Hedging Industrial Metals With Stochastic Volatility Models

Qingfu Liu · Michael Tuan Shew Chng

20 citations0/0 files storedJournal of Futures Markets

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Stochastic processes and financial applications Financial Risk and Volatility Modeling Market Dynamics and Volatility

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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References

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