2018
DOI: 10.1016/j.tra.2018.09.017
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Dynamic patterns of dry bulk freight spot rates through the lens of a time-varying coefficient model

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Cited by 8 publications
(1 citation statement)
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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%
“…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%