Forecasting Natural Gas Prices Using Highly Flexible Time-Varying Parameter Models

24 Pages Posted: 14 May 2020

See all articles by Shen Gao

Shen Gao

Center for Economics, Finance and Management Studies, Hunan University, China

Chenghan Hou

Hunan University - Center for Economics, Finance and Management Studies

Bao H. Nguyen

Tasmanian School of Business and Economics, University of Tasmania

Date Written: March 26, 2020

Abstract

The growing disintegration between the natural gas and oil prices, together with shale revolution and market financialization, lead to continued fundamental changes in the natural gas markets. To capture these structural changes, this paper considers a wide set of highly flexible time-varying parameter models to evaluate the out-of-sample forecasting performance of the natural gas spot prices across the US, European and Japanese markets. The results show that for both Japan and EU markets, the best forecasting performance is found when the model allows for drastic changes in the conditional mean and gradual changes in the conditional volatility. For the US market, however, no model performs systematically better than the simple auto-regressive model. Full sample estimation results further confirm that allowing t-distributed error is important in modelling the natural gas prices, especially for EU markets.

Keywords: Natural Gas Price, Structural Breaks, Forecasting, Time-Varying Parameter, Markov Switching, Stochastic Volatility

JEL Classification: C32, E32, Q43

Suggested Citation

Gao, Shen and Hou, Chenghan and Nguyen, Bao H., Forecasting Natural Gas Prices Using Highly Flexible Time-Varying Parameter Models (March 26, 2020). CAMA Working Paper No. 30/2020, Available at SSRN: https://ssrn.com/abstract=3562074 or http://dx.doi.org/10.2139/ssrn.3562074

Shen Gao

Center for Economics, Finance and Management Studies, Hunan University, China ( email )

2 Lushan South Rd
Changsha, CA Hunan 410082
China

Chenghan Hou

Hunan University - Center for Economics, Finance and Management Studies ( email )

2 Lushan South Rd
Changsha, Hunan 410082
China

Bao H. Nguyen (Contact Author)

Tasmanian School of Business and Economics, University of Tasmania ( email )

French Street
Sandy Bay
Tasmania, 7250
Australia

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
38
Abstract Views
241
PlumX Metrics