• Korea Trade Review
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• v.44 no.1
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• pp.75-86
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• 2019

This study performs a factor analysis that affects the bunker oil price using the Co-integration model and Vector Error Correction Model (VECM). For this purpose, we use data from Clarkson and the analysis results show 17.6% decrease in bunker oil price when the amount of crude oil production increases at 1.0%, 10.3% increase in bunker oil price when the seaborne trade volume increases at 1.0%, 1.0% decrease in bunker oil price when total volume of vessels increases at 1.0%, and 0.003% increase in bunker oil price when 1.0% increase in world GDP, respectively. This study is meaningful in that this study estimates the speed of convergence to long-term equilibrium and identifies the price adjust mechanism which naturally exists in bunker oil market. And it is expected that the future study can provide statistically more meaningful econometric results if it can obtain data during more long-periods and use more various kinds of explanatory variables.

• Journal of Korea Port Economic Association
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• v.33 no.1
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• pp.75-87
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• 2017

The purpose of this study is to utilize the system dynamics to carry out a medium and long-term forecasting analysis of the bunker price. In order to secure accurate bunker price forecast, a quantitative analysis was established based on the casual loop diagram between various variables that affects bunker price. Based on various configuration variables such as crude oil price which affects crude oil consumption & production, GDP and exchange rate which influences economic changes and freight rate which is decided by supply and demand in shipping and logistic market were used in accordance with System Dynamics to forecast bunker price and then objectivity was verified through MAPEs. Based on the result of this study, bunker price is expected to rise until 2029 compared to 2016 but it will not be near the surge sighted in 2012. This study holds value in two ways. First, it supports shipping companies to efficiently manage its fleet, offering comprehensive bunker price risk management by presenting structural relationship between various variables affecting bunker price. Second, rational result derived from bunker price forecast by utilizing dynamic casual loop between various variables.

• Environmental and Resource Economics Review
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• v.16 no.2
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• pp.239-273
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• 2007

Bunker-C is sold at the different price in the market for international bunkering and for export, though the quality of bunker-c is not much different in two markets. The price difference in two markets tends to increase since 2002 in Korea. This study shows that there is a possibility for a structural change in the price difference in two markets in Korea around June, 2002. In the search for possible explanations for this structural change, empirical analyses found that the price difference in Singapore, which had not have any explanatory power before June, 2002, has explained the price difference in Korea after July, 2002. Other explanatory variable for the price difference was the growth rate of crude oil price in the previous period. The empirical results suggest that the price difference in bunkering market and export market might be explained by the price discrimination which is adopted as a competitive strategy by oil companies in competing with Singapore.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.179-184
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• 2021

In this paper, we propose the deep learning-based neural network model to predict bunker price. In the shipping industry, since fuel oil accounts for the largest portion of ship operation costs and its price is highly volatile, so companies can secure market competitiveness by making fuel oil purchasing decisions based on rational and scientific method. In this paper, short-term predictive analysis of HSFO 380CST in Singapore is conducted by using three recurrent neural network models like RNN, LSTM, and GRU. As a result, first, the forecasting performance of RNN models is better than LSTM and GRUs using long-term memory, and thus the predictive contribution of long-term information is low. Second, since the predictive performance of recurrent neural network models is superior to the previous studies using econometric models, it is confirmed that the recurrent neural network models should consider nonlinear properties of bunker price. The result of this paper will be helpful to improve the decision quality of bunker purchasing.

• Journal of Korea Port Economic Association
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• v.29 no.2
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• pp.63-79
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• 2013

The fundamental endeavor of this study is to investigate the asymmetric relationship between bunker price and Baltic Dry-bulk Index (hereafter BDI). Previous investigations employ linear form based analysis between oil price and BDI but we develop nonlinear and asymmetric cointegration method, which is properly able to capture the decreasing and increasing periods differently. The empirical results show there is no relationships in linear model (e.g. Engle and Granger's methods). On the contrary, our estimate reveals there is significant long-run relationship with asymmetric framework, which implies the necessity of nonlinear and asymmetric consideration to the bunker price analysis.

• Journal of Korea Port Economic Association
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• v.38 no.3
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• pp.15-28
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• 2022

Bunkering refers to the supply of bunker fuel necessary for the ship operation, as well as minimizing the price and supply cost of fuel itself, and includes supplying good quality fuel oil in a timely manner and at the optimal port. Bunkering is an important criterion in terms of cost for shipping companies because bunkering involves a significant cost to the purchaser of bunkering from the time of initial purchase. This study aims to prioritize selection criteria for tramper companies to call port for bunkering. For this study, the variables were selected by analyzing the common criteria such as price, location, bunker quality and service and infrastructure etc. employed in previous studies. The AHP method was employed to prioritize the criteria in order. As a result of the analysis, the high level factors appeared in the order of price, location, bunkering quality and port service and infrastructure factors. The importance of price criterion and location criterion was found to be high. In the low level criterion of price, the bunker price per MT was ranked first in importance. In terms of location criteria, the location on the main trade route was high. In the low criteria of bunker quality and port service, the bunkering available types and bunker quality were found to be important factors, and in the low level criteria of infrastructure, anchorage and availability of bunkering during loading and discharging and port security factors were found to be important criteria. This study provides the guidelines for research designed to compare the bunkering port selection factors and to derive their importance suggesting the ways to enhance competitiveness as a bunkering port.

