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Modelling Long Memory Volatility in Agricultural Commodity Futures Returns

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2012-05
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This paper estimates a long memory volatility model for 16 agricultural commodity futures returns from different futures markets, namely corn, oats, soybeans, soybean meal, soybean oil, wheat, live cattle, cattle feeder, pork, cocoa, coffee, cotton, orange juice, Kansas City wheat, rubber, and palm oil. The class of fractional GARCH models, namely the FIGARCH model of Baillie et al. (1996), FIEGARCH model of Bollerslev and Mikkelsen (1996), and FIAPARCH model of Tse (1998), are modelled and compared with the GARCH model of Bollerslev (1986), EGARCH model of Nelson (1991), and APARCH model of Ding et al. (1993). The estimated d parameters, indicating long-term dependence, suggest that fractional integration is found in most of agricultural commodity futures returns series. In addition, the FIGARCH (1,d,1) and FIEGARCH(1,d,1) models are found to outperform their GARCH(1,1) and EGARCH(1,1) counterparts.
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For financial support, the first author is most grateful to the National Science Council, Taiwan, the second author wishes to thank the Australian Research Council, National Science Council, Taiwan, and the Japan Society for the Promotion of Science, and the third author acknowledges the Faculty of Economics, Maejo University.
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Baillie, R., T. Bollerslev and H. Mikkelsen (1996), Fractionally Integrated Generalized Autoregressive Conditional Heteroskedasticity, Journal of Econometrics, 73, 5–59. Baillie, R., Y. Han, R. Myers, and J. Song (2007), Long Memory Models for Daily and High Frequency Commodity Futures Returns, Journal of Futures Markets, 27, 643-668. Baillie, R., Y. Han and T. Kwon (2002), Further Long Memory Properties of Inflationary Shocks, Southern Economic Journal, 68, 496-510. Barkoulas, J., W. Labys and J. Onochie (1997), Fractional Dynamics in International Commodity Prices, Journal of Futures Markets, 17, 161–189. Bollerslev, T. (1986), Generalized Autoregressive Conditional Heteroscedasticity, Journal of Econometrices, 31, 307-327. Bollerslev, T. and H. Mikkelsen (1996), Modeling and Pricing Long Memory in Stock Market Volatility, Journal of Econometrics, 73, 151–184. Brunetti, C. and C. Gilbert (2000), Bivariate FIGARCH and Fractional Cointegration, Journal of Empirical Finance, 7, 509-530. Chung, C. (1999), Estimating the Fractionally Integrated GARCH Model, unpublished paper, National Taiwan University. Coakley, J., J. Dollery and N. Kellard (2008), The Role of Long Memory in Hedging Effectiveness, Computational Statistics and Data Analysis, 52, 3075-3082. Conrad, C. and M. Lamla (2007), The High-Frequency Response of the EUR-US Dollar Exchange Rate to ECB Monetary Policy Announcements, KOF Working Papers, No 174. Crato, N. and B. Ray (2000), Memory in Returns and Volatilities of Futures Contracts, Journal of Futures Markets, 20, 525–543. Davidson, J. (2004), Moment and Memory Properties of Linear Conditional Heteroscedasticity Models, and A New Model, Journal of Business and Economic Statistics, 22, 16-29. Degiannakis, S. (2004), Volatility Forecasting: Evidence from a Fractional Integrated Asymmetric Power ARCH Skewed-t Model, Applied Financial Economics, 14, 1333-1342. Ding, Z., C. Granger and R. Engle (1993), A Long Memory Property of Stock Market Returns and a New Model, Journal of Empirical Finance 1, 83-106. Engle, R.F. (1982), Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation, Econometrica, 55, 391-407. Engle, R.F. and T. Bollerslev (1986), Modeling the persistence of conditional variances, Econometric Reviews, 5, 1-50. Geweke, J. (1986), Modeling the Persistence of Conditional Variances: A Comment, Econometric Reviews, 5, 57-61. Glosten, L., R. Jagannathan and D. Runkle (1992), On the Relation between the Expected Value and Volatiltiy and of the Nominal Excess Returns on Stocks, Journal of Finance, 46, 1779-1801. Higgins, M. and A. Bera (1992), A Class of Nonlinear ARCH Models, International Economic Review, 33, 137-158. Hyun-Joung, J. (2008), A Long Memory Conditional Variance Model for International Grain Markets, Journal of Rural Development, 31, 81-103. Jefferis, K. and P. Thupayagale (2008), Long Memory in Southern Africa Stock Markets, South African Journal of Economics, 73, 384-398. Jin, H. and D. Frechette (2004), Fractional Integration in Agricultural Futures Price Volatilities, American Journal of Agricultural Economics, 86, 432-443. Kang, S. and S. Yoon (2007), Long Memory Properties in Return and Volatility: Evidence from the Korean Stock Market, Physica A, 385, 591-600. Laurent S. and J. Peters (2006), G@RCH 4.2, Estimating and Forecasting ARCH Models, London, Timberlake Consultants. Ling, S. and M. McAleer (2002), Necessary and Sufficient Moment Conditions for the GARCH(r,s) and Asymmetric Power GARCH(r,s) Models, Econometric Theory, 18, 722-729. Lux, T. and T. Kaizoji (2007), Forecasting Volatility and Volume in the Tokyo Stock Market: Long Memory, Fractality and Regime Switching, Journal of Economic Dynamics and Control, 31, 1808-1843. McAleer, M. (2005), Automated Inference and Learning in Modeling Financial Volatility, Econometric Theory, 21, 232-261. McAleer, M., F. Chan, and D. Marinova (2007), An Econometric Analysis of Asymmetric Volatility: Theory and Application to Patents, Journal of Econometrics, 139, 259-284. Nelson, D. (1991), Conditional Heteroskedasticity in Asset Returns: A New Approach, Econometrica, 59, 347–370. Ñiguez , T. (2007), Volatility and VaR Forecasting in the Madrid Stock Exchange, Spanish Economic Review, 10, 169-196. Pantula, S. (1986), Modeling the Persistence of Conditional Variances: A Comment, Econometric Reviews, 5, 71–74. Poon, S. and C. Granger (2003), Forecasting Volatility in Financial Markets: A Review, Journal of Economic Literature, XLI, 478-539. Ruiz, E. and H. Veiga (2008), Modelling Long-Memory Volatilities with Leverage Effect: ALMSV versus FIEGARCH, Computational Statistics and Data Analysis, 52, 2846-2862. Schwert, W. (1990), Stock Volatility and the Crash of ’87. Review of Financial Studies, 3, 77–102. Sephton, P. (2009), Fractional integration in agricultural futures price volatilities revisited. Agricultural Economics, 40, 103-111. Taylor, S. (1986), Modelling Financial Time Series. New York, Wiley. Tse, Y. (1998), The Conditional Heteroscedasticity of the Yen-Dollar Exchange Rate, Journal of Applied Econometrics, 193, 49-55. Zakoian, J. (1994), Threshold Heteroskedasticity Models, Journal of Economic Dynamics and Control, 15, 931-955.