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Power ARCH modelling of commodity futures data on the London Metal Exchange

Author

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  • Michael McKenzie
  • Heather Mitchell
  • Robert Brooks
  • Robert Faff

Abstract

A recent addition to the ARCH family of econometric models was introduced by Ding and co-workers wherein the power term by which the data is transformed was estimated within the model rather than being imposed by the researcher. This paper considers the ability of the Power GARCH class of models to capture the stylized features of volatility in a range of commodity futures prices traded on the London Metals Exchange (LME). The results of this procedure suggest that asymmetric effects are not generally present in the LME futures data. Further, unlike stock market data which is well described by the model, futures data is not as well described by the APGARCH model. Nested within the APGARCH model are several other models from the ARCH family. This paper uses the standard log likelihood procedure to conduct pairwise comparisons of the relative merits of each and the results suggest that it is the Taylor GARCH model which performs best.

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  • Michael McKenzie & Heather Mitchell & Robert Brooks & Robert Faff, 2001. "Power ARCH modelling of commodity futures data on the London Metal Exchange," The European Journal of Finance, Taylor & Francis Journals, vol. 7(1), pages 22-38.
    • Handle: RePEc:taf:eurjfi:v:7:y:2001:i:1:p:22-38
    DOI: 10.1080/13518470123011
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    1. Nelson, Daniel B., 1990. "ARCH models as diffusion approximations," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 7-38.
    2. Michael McKenzie, 1997. "ARCH modelling of Australian bilateral exchange rate data," Applied Financial Economics, Taylor & Francis Journals, vol. 7(2), pages 147-164.
    3. Cecchetti, Stephen G & Cumby, Robert E & Figlewski, Stephen, 1988. "Estimation of the Optimal Futures Hedge," The Review of Economics and Statistics, MIT Press, vol. 70(4), pages 623-630, November.
    4. Baillie, Richard T & Myers, Robert J, 1991. "Bivariate GARCH Estimation of the Optimal Commodity Futures Hedge," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(2), pages 109-124, April-Jun.
    5. Berry Wilson & Reena Aggarwal & Carla Inclan, 1996. "Detecting volatility changes across the oil sector," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 16(3), pages 313-330, May.
    6. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    7. Christopher F. Baum & John Barkoulas, 1996. "Time‐varying risk premia in the foreign currency futures basis," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 16(7), pages 735-755, October.
    8. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    9. Higgins, Matthew L & Bera, Anil K, 1992. "A Class of Nonlinear ARCH Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 33(1), pages 137-158, February.
    10. Hall, S G, 1991. "An Application of the Stochastic GARCH-in-Mean Model to Risk Premia in the London Metal Exchange," The Manchester School of Economic & Social Studies, University of Manchester, vol. 59(0), pages 57-71, Supplemen.
    11. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    12. Ding, Zhuanxin & Granger, Clive W. J., 1996. "Modeling volatility persistence of speculative returns: A new approach," Journal of Econometrics, Elsevier, vol. 73(1), pages 185-215, July.
    13. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    14. Geoffrey Heal & Michael Barrow, 1980. "The Relationship between Interest Rates and Metal Price Movements," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 161-181.
    15. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    16. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    17. Dajiang Guo, 1996. "The predictive power of implied stochastic variance from currency options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 16(8), pages 915-942, December.
    18. Hsieh, David A & Kulatilaka, Nalin, 1982. "Rational Expectations and Risk Premia in Forward Markets: Primary Metals at the London Metals Exchange," Journal of Finance, American Finance Association, vol. 37(5), pages 1199-1207, December.
    19. Sephton, Peter S. & Cochrane, Donald K., 1990. "A note on the efficiency of the London metal exchange," Economics Letters, Elsevier, vol. 33(4), pages 341-345, August.
    20. Laulajainen, Risto, 1995. "The geographical reach of a commodity exchange : The London metal exchange and beyond," Resources Policy, Elsevier, vol. 21(2), pages 133-141, June.
    21. Kroner, Kenneth F. & Sultan, Jahangir, 1993. "Time-Varying Distributions and Dynamic Hedging with Foreign Currency Futures," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(4), pages 535-551, December.
    22. Tae H. Park & Lorne N. Switzer, 1995. "Bivariate GARCH estimation of the optimal hedge ratios for stock index futures: A note," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 15(1), pages 61-67, February.
    23. Seung‐Ryong Yang & B. Wade Brorsen, 1993. "Nonlinear dynamics of daily futures prices: Conditional heteroskedasticity or chaos?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 13(2), pages 175-191, April.
    24. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    25. Tse, Y. K. & Tsui, Albert K. C., 1997. "Conditional volatility in foreign exchange rates: Evidence from the Malaysian ringgit and Singapore dollar," Pacific-Basin Finance Journal, Elsevier, vol. 5(3), pages 345-356, July.
    26. G. William Schwert, 1988. "Why Does Stock Market Volatility Change Over Time?," NBER Working Papers 2798, National Bureau of Economic Research, Inc.
    27. Fama, Eugene F, 1976. "Inflation Uncertainty and Expected Returns on Treasury Bills," Journal of Political Economy, University of Chicago Press, vol. 84(3), pages 427-448, June.
    28. MacDonald, Ronald & Taylor, Mark P, 1988. "Metals Prices, Efficiency and Cointegration: Some Evidence from the London Metal Exchange," Bulletin of Economic Research, Wiley Blackwell, vol. 40(3), pages 235-239, June.
    29. Bera, Anil K & Higgins, Matthew L, 1993. "ARCH Models: Properties, Estimation and Testing," Journal of Economic Surveys, Wiley Blackwell, vol. 7(4), pages 305-366, December.
    30. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-547, August.
    31. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    32. MacDonald, Ronald & Taylor, Mark P, 1988. "Testing Rational Expectations and Efficiency in the London Metal Exchange," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 50(1), pages 41-52, February.
    33. Brooks, Robert D. & Faff, Robert W. & McKenzie, Michael D. & Mitchell, Heather, 2000. "A multi-country study of power ARCH models and national stock market returns," Journal of International Money and Finance, Elsevier, vol. 19(3), pages 377-397, June.
    34. Donald Lien & Xiangdong Luo, 1994. "Multiperiod hedging in the presence of conditional heteroskedasticity," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 14(8), pages 927-955, December.
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    Cited by:

