| 来源类型 | FEEM working papers "Note di lavoro" series
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| 规范类型 | 论文
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| Pricing and Hedging Illiquid Energy Derivatives: an Application to the JCC Index |
| Matteo Manera; Elisa Scarpa
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| 发表日期 | 2006
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| 出处 | Energy: Resources and Markets
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| 出版年 | 2006
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| 语种 | 英语
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| 摘要 | In this paper we discuss a simple strategy for pricing and hedging illiquid financial products, such as the Japanese crude oil cocktail (JCC) index, the most popular OTC energy derivative in Japan. First, we review the existing literature for computing optimal hedge ratios (OHR) and we propose a critical classification of the existing approaches. Second, we compare the empirical performance of different econometric models (namely, regression models for price levels, price first differences, and price returns, as well as error correction and autoregressive distributed lag models) in terms of their computed OHR, using monthly data on the JCC over the period Janury 2000-January 2006. Third, we illustrate and implement a reliable procedure to price and hedge a swap contract on the JCC with a variable oil volume. We explain how to compute a bid/ask spread and to construct the hedging position for the JCC swap. Fourth, we evaluate our swap pricing scheme with backtesting and rolling regression techniques. Our empirical findings show that it is not necessary to use complicated econometric techniques, since the price-level regression model permits to compute more precise optimal hedge ratios relative to its competing alternatives. |
| 特色分类 | G13,G15
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| 关键词 | Hedging models,Cross-hedging,Energy derivatives,Illiquid financial products,Commodity markets,JCC price index
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| URL | https://www.feem.it/en/publications/feem-working-papers-note-di-lavoro-series/pricing-and-hedging-illiquid-energy-derivatives-an-application-to-the-jcc-index/
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| 来源智库 | Fondazione Eni Enrico Mattei (Italy)
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| 资源类型 | 智库出版物
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| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/117393
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推荐引用方式
GB/T 7714 |
Matteo Manera,Elisa Scarpa. Pricing and Hedging Illiquid Energy Derivatives: an Application to the JCC Index. 2006.
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