Analysis of crisis impact on crude oil prices: a new approach with interval time series modelling

Abstract

This paper proposes two types of dummy variables for an interval regression model to assess the impact of economic shocks/crises on an interval time series (ITS), e.g. daily intervals of energy prices. We present different economic interpretations of the two types of dummy variables for an interval regression model. Particularly, we discuss how they measure the direction and magnitudes of the change of an ITS caused by an economic crisis, and develop the corresponding hypothesis tests. A main advantage of the proposed ITS modelling approach over traditional point-based methods is that it can assess the change in both the trend and volatility of an asset price process simultaneously. This is due to the informational gain of an ITS sample over a point-valued sample, e.g. closing prices, since an interval observation contains both the trend and variation information of a price process in a given period. Using the proposed interval framework, we focus on the impact of the subprime mortgage crisis in the commodity market as a case study based on the ITS of monthly crude oil future price data. Empirical results suggest a strong evidence that the subprime crisis has lowered the level/trend and increased the volatility of crude oil prices. We also show that the trend of crude oil future prices moves towards an equilibrium state driven by the variation of the price process in last period, and the speculation index, as a proxy of crude oil market liquidity, is significant in explaining the dynamics of crude oil prices. Both findings provide quantitative evidence for theoretical results in the previous literature.

Keywords:

• Interval dummy variable
• Interval time series
• Crisis
• Crude oil prices
• Speculation index
• Range volatility

JEL Classifications:

• C01
• C22
• C51
• G01

Acknowledgements

This work was supported by the MOE (Ministry of Education in China) Youth Project of Humanities and Social Sciences Fund [14YJC630163], National Natural Science Foundation of China [grant number 71501115] [grant number 71201161]; National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences. The authors also would like to thank two anonymous reviewers for their careful reading and invaluable comments. All remaining errors are our own.

Notes

No potential conflict of interest was reported by the authors.

1 The ending is set to be December 2009 which can be seen as the start of the European debt crisis when Fitch downgraded Greece’s credit rating from to .

2 The reasons for the interval-valued error correction term are as follows. Firstly, several studies (Cheung et al. 2009, He et al. 2010) have pointed out the error correction term between and has a significantly negative and positive effect on the high and low prices, respectively, and the numerical magnitude of the two effects is almost equal. Secondly, we ensure that the range of the interval is , which is closely with the monthly range information of the crude oil prices.

3 For traders, in the futures market who hold positions in futures at or above specific reporting levels, CFTC classifies their futures positions as either ‘commercial’ or ‘noncommercial’. Commercial positions in a commodity are held for hedging purposes, while noncommercial positions mainly represent speculative activity in pursuit of financial profits.