Autori: Canepa, Alessandra, Zanetti Chini, Emilio, Huthaifa, Alqaralleh
Titolo: Modelling and Forecasting Energy Market Cycles: A Generalized Smooth Transition Approach.
Periodico: Università degli studi di Torino. Dip. Di Economia e Statistica Cognetti de Martiis. Working paper series
Anno: 2023 - Volume: 9 - Fascicolo: 18 - Pagina iniziale: 1 - Pagina finale: 35

In this paper we investigate the dynamic features of energy commodity prices. Using a generalized smooth transition model (GSTAR) we show that dynamic symmetry in price cycles in the energy markets is strongly rejected. Further, our results show that the proposed model performs well when compared to other linear and nonlinear speciÖcations in a out-of-sample forecasting exercise.




Testo completo: https://www.est.unito.it/do/home.pl/Download?doc=/allegati/wp2023dip/wp_18_2023.pdf

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