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Return distributions and volatility forecasting in metal futures markets: Evidence from gold, silver, and copper

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  • Ahmed A. A. Khalifa
  • Hong Miao
  • Sanjay Ramchander

Abstract

The characterization of return distributions and forecast of asset‐price variability play a critical role in the study of financial markets. This study estimates four measures of integrated volatility—daily absolute returns, realized volatility, realized bipower volatility, and integrated volatility via Fourier transformation (IVFT)—for gold, silver, and copper by using high‐frequency data for the period 1999 through 2008. The distributional properties are investigated by applying recently developed jump detection procedures and by constructing financial‐time return series. The predictive ability of a GARCH (1,1) forecasting model that uses various volatility measures is also examined. Three important findings are reported. First, the magnitude of the IVFT volatility estimate is the greatest among the four volatility measures. Second, the return distributions of the three markets are not normal. However, when returns are standardized by IVFT and realized volatility, the corresponding return distributions bear closer resemblance to a normal distribution. Notably, the application of financial‐time sampling technique is helpful in obtaining a normal distribution. Finally, the IVFT and realized volatility proxies produce the smallest forecasting errors, and increasing the time frequency of estimating integrated volatility does not necessarily improve forecast accuracy. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark 31:55–80, 2011

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  • Ahmed A. A. Khalifa & Hong Miao & Sanjay Ramchander, 2011. "Return distributions and volatility forecasting in metal futures markets: Evidence from gold, silver, and copper," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(1), pages 55-80, January.
  • Handle: RePEc:wly:jfutmk:v:31:y:2011:i:1:p:55-80
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    1. Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March.
    2. Brian Lucey & Edel Tully, 2006. "Seasonality, risk and return in daily COMEX gold and silver data 1982-2002," Applied Financial Economics, Taylor & Francis Journals, vol. 16(4), pages 319-333.
    3. West, Kenneth D. & Cho, Dongchul, 1995. "The predictive ability of several models of exchange rate volatility," Journal of Econometrics, Elsevier, vol. 69(2), pages 367-391, October.
    4. Koopman, Siem Jan & Jungbacker, Borus & Hol, Eugenie, 2005. "Forecasting daily variability of the S&P 100 stock index using historical, realised and implied volatility measurements," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 445-475, June.
    5. Barucci, Emilio & Reno, Roberto, 2002. "On measuring volatility and the GARCH forecasting performance," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 12(3), pages 183-200, July.
    6. Akgiray, Vedat, et al, 1991. "Conditional Dependence in Precious Metal Prices," The Financial Review, Eastern Finance Association, vol. 26(3), pages 367-386, August.
    7. Baillie, Richard T. & Bollerslev, Tim, 1992. "Prediction in dynamic models with time-dependent conditional variances," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 91-113.
    8. Bahram Adrangi & Arjun Chatrath & Rohan Christie David, 2000. "Price discovery in strategically-linked markets: the case of the gold-silver spread," Applied Financial Economics, Taylor & Francis Journals, vol. 10(3), pages 227-234.
    9. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    10. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
    11. Torben G. Andersen & Tim Bollerslev & Per Frederiksen & Morten Ørregaard Nielsen, 2010. "Continuous-time models, realized volatilities, and testable distributional implications for daily stock returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 233-261.
    12. Ahmet Enis Kocagil, 1997. "Does futures speculation stabilize spot prices? Evidence from metals markets," Applied Financial Economics, Taylor & Francis Journals, vol. 7(1), pages 115-125.
    13. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
    14. Andersen, Torben G. & Bollerslev, Tim & Dobrev, Dobrislav, 2007. "No-arbitrage semi-martingale restrictions for continuous-time volatility models subject to leverage effects, jumps and i.i.d. noise: Theory and testable distributional implications," Journal of Econometrics, Elsevier, vol. 138(1), pages 125-180, May.
    15. Tim Krehbiel & Lee C. Adkins, 1993. "Cointegration tests of the unbiased expectations hypothesis in metals markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 13(7), pages 753-763, October.
    16. Torben G. Andersen & Tim Bollerslev, 1998. "Deutsche Mark-Dollar Volatility: Intraday Activity Patterns, Macroeconomic Announcements, and Longer Run Dependencies," Journal of Finance, American Finance Association, vol. 53(1), pages 219-265, February.
    17. Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
    18. Mancino, M.E. & Sanfelici, S., 2008. "Robustness of Fourier estimator of integrated volatility in the presence of microstructure noise," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2966-2989, February.
    19. Maria Elvira Mancino & Paul Malliavin, 2002. "Fourier series method for measurement of multivariate volatilities," Finance and Stochastics, Springer, vol. 6(1), pages 49-61.
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    Cited by:

