Commodity futures and market efficiency: A fractional integrated approach
In financial time series, persistence or inertia is a feature usually observable in absolute returns, i.e., a proxy for volatility. Moreover, asset return series should be essentially unpredictable according to the efficiency market hypothesis (EMH) in its weak form. Surprisingly, recent literature has found evidence of anti-persistence in technology stocks and commodity futures returns. Anti-persistence would be indicative of an overreaction of asset prices to incoming information. In this article, we concentrate on a sample of 20 DJ-AIG commodity future indices--including broad indices and sub-indices (e.g., energy, grains, industrial metals, and livestock) over the period January 1991-June 2008. We conclude that returns series either over-react or under-react to new market information, which disconfirms the EMH in its weak form. Such disconfirmation would make it possible for market participants to devise non-linear statistical models for improved index forecasting and derivatives valuation.
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- Cornelis A. Los & Bing Yu, 2005.
"Persistence Characteristics of the Chinese Stock Markets,"
- Los, Cornelis A. & Yu, Bing, 2008. "Persistence characteristics of the Chinese stock markets," International Review of Financial Analysis, Elsevier, vol. 17(1), pages 64-82.
- George Kapetanios, 2007. "Measuring Conditional Persistence in Nonlinear Time Series," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(3), pages 363-386, 06.
- Pasquini, Michele & Serva, Maurizio, 1999. "Multiscaling and clustering of volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 269(1), pages 140-147.
- Jensen, Mark J, 1999.
"Using wavelets to obtain a consistent ordinary least squares estimator of the long-memory parameter,"
39152, University Library of Munich, Germany.
- Mark J. Jensen, 1997. "Using Wavelets to Obtain a Consistent Ordinary Least Squares Estimator of the Long Memory Parameter," Econometrics 9710002, EconWPA.
- Thierry Ané & Loredana Ureche-Rangau, 2004.
"Does trading volume really explain stock returns volatility?,"
2004-FIN-02, IESEG School of Management.
- Ané, Thierry & Ureche-Rangau, Loredana, 2008. "Does trading volume really explain stock returns volatility?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(3), pages 216-235, July.
- Fernandez, Viviana, 2007. "A postcard from the past: The behavior of U.S. stock markets during 1871–1938," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 386(1), pages 267-282.
- T. Ane & L. Ureche-Rangau, 2008. "Does Trading Volume Really Explain Stock Returns Volatility ?," Post-Print hal-00260668, HAL.
- John Barkoulas & Christopher F. Baum, 2003.
"Long-Memory Forecasting of U.S. Monetary Indices,"
Boston College Working Papers in Economics
558, Boston College Department of Economics.
- Connor Jeff & Rossiter Rosemary, 2005. "Wavelet Transforms and Commodity Prices," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(1), pages 1-22, March.
- Jensen, Mark J., 2000.
"An alternative maximum likelihood estimator of long-memory processes using compactly supported wavelets,"
Journal of Economic Dynamics and Control,
Elsevier, vol. 24(3), pages 361-387, March.
- Mark J. Jensen, 1997. "An Alternative Maximum Likelihood Estimator of Long-Memeory Processes Using Compactly Supported Wavelets," Econometrics 9709002, EconWPA.
- Carbone, A. & Castelli, G. & Stanley, H.E., 2004. "Time-dependent Hurst exponent in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 267-271.
- John T. Barkoulas & Christopher F. Baum & Nickolaos Travlos, 1996.
"Long Memory in the Greek Stock Market,"
Boston College Working Papers in Economics
356., Boston College Department of Economics.
- Mulligan, Robert F., 2004. "Fractal analysis of highly volatile markets: an application to technology equities," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(1), pages 155-179, February.
- Mielniczuk, J. & Wojdyllo, P., 2007. "Estimation of Hurst exponent revisited," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4510-4525, May.
- Mills, Terence C., 2004. "Statistical analysis of daily gold price data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 338(3), pages 559-566.
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