Dynamic patterns of dry bulk freight spot rates through the lens of a time-varying coefficient model

Ko, Byoung-Wook

doi:10.1016/j.tra.2018.09.017

Cited by 8 publications

(1 citation statement)

References 22 publications

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“…Yang and Mehmed (2019) utilize artificial neural networks to examine freight rate forecasting and provide evidence supporting that the information contained in FFA prices can generate more accurate forecasts of spot freight rates in the selected Panamax routes. Other studies investigating the pricing relationship between the spot freight rates and FFA prices include Bessler et al (2008) who find support for the cointegration relationship for Panamax bulk carriers by the extended VECM, Tezuka et al (2012) who develop an equilibrium price model with consideration of non‐homogeneous market participants, Benth and Koekebakker (2016) who apply the stochastic model to derive theoretical FFA prices based on the dynamics of Supramax spot freight rates, and Ko (2018) who utilizes a time‐varying coefficient‐error correction model for the dry bulk shipping markets.…”

Section: Literature Reviewmentioning

confidence: 99%

Maximum utility portfolio construction in the forward freight agreement markets: Evidence from a multivariate skewed t copula

Gong

Wang

Zhu

et al. 2022

Journal of Futures Markets

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We form portfolios consisting of diverse quarterly forward freight agreement (FFA) contracts to maximize the market participant's expected utility. The empirical findings indicate that individual FFA returns display clear autocorrelation, seasonality, fat tail, and heteroscedasticity. The multivariate positively skewed t copula is suggested for constructing maximum utility FFA portfolios, implying that the constituent FFA returns exhibit higher correlations when they rise together. The out-of-sample trading strategy performance metrics and various robustness checks further indicate that the aforementioned copula performs best and robustly for all portfolios. These findings provide profound methodological and managerial implications for market participants to improve risk management.

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