VaR as a mitigating risk tool in the maritime sector: An empirical approach on freight rates

Basdekis Charalampos; Katsampoxakis Ioannis; Gkolfinopoulos Alexandros; Basdekis Charalampos; Katsampoxakis Ioannis; Gkolfinopoulos Alexandros

doi:10.3934/QFE.2022007

Quantitative Finance and Economics

2022, Volume 6, Issue 2: 158-176. doi: 10.3934/QFE.2022007

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Research article

VaR as a mitigating risk tool in the maritime sector: An empirical approach on freight rates

1.
Department of Economics, National and Kapodistrian University of Athens, Athens, Greece
2.
Department of Statistics and Actuarial-Financial Mathematics, University of the Aegean, Greece
3.
School of Applied Mathematics and Physics, National Technical University of Athens, Greece

Received: 30 December 2021 Revised: 02 April 2022 Accepted: 11 April 2022 Published: 19 April 2022
JEL Codes: G32, G13, G11, C14, C15

Shipping freight rates fluctuation is considered as one of the most important risk factors that participants face in the tanker shipping market (ship-owners, charterers, traders, hedge funds, banks and other financial institutions) in order to watch its evolution. This study examines freight rates for two of the most popular clean and dirty tanker routes; TC2 and TD3 from 22 May 2007 to 21 September 2015, using daily spot and future prices. The full data sample is divided into two sub periods, from 22 May 2007 to 13 August 2013 (in sample period) on which the model estimation section is based and from 14 August 2013 to 21 September 2015 (out of sample period) over which the Value at Risk is measured and backtesting process was performed. In all cases tested, there are observed high peaks and fat tails in all distributions. We apply a range of VaR models (parametric and non-parametric) in order to estimate the risk of the returns of TC2 route and TD3 route for spot, one month and three months future market. Backtesting tools are implemented in order to find the best fit model in terms of economic and statistical accuracy. Our empirical analysis concludes that the best fit models used for mitigating risk are simple GARCH model and non-parametric model. The above outcome seems to be valid a) for spot returns as well as for future returns and b) for short and long positions. In addition to the aforementioned conclusions, it is observed high freight rate risk at all routes. Our results are useful for risk management purposes for all the tanker shipping market participants and derivatives' counterparties.
- Value at Risk,
- GARCH,
- tanker shipping market,
- parametric models,
- non-parametric models
Citation: Basdekis Charalampos, Katsampoxakis Ioannis, Gkolfinopoulos Alexandros. VaR as a mitigating risk tool in the maritime sector: An empirical approach on freight rates[J]. Quantitative Finance and Economics, 2022, 6(2): 158-176. doi: 10.3934/QFE.2022007

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Abstract

Shipping freight rates fluctuation is considered as one of the most important risk factors that participants face in the tanker shipping market (ship-owners, charterers, traders, hedge funds, banks and other financial institutions) in order to watch its evolution. This study examines freight rates for two of the most popular clean and dirty tanker routes; TC2 and TD3 from 22 May 2007 to 21 September 2015, using daily spot and future prices. The full data sample is divided into two sub periods, from 22 May 2007 to 13 August 2013 (in sample period) on which the model estimation section is based and from 14 August 2013 to 21 September 2015 (out of sample period) over which the Value at Risk is measured and backtesting process was performed. In all cases tested, there are observed high peaks and fat tails in all distributions. We apply a range of VaR models (parametric and non-parametric) in order to estimate the risk of the returns of TC2 route and TD3 route for spot, one month and three months future market. Backtesting tools are implemented in order to find the best fit model in terms of economic and statistical accuracy. Our empirical analysis concludes that the best fit models used for mitigating risk are simple GARCH model and non-parametric model. The above outcome seems to be valid a) for spot returns as well as for future returns and b) for short and long positions. In addition to the aforementioned conclusions, it is observed high freight rate risk at all routes. Our results are useful for risk management purposes for all the tanker shipping market participants and derivatives' counterparties.

References

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