    1. Hammoudeh, Shawkat & Malik, Farooq & McAleer, Michael, 2011. "Risk management of precious metals," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(4), pages 435-441.
    2. Sánchez Lasheras, Fernando & de Cos Juez, Francisco Javier & Suárez Sánchez, Ana & Krzemień, Alicja & Riesgo Fernández, Pedro, 2015. "Forecasting the COMEX copper spot price by means of neural networks and ARIMA models," Resources Policy, Elsevier, vol. 45(C), pages 37-43.
    3. 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.
    4. Massimiliano Caporin & Angelo Ranaldo & Gabriel G. Velo, 2015. "Precious metals under the microscope: a high-frequency analysis," Quantitative Finance, Taylor & Francis Journals, vol. 15(5), pages 743-759, May.
    5. repec:gam:jijfss:v:7:y:2019:i:2:p:33-:d:240663 is not listed on IDEAS
    6. Huang, Wen & Huang, Zhuo & Matei, Marius & Wang, Tianyi, 2012. "Price Volatility Forecast for Agricultural Commodity Futures: The Role of High Frequency Data," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 83-103, December.
    7. Tim Pullen & Karen Benson & Robert Faff, 2014. "A Comparative Analysis of the Investment Characteristics of Alternative Gold Assets," Abacus, Accounting Foundation, University of Sydney, vol. 50(1), pages 76-92, March.
    8. 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.
    9. repec:eee:jrpoli:v:58:y:2018:i:c:p:295-302 is not listed on IDEAS
    10. repec:eee:intfin:v:51:y:2017:i:c:p:228-247 is not listed on IDEAS
    11. Antonakakis, Nikolaos & Kizys, Renatas, 2015. "Dynamic spillovers between commodity and currency markets," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 303-319.
    12. repec:eee:glofin:v:36:y:2018:i:c:p:62-77 is not listed on IDEAS
    13. Sinha, Pankaj & Mathur, Kritika, 2016. "Impact of Global Financial Crisis and Implied Volatility in the Equity Market on Gold Futures Traded on Multi Commodity Exchange, India," MPRA Paper 72966, University Library of Munich, Germany.
    14. Caporin, Massimiliano & Ranaldo, Angelo & Velo, Gabriel G., 2013. "Stylized Facts and Dynamic Modeling of High-frequency Data on Precious Metals," Working Papers on Finance 1318, University of St. Gallen, School of Finance.
    15. Wei Long & Dingding Li & Qi Li, 2016. "Testing explosive behavior in the gold market," Empirical Economics, Springer, vol. 51(3), pages 1151-1164, November.
    16. repec:spr:empeco:v:52:y:2017:i:4:d:10.1007_s00181-016-1113-5 is not listed on IDEAS
    17. A. Khalifa & S. Hammoudeh & E. Otranto & S. Ramchander, 2012. "Volatility Transmission across Currency, Commodity and Equity Markets under Multi-Chain Regime Switching: Implications for Hedging and Portfolio Allocation," Working Paper CRENoS 201214, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    18. repec:wly:jforec:v:37:y:2018:i:1:p:16-36 is not listed on IDEAS
    19. Claudiu Tiberiu Albulescu & Daniel Goyeau & Aviral Kumar Tiwari, 2017. "Co-movements and contagion between international stock index futures markets," Empirical Economics, Springer, vol. 52(4), pages 1529-1568, June.
    20. He, Kaijian & Liu, Youjin & Yu, Lean & Lai, Kin Keung, 2016. "Multiscale dependence analysis and portfolio risk modeling for precious metal markets," Resources Policy, Elsevier, vol. 50(C), pages 224-233.
    21. Ehsan Ahmed & J. Rosser & Jamshed Uppal, 2014. "Are there nonlinear speculative bubbles in commodities prices?," Journal of Post Keynesian Economics, Taylor & Francis Journals, vol. 36(3), pages 415-438.

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