Real-Time Demand in U.S. Natural Gas Price Forecasting: The Role of Temperature Data

30 Pages Posted: 7 Jul 2021 Last revised: 21 Sep 2021

See all articles by Zakaria Moussa

Zakaria Moussa

University of Nantes - LEMNA

Benoît Sévi

Université de Nantes

Arthur Thomas

CREST - ENSAE

Date Written: July 6, 2021

Abstract

This paper provides evidence of the pivotal role temperature data can play in forecasting natural gas prices at the Henry Hub in real time. Considering a newly constructed temperature index as an additional exogenous variable in a Bayesian vector autoregressive (BVAR) framework significantly increases forecast accuracy at horizons of up to 12 months. Our novel approach to energy price forecasting simultaneously considers both supply and demand and incorporates temperature data as a proxy of real-time demand for natural gas.

Keywords: energy prices, natural gas, Bayesian VAR, price forecasting, real-time data, temperature

JEL Classification: C11, C32, C53, Q41, Q47

Suggested Citation

Moussa, Zakaria and Sévi, Benoît and Thomas, Arthur, Real-Time Demand in U.S. Natural Gas Price Forecasting: The Role of Temperature Data (July 6, 2021). USAEE Working Paper No. 21-507, Available at SSRN: https://ssrn.com/abstract=3880809 or http://dx.doi.org/10.2139/ssrn.3880809

Zakaria Moussa (Contact Author)

University of Nantes - LEMNA ( email )

Nantes, 44000
France

Benoît Sévi

Université de Nantes ( email )

Nantes, Pays de la Loire 44300
France

Arthur Thomas

CREST - ENSAE ( email )

France

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