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• W2042181121 abstract "Statistical time-series approaches to hedging are difficult to beat, especially out-of-sample, and are capable of out-performing many theory-based derivative pricing model approaches to hedging commodity price risks using futures contracts. However, the vast majority of time-series approaches to hedging discussed in the literature are essentially linear statistical projections, whether univariate or multivariate. Little is known about the potential hedging capabilities of nonlinear methods. This study describes how least-squares orthogonal polynomial approximation methods based on the spanning polynomial projection (SPP) can be used to enhance standard (linear) optimal hedging methods and improve hedging performance for a hedger with a mean–variance objective. Empirical analyses show that the SPP can be used effectively for hedging and gives better out-of-sample hedging performance than the benchmark VEC-GARCH hedging model. Results are robust to the inclusion of transaction costs and risk-aversion assumptions." @default.
• W2042181121 created "2016-06-24" @default.
• W2042181121 creator A5041718386 @default.
• W2042181121 creator A5076898648 @default.
• W2042181121 date "2008-09-01" @default.
• W2042181121 modified "2023-10-01" @default.
• W2042181121 title "Enhancing hedging performance with the spanning polynomial projection" @default.
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• W2042181121 doi "https://doi.org/10.1080/14697680701570101" @default.
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