Analysis of crisis impact on crude oil prices: a new approach with interval time series modelling
Yongmiao Hong () and
Quantitative Finance, 2016, vol. 16, issue 12, 1917-1928
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.
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