2022
DOI: 10.1016/j.energy.2022.124354
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Determinants of dynamic dependence between the crude oil and tanker freight markets: A mixed-frequency data sampling copula model

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Cited by 5 publications
(2 citation statements)
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“…The microeconomic factors discovered in the literature can be listed as age of the ship (Alizadeh and Talley, 2011), size of the ship (Kavussanos, 2003), speed of the ship (Beenstock and Vergottis, 1989;Magirou et al, 2015), characteristics of buyers and sellers (Adland et al, 2016), open registries (Wilmsmeier and Martinez-Zarzoso, 2010), and bunker price (Shen and Chou, 2015;Yin et al, 2017). On the other hand, the macroeconomic and some other factors discovered in the literature can be listed as oil price (Shi et al, 2022), fleet size (Xu et al, 2011), industrial production (Strandenes, 1984), connectivity to transportation network (Wilmsmeier and Hoffmann, 2008), exchange rates (Chi, 2016), commodity prices (Bandyopadhyay and Rajib, 2023), inflation (Michail et al, 2022), GDP (Başer and Açık, 2019), port efficiency (Lei and Bachmann, 2020), port closures (Lewis et al, 2006), market sentiment (Bai et al, 2021), weather conditions (Açık and Başer, 2018), and pandemics (Xu et al, 2022). Any factor that affects freight will naturally be reflected in the GSCPI value, but modeling all these factors is relatively difficult.…”
Section: Literature Reviewmentioning
confidence: 99%
“…The microeconomic factors discovered in the literature can be listed as age of the ship (Alizadeh and Talley, 2011), size of the ship (Kavussanos, 2003), speed of the ship (Beenstock and Vergottis, 1989;Magirou et al, 2015), characteristics of buyers and sellers (Adland et al, 2016), open registries (Wilmsmeier and Martinez-Zarzoso, 2010), and bunker price (Shen and Chou, 2015;Yin et al, 2017). On the other hand, the macroeconomic and some other factors discovered in the literature can be listed as oil price (Shi et al, 2022), fleet size (Xu et al, 2011), industrial production (Strandenes, 1984), connectivity to transportation network (Wilmsmeier and Hoffmann, 2008), exchange rates (Chi, 2016), commodity prices (Bandyopadhyay and Rajib, 2023), inflation (Michail et al, 2022), GDP (Başer and Açık, 2019), port efficiency (Lei and Bachmann, 2020), port closures (Lewis et al, 2006), market sentiment (Bai et al, 2021), weather conditions (Açık and Başer, 2018), and pandemics (Xu et al, 2022). Any factor that affects freight will naturally be reflected in the GSCPI value, but modeling all these factors is relatively difficult.…”
Section: Literature Reviewmentioning
confidence: 99%
“…In order to deal with the problem of mixed frequency data, the copula-MIDAS framework proposed by Gong et al (2018) is employed in this papaer. The copula-MIDAS model provides a convenient framework for describing the dependence between financial assets that exhibits obvious time-varying characteristics, which allows explanatory variables to be directly included in the dependence structure (Jiang et al, 2020;Nguyen and Javed, 2021;Gong et al, 2022;Shi et al, 2022;Wu et al, 2022). However, the copula-MIDAS model fails to investigate the influence of RA on the dependence between crude oil futures and EUA futurres merkats.…”
Section: Open Accessmentioning
confidence: 99%