• Journal of Fisheries and Marine Sciences Education
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• v.27 no.1
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• pp.133-144
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• 2015

Recently, Korea shipping companies have been internally/externally difficult to manage their fleet due to the high price of bunker, wage and low cost of charterage and freight. To solve these problems, some shipping companies have tried to set up a new business regarding offshore plant supply vessel(OSV). Owing to the absence of big oil field near the Korea coast, OSV market has not been gradually progressing as far. This study intends to review the legal review of both international and municipal law for the OSV. Therefore I have provided basic legal information to the domestic shipping companies which have desired to enter the OSV's market and suggest legal revision harmoniously to identify the problem in the municipal law.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.107-110
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• 2013

Recently, Korea parliament legislated the Low Carbon Green Growth Act (April, 2012) and approved a bill (May, 2012) to start carbon emission trading system in 2015. It means that for the first time, government would regulate the amounts of carbon emission in private entities, and private entities should attain predefined emission reduction goals by implementing clean development mechanism (CDM) project or buy the Certified Emission Reductions (CERs) from the trading market to avoid penalty. Under these circumstances, it is not easy for them to determine when or how to implement the CDM project because the governmental energy policies about the level of governmental subsidies, periods for free emission allocation, etc. are still under discussion and the future price of the CERs is quite uncertain. Thus, this study presents a real-option based model to assess the financial viability of the CDM project which switches bunker-C oil to liquefied natural gas (LNG). The proposed model is expected to assist private entities in establishing the investment strategy for CDM project under uncertain government energy policies.

• Korea Trade Review
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• v.43 no.3
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• pp.125-145
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• 2018

The Baltic Shipping Exchange is reporting the Baltic Dry Index (BDI) which represents the average charter rate for bulk carriers transporting major cargoes such as iron ore, coal, grain, and so on. And the current BDI index is reflected in the proportion of capesize 40%, panamax 30% and spramax 30%. Like mentioned above, the capesize plays a major role among the various sizes of bulk carriers and this study is to analyze the influence of the factors influencing on charter rate of capesize carriers which transport iron ore and coal as the major cargoes. For this purpose, this study verified causality between variables using Vector Error Correction Model (VECM) and tried to derive a long-run equilibrium model between the dependent variable and independent variables. Regression analysis showed that every six independent variable has a significant effect on the capesize charter rate, even at the 1% level of significance. Charter rate decreases by 0.08% when capesize total fleet increases by 1%, charter rate increases by 0.04% when bunker oil price increases by 1%, and charter rate decreases by 0.01% when Yen/Dollar rate increases by 1%. And charter rate increases by 0.02% when global GDP increases by one unit (1%). In addition, the increase in cargo volume of iron ore and coal which are major transportation items of capesize carriers has also been shown to increase charter rates. Charter rate increases by 0.11% in case of 1% increase in iron ore cargo volume, and 0.09% in case of 1% increase in coal cargo volume. Although there have been some studies to analyze the influence of factors affecting the charterage of bulk carriers in the past, there have been few studies on the analysis of specific size vessels. At present moment when ship size is getting bigger, this study carried out research on capesize vessels, which are biggest among bulk carriers, and whose utilization is continuously increasing. This study is also expected to contribute to the establishment of trade policies for specific cargoes such as iron ore and coal.

• Journal of Korea Port Economic Association
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• v.36 no.4
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• pp.17-30
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• 2020

In the shipping industry, it is essential to engage in the preemptive prediction of freight rate volatility through market monitoring. Considering that freight rates have already started to fall, the loss of shipping companies will soon be uncontrollable. Therefore, in this study, factors affecting the freight rates of bulk carriers, which have relatively large freight rate volatility as compared to container freight rates, were quantified and analyzed. In doing so, we intended to contribute to future shipping market monitoring. We performed an analysis using a vector error correction model and estimated the influence of six independent variables on the charter rates of bulk carriers by Handy Size, Supramax, Panamax, and Cape Size. The six independent variables included the bulk carrier fleet volume, iron ore traffic volume, ribo interest rate, bunker oil price, and Euro-Dollar exchange rate. The dependent variables were handy size (32,000 DWT) spot charter rates, Supramax 6 T/C average charter rates, Pana Max (75,000 DWT) spot charter, and Cape Size (170,000 DWT) spot charter. The study examined charter rates by size of bulk carriers, which was different from studies on existing specific types of ships or fares in oil tankers and chemical carriers other than bulk carriers. Findings revealed that influencing factors differed for each ship size. The Libo interest rate had a significant effect on all four ship types, and the iron ore traffic volume had a significant effect on three ship types. The Ribo rate showed a negative (-) relationship with Handy Size, Supramax, Panamax, and Cape Size. Iron ore traffic influenced three types of linearity, except for Panamax. The size of shipping companies differed depending on their characteristics. These findings are expected to contribute to the establishment of a management strategy for shipping companies by analyzing the factors influencing changes in the freight rates of charterers, which have a profound effect on the management performance of shipping companies.