Optimal hedging efficiency in global freight markets: Comparing FFAs and time charter strategies

Authors

  • Michael Tsatsaronis Department of Port Management and Shipping, School of Economics and Political Sciences, National and Kapodistrian University of Athens, Greece

DOI:

https://doi.org/10.33175/mtr.2024.268609

Keywords:

Static Hedge ratio, Time-Varying Hedge Ratio, OLS, GARCH, Error Correction Model, Rolling Window OLS, Hedging effectiveness, FFAs, Shipping derivatives, Risk management

Abstract

The paper aims to mitigate financial risk in highly volatile shipping freight markets by employing a dynamic hedging model. The primary criterion for evaluating the effectiveness of various methods for estimating optimal hedge ratios through Forward Freight Agreements (FFAs) is the minimum variance hedging rule. Four different methods are utilized to estimate two types of hedge ratios. The first type, a static hedge ratio, is calculated using the OLS and ECM methods. The second type, a time-varying hedge ratio, is determined through a bivariate GARCH model and a Rolling Window OLS method. Additionally, the hedging effectiveness of the traditional method of hedging, time chartering, is compared to the more modern and sophisticated shipping derivatives methods using the coefficient of variation.

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Cite this article: Tsatsaronis, M. (2024). Optimal hedging efficiency in global freight markets: Comparing FFAs and time charter strategies. Maritime Technology and Research, 6(3), 268609. https://doi.org/10.33175/mtr.2024.268609
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Highlights

  • Estimating optimal hedge ratios through Forward Freight Agreements (FFAs) with the minimum variance hedging rule
  • Four different methods are utilized to estimate two types of hedge ratios for static and dynamic hedging
  • Assess the hedging effectiveness of the different methods of hedge ration estimation
  • Compare the hedging effectiveness of the traditional method of hedging, time chartering, to the more modern and sophisticated shipping derivatives methods using the coefficient of variation

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Published

2024-03-20