A Markov regime‐switching model for crude‐oil markets: Comparison of composite likelihood and full likelihood |
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Authors: | Wei Zou Jiahua Chen |
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Affiliation: | 1. School of Statistics, Central University of Finance and Economics, Beijing 100081, P.R. China;2. Department of Statistics, University of British Columbia, Vancouver, BC, Canada V6T 1Z2 |
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Abstract: | We use the two‐state Markov regime‐switching model to explain the behaviour of the WTI crude‐oil spot prices from January 1986 to February 2012. We investigated the use of methods based on the composite likelihood and the full likelihood. We found that the composite‐likelihood approach can better capture the general structural changes in world oil prices. The two‐state Markov regime‐switching model based on the composite‐likelihood approach closely depicts the cycles of the two postulated states: fall and rise. These two states persist for on average 8 and 15 months, which matches the observed cycles during the period. According to the fitted model, drops in oil prices are more volatile than rises. We believe that this information can be useful for financial officers working in related areas. The model based on the full‐likelihood approach was less satisfactory. We attribute its failure to the fact that the two‐state Markov regime‐switching model is too rigid and overly simplistic. In comparison, the composite likelihood requires only that the model correctly specifies the joint distribution of two adjacent price changes. Thus, model violations in other areas do not invalidate the results. The Canadian Journal of Statistics 41: 353–367; 2013 © 2013 Statistical Society of Canada |
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Keywords: | Composite likelihood finite mixture model full likelihood Markov regime‐switching model MSC 2010: Primary 62M05 secondary 62P05 |
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