Unbalanced Fractional Cointegration and the No-Arbitrage Condition on Commodity Markets
Technical abstract: A necessary condition for two time series to be nontrivially cointegrated is the equality of their respective integration orders. Nonetheless, in some cases, the apparent unbalance of integration orders of the observables can be misleading and the cointegration theory applies all the same. This situation refers to unbalanced cointegration in the sense that balanced long run relationship can be recovered by an appropriate filtering of one of the time series. In this paper, we suggest a local Whittle estimator of bivariate unbalanced fractional cointegration systems. Focusing on a degenerating band around the origin, it estimates jointly the unbalance parameter, the long run coefficient and the integration orders of the regressor and the cointegrating errors. Its consistency is demonstrated for the stationary regions of the parameter space and a finite sample analysis is conducted by means of Monte Carlo experiments. An application to the no-arbitrage condition between crude oil spot and futures prices is proposed to illustrate the empirical relevance of the developed estimator. Non-technical abstract: The no-arbitrage condition between spot and future prices implies an analogous condition on their underlying volatilities. Interestingly, the long memory behavior of the volatility series also involves a long-run relationship that allows to test for the no-arbitrage condition by means of cointegration techniques. Unfortunately, the persistent nature of the volatility can vary with the future maturity, thereby leading to unbalanced integration orders between spot and future volatility series. Nonetheless, if a balanced long-run relationship can be recovered by an appropriate filtering of one of the time series, the cointegration theory applies all the same and unbalanced cointegration operates between the raw series. In this paper, we introduce a new estimator of unbalanced fractional cointegration systems that allows to test for the no-arbitrage condition between the crude oil spot and futures volatilities.
|Date of creation:||Sep 2014|
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- Guglielmo Maria Caporale & Davide Ciferri & Alessandro Girardi, 2014.
"Time-Varying Spot and Futures Oil Price Dynamics,"
Scottish Journal of Political Economy,
Scottish Economic Society, vol. 61(1), pages 78-97, February.
- Guglielmo Maria Caporale & Davide Ciferri & Allessandro Girardi, 2010. "Time-Varying Spot and Futures Oil Price Dynamics," Discussion Papers of DIW Berlin 988, DIW Berlin, German Institute for Economic Research.
- Guglielmo Maria Caporale & Davide Ciferri & Alessandro Girardi, 2010. "Time-Varying Spot and Futures Oil Price Dynamics," CESifo Working Paper Series 3015, CESifo Group Munich.
- Guglielmo Caporale & Davide Ciferri & Alessandro Girardi, 2010. "Time-varying spot and futures oil price dynamics," Quaderni del Dipartimento di Economia, Finanza e Statistica 75/2010, Università di Perugia, Dipartimento Economia.
- Abadir, Karim M. & Caggiano, Giovanni & Talmain, Gabriel, 2013. "Nelson–Plosser revisited: The ACF approach," Journal of Econometrics, Elsevier, vol. 175(1), pages 22-34.
- Karim Abadir & Giovanni Caggiano & Gabriel Talmain, 2005. "Nelson-Plosser Revisited: the ACF Approach," Working Papers 2005_7, Business School - Economics, University of Glasgow.
- Karim M. Abadir & Gabriel Talmain & Giovanni Caggiano, 2008. "Nelson-Plosser revisited: the ACF approach," Working Paper Series 18_08, The Rimini Centre for Economic Analysis.
- Chakraborty, Avik & Evans, George W., 2008. "Can perpetual learning explain the forward-premium puzzle?," Journal of Monetary Economics, Elsevier, vol. 55(3), pages 477-490, April.
- George W. Evans & Avik Chakraborty, 2006. "Can Perpetual Learning Explain the Forward Premium Puzzle?," University of Oregon Economics Department Working Papers 2006-8, University of Oregon Economics Department, revised 20 Aug 2006.
- Baillie, Richard T. & Bollerslev, Tim, 2000. "The forward premium anomaly is not as bad as you think," Journal of International Money and Finance, Elsevier, vol. 19(4), pages 471-488, August.
- Chevillon, Guillaume & Mavroeidis, Sophocles, 2011. "Learning generates Long Memory," ESSEC Working Papers WP1113, ESSEC Research Center, ESSEC Business School.
- Guillaume Chevillon & Sophocles Mavroeidis, 2013. "Learning generates Long Memory," Post-Print hal-00661012, HAL.
- Karim Abadir & Gabriel Talmain, 2002. "Aggregation, Persistence and Volatility in a Macro Model," Review of Economic Studies, Oxford University Press, vol. 69(4), pages 749-779.
- Karim Abadir & Gabriel Talmain, "undated". "Aggregation, Persistence and Volatility in a Macromodel," Discussion Papers 01/03, Department of Economics, University of York.
- Karim Abadir & Gabriel Talmain, 2001. "Aggregation, Persistence and Volatility in a Macromodel," Working Papers w200106, Banco de Portugal, Economics and Research Department.
- Cheung, Yin-Wong & Lai, Kon S, 1993. "A Fractional Cointegration Analysis of Purchasing Power Parity," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 103-112, January.
- Brenner, Robin J. & Kroner, Kenneth F., 1995. "Arbitrage, Cointegration, and Testing the Unbiasedness Hypothesis in Financial Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 30(01), pages 23-42, March. Full references (including those not matched with items on IDEAS)
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