Forecasting the Sign of U.S. Oil and Gas Industry Stock Index Excess Returns Employing Macroeconomic Variables

53 Pages Posted: 23 Jun 2017 Last revised: 7 May 2019

See all articles by Jingzhen Liu

Jingzhen Liu

University of Aberdeen - Business School

Alexander G. Kemp

Aberdeen Centre for Research in Energy Economics and Finance, University of Aberdeen

Date Written: July 24, 2017

Abstract

In this study, we investigate whether we can identify a probit model with macroeconomic variables to forecast the monthly excess return signs of the U.S. oil and gas industry index by mining a big macroeconomic variable dataset designed by McCracken and Ng (2015). Three different information criteria and a Forward Sequential Variable Selection Algorithm are combined to select the most ”important” macroeconomic variables for prediction. A static probit model with 14 monthly macroeconomic predictors is found to predict one-month ahead excess returns of the U.S. oil and gas industry. We also show that the predictors in this model are related to the future performance of the S&P 500 index, the WTI crude oil price and the U.S. foreign exchange rate against the major currencies, which are the key risk factors of the oil and gas industry identified by previous studies. Active trading strategies based on the static probit model can generate higher Sharpe ratios than a buy-and-hold strategy. The forecasting ability of the identified model is found to be robust to different industry classification systems. The empirical results have important implications for investors and policy makers.

Keywords: Excess stock return; U.S. Oil and gas industry; Probit model; Market timing; Big data

JEL Classification: C53, C55, C58, G11, G17, E00

Suggested Citation

Liu, Jingzhen and Kemp, Alexander G., Forecasting the Sign of U.S. Oil and Gas Industry Stock Index Excess Returns Employing Macroeconomic Variables (July 24, 2017). Available at SSRN: https://ssrn.com/abstract=2990880 or http://dx.doi.org/10.2139/ssrn.2990880

Jingzhen Liu (Contact Author)

University of Aberdeen - Business School ( email )

Edward Wright Building
Dunbar Street
Aberdeen, Scotland AB24 3QY
United Kingdom

Alexander G. Kemp

Aberdeen Centre for Research in Energy Economics and Finance, University of Aberdeen ( email )

Edward Wright Building
Dunbar Street
Old Aberdeen AB24 3QY, Scotland AB24 3QY
United Kingdom
(0)1224 272168 (Phone)
(0)1224 272181 (Fax)

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