Companies dependent on commodities for their production have to deal with volatile commodity prices and should employ measures for risk reduction as unfavourable spot price development may cause significant losses. A useful tool for diminishing the risk is hedging on futures market; however, this approach faces a crucial question of optimal hedge ratio determination (ratio between spot and futures units). Our thesis examines nine different ways of optimal hedge ratio estimation (naive, Sharpe, mean extended Gini coefficient, generalized semivariance, value at risk, and minimum variance through OLS, error correction, GARCH, and bivariate GARCH models) and evaluates their efficiency using the data on eight different commodities. The results differ across the respective commodities and cannot be generalized. Two conclusions resulting from the analysis refer to performance of naive and OLS hedge ratios and constant vs time varying hedge ratios. We find that complex hedge ratios, such as bivariate GARCH or VaR hedge ratios, do not outperform naive and OLS hedge ratios and that the results of constant hedge ratios are mostly as good as results of time-varying hedge ratios.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:198395 |
| Date | January 2013 |
| Creators | Máková, Barbora |
| Contributors | Černý, Michal, Cahlík, Tomáš |
| Publisher | Vysoká škola ekonomická v Praze |
| Source Sets | Czech ETDs |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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