham. https://doi.org/10.1007/978-3-030-99638-3_24
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DOI: https://doi.org/10.1007/978-3-030-99638-3_24
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