Modelling the industrial production of electric and gas utilities through a stochastic three-factor model

29 Pages Posted: 28 Mar 2022

See all articles by Claudia Ceci

Claudia Ceci

Sapienza University of Rome

Michele Bufalo

Sapienza University of Rome

Giuseppe Orlando

Università degli Studi di Bari “Aldo Moro” (UNIBA) - Department of Economics and Mathematical Methods

Date Written: February 28, 2022

Abstract

This work aims to demonstrate how a trifactorial stochastic model, which we call CIR3, can be turned into a forecasting tool to predict changes in the industrial production of electric and gas utilities. The model accounts for several stylized facts such as the mean reversion of both the process and its volatility to a short-run mean, non-normality, cluster volatility and fat tails. In addition to that, we provide two theoretical results which are of particular importance in modelling and simulations. The first is the proof of existence and uniqueness of the solution to the SDEs system that describes the model. The second theoretical result is to convert, by the means of Lamperti transformations, the correlated system into an uncorrelated one. The forecasting performance is tested versus an ARIMA-GARCH and a nonlinear regression model (NRM).

Keywords: Energy; Forecasting; Three-factor stochastic model; Stochastic differential equations

JEL Classification: C1, C53, C6, Q4

Suggested Citation

Ceci, Claudia and Bufalo, Michele and Orlando, Giuseppe, Modelling the industrial production of electric and gas utilities through a stochastic three-factor model (February 28, 2022). Available at SSRN: https://ssrn.com/abstract=4048298 or http://dx.doi.org/10.2139/ssrn.4048298

Claudia Ceci

Sapienza University of Rome ( email )

Michele Bufalo

Sapienza University of Rome ( email )

Giuseppe Orlando (Contact Author)

Università degli Studi di Bari “Aldo Moro” (UNIBA) - Department of Economics and Mathematical Methods ( email )

Via C. Rosalba 53
VI Floor, Room 12
Bari, 70124
Italy
+39 080 5049218 (Phone)

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