Hedging Industrial Metals With Stochastic Volatility Models

Authors

  • Qingfu Liu,

    1. Qingfu Liu and Dongxia Xu are at Institute for Financial Studies, School of Economics, Fudan University, Shanghai, China
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  • Michael T. Chng,

    Corresponding author
    1. Michael T. Chng is at International Business School Suzhou, Xian-Jiaotong Liverpool University, Suzhou, China
    2. School of Accounting, Economics and Finance, Deakin University, Melbourne, VIC, Australia
    • Correspondence author, International Business School Suzhou, Xian-Jiaotong Liverpool University, Suzhou, China, and School of Accounting, Economics and Finance, Deakin University, Melbourne Australia. Tel: +61 3 92446537, e-mail: mchng@deakin.edu.au

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  • Dongxia Xu

    1. Qingfu Liu and Dongxia Xu are at Institute for Financial Studies, School of Economics, Fudan University, Shanghai, China
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  • We thank Donald Chance, Chris Gilbert, Ke Tang, Lawrence Zhang, Jari Kappi, Yuelan Chen, and seminar participants at The University of Adelaide, NKFUST, NTUST, SHFE, and UNSW. Liu acknowledges funding support from the National Nature Science Funds of China (71073026; 71173096) and the 985 Engineering Innovation Base at Fudan University. Chng acknowledges funding support from the Australian Center for Financial Studies. We retain full property rights to all existing errors.

Abstract

The financialization of commodities documented in [Tang and Xiong (2012) Financial Analyst Journal, 68:54–74] has led commodity prices to exhibit not only time-varying volatility, but also price and volatility jumps. Using the class of stochastic volatility (SV) models, we incorporate such extreme price movements to generate out-of-sample hedge ratios. In-sample estimation on China's copper (CU) and aluminum (AL) spot and futures markets confirms the presence of price jumps and price-volatility jump correlations. Out-of-sample hedge ratios from the [Bates (1996) Review of Financial Studies, 9:69–107] SV with price jumps model deliver the greatest risk reduction on the unhedged positions at 59.55% for CU and 49.85% for AL. But it is the [Duffie, Pan, and Singleton (2000) Econometrica, 68:1343–1376] SV model with correlated price and volatility jumps that produces hedge ratios which yield the largest Sharpe Ratios of 0.644 for CU and 0.886 for AL. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark 34:704–730, 2014

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