    1. Tully, Edel & Lucey, Brian M., 2007. "A power GARCH examination of the gold market," Research in International Business and Finance, Elsevier, vol. 21(2), pages 316-325, June.
    2. Sinha, Pankaj & Mathur, Kritika, 2013. "A study on the Price Behavior of Base Metals traded in India," MPRA Paper 47028, University Library of Munich, Germany.
    3. Hammoudeh, Shawkat M. & Yuan, Yuan & McAleer, Michael & Thompson, Mark A., 2010. "Precious metals-exchange rate volatility transmissions and hedging strategies," International Review of Economics & Finance, Elsevier, vol. 19(4), pages 633-647, October.
    4. Gaye Hatice Gencer & Zafer Musoglu, 2014. "Volatility Modeling and Forecasting of Istanbul Gold Exchange (IGE)," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 5(2), pages 87-101, April.
    5. Qiang Xia & Heung Wong & Jinshan Liu & Rubing Liang, 2017. "Bayesian Analysis of Power-Transformed and Threshold GARCH Models: A Griddy-Gibbs Sampler Approach," Computational Economics, Springer;Society for Computational Economics, vol. 50(3), pages 353-372, October.
    6. Chkili, Walid & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2014. "Volatility forecasting and risk management for commodity markets in the presence of asymmetry and long memory," Energy Economics, Elsevier, vol. 41(C), pages 1-18.
    7. Triantafyllopoulos, Kostas, 2006. "Multivariate discount weighted regression and local level models," Computational Statistics & Data Analysis, Elsevier, vol. 50(12), pages 3702-3720, August.
    8. Nidhi Choudhary & Girish K. Nair & Harsh Purohit, 2015. "Volatility In Copper Prices In India," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 1-26, December.
    9. Perry Sadorsky & Michael D. McKenzie, 2008. "Power transformation models and volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(7), pages 587-606.
    10. Jin, Jiayu & Han, Liyan & Wu, Lei & Zeng, Hongchao, 2020. "The hedging effect of green bonds on carbon market risk," International Review of Financial Analysis, Elsevier, vol. 71(C).
    11. K. Triantafyllopoulos, 2008. "Multivariate stochastic volatility with Bayesian dynamic linear models," Papers 0802.0214, arXiv.org.
    12. Nikhil Kaushik, 2018. "Do global oil price shocks affect Indian metal market?," Energy & Environment, , vol. 29(6), pages 891-904, September.
    13. Clinton Watkins & Michael McAleer, 2004. "Econometric modelling of non‐ferrous metal prices," Journal of Economic Surveys, Wiley Blackwell, vol. 18(5), pages 651-701, December.
    14. Chevallier, Julien & Ielpo, Florian, 2017. "Investigating the leverage effect in commodity markets with a recursive estimation approach," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 763-778.
    15. Ane, Thierry, 2006. "An analysis of the flexibility of Asymmetric Power GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1293-1311, November.

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    More about this item

    Keywords

    Power Arch London Metal Exchange Futures;

    JEL classification:

    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products

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