• Korea Trade Review
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• v.43 no.5
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• pp.159-177
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• 2018

The container shipping sector is an important international logistics operation that connects open economies. Freight rates rapidly change as the market fluctuates, and staff related to the shipping market are interested in factors that determine freight rates in the container market. This study uses the Vector Error Correction Model(VECM) to estimate the impact of factors affecting container freight rates. This study uses data published by Clarksons. The analysis results show a 4.2% increase in freight rates when world container traffic increases at 1.0%, a 4.0% decrease in freight rates when volume of container carriers increases by 1.0%, a 0.07% increase in freight rates when bunker price increases by 1.0%, and a 0.04% increase in freight rates accompanying 1.0% increase in libor interests rates. In addition, if the current freight rate is 1.0% higher than the long-term equilibrium rate, the freight rate will be reduced by 3.2% in the subsequent term. In addition, if the current freight rate is 1.0% lower than the long-term equilibrium rate, the freight rate will decrease by 0.12% in the following term. However, the adjusting power in a period of recession is not statistically significant which means that the pressure of freight rate increase in this case is neglectable. This research is expected to contribute to the utilization of scientific methods in forecasting container freight rates.

• Journal of Korea Trade
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• v.23 no.2
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• pp.34-45
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• 2019

Purpose - This study investigates the lead-lag relations between the prices of major commodities imported into Korea and corresponding shipping freight rates. This paper aims to provide implications for cross-market causal relations between related economic segments. Design/Methodology - For economic long-run equilibrium between commodity prices and freights, a Johansen (1988) cointegration test is employed first. Then, Granger (1987) causality tests are performed under the vector error correction model (VECM) framework. Findings - The results indicate that the direction of causality varies by raw materials, which is attributable to different economic mechanisms in the corresponding shipping transportation sectors. In addition, the significance of causality becomes blurred during the post-2008 period. Practical Implication - Corporate managers in commodity trading, steelmaking, power generation, and oil refinery sectors can take advantage of the findings in this study as identifying leading economic indicators can be helpful for decision making in both short- and long-term strategies. Originality/value - This study is the first attempt to analyze the inter-relations between commodity prices and corresponding freight rates focusing on raw material imports of Korea.

• Korea Trade Review
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• v.43 no.6
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• pp.51-70
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• 2018

This study is to define the relationship between capital structure and the market share in the global shipping market, estimating the debt-equity ratio. To analyze the impact of the debt-equity ratio on market share, this study collected data from the 100 largest shipping companies from 2010 to 2017. Results identified that global shipping lines moderate their debt-equity rates to 62%, and all of them strategically utilize debt in order to increase market share in global shipping market. In comparison between the group focused on cargo volume and another group focused on freight rates, it is found that the group focused on cargo volume increase their handling cargo volume through increasing the debt rates. Another group used debt rate for reducing the freight rate and enhancing market power. Furthermore, after classifying the samples into high-growth and low-growth companies, this study compared the group focused on cargo volume and another group focused on freight rates. As a result, the low-growth group showed more significant impacts of the debt rate on market share than the high-growth group. The results of this study provide useful insight for future strategic decision making of shipping lines in the global shipping market.

• Journal of Korea Port Economic Association
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• v.35 no.3
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• pp.61-72
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• 2019

In order to enhance the competitiveness of the container shipping industry and promote its development, based on the empirical analyses using multivariate time series models, this study aims to suggest a few strategies related to the dynamics of the container shipping market. It uses the vector autoregressive (VAR) and vector error correction (VEC) models as analytical methodologies. Additionally, it uses the annual trade volumes, fleets, and freight rates as the dataset. According to the empirical results, we can infer that the most exogenous variable, the trade volume, exerted the highest influence on the total dynamics of the container shipping market. Based on these empirical results, this study suggests some implications for ship investment, freight rate forecasting, and the strategies of shipping firms. Concerning ship investment, since the exogenous trade volume variable contributes most to the uncertainty of freight rates, corporate finance can be considered more appropriate for container ship investment than project finance. Concerning the freight rate forecasting, the VAR and VEC models use the past information and the cointegrating regression model assumes future information, and hence the former models are found better than the latter model. Finally, concerning the strategies of shipping firms, this study recommends the use of cycle-linked repayment scheme and services contract.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.5
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• pp.574-583
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• 2021

Predicting shipping markets is an important issue. Such predictions form the basis for decisions on investment methods, fleet formation methods, freight rates, etc., which greatly affect the profits and survival of a company. To this end, in this study, we propose a shipping freight rate prediction model for container ships using gated recurrent units (GRUs) and long short-term memory structure. The target of our freight rate prediction is the China Container Freight Index (CCFI), and CCFI data from March 2003 to May 2020 were used for training. The CCFI after June 2020 was first predicted according to each model and then compared and analyzed with the actual CCFI. For the experimental model, a total of six models were designed according to the hyperparameter settings. Additionally, the ARIMA model was included in the experiment for performance comparison with the traditional analysis method. The optimal model was selected based on two evaluation methods. The first evaluation method selects the model with the smallest average value of the root mean square error (RMSE) obtained by repeating each model 10 times. The second method selects the model with the lowest RMSE in all experiments. The experimental results revealed not only the improved accuracy of the deep learning model compared to the traditional time series prediction model, ARIMA, but also the contribution in enhancing the risk management ability of freight fluctuations through deep learning models. On the contrary, in the event of sudden changes in freight owing to the effects of external factors such as the Covid-19 pandemic, the accuracy of the forecasting model reduced. The GRU1 model recorded the lowest RMSE (69.55, 49.35) in both evaluation methods, and it was selected as the optimal model.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.385-391
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• 2022

In this study, a multivariate time series analysis was conducted to identify various variables that impact ocean freight rates in addition to supply and demand factors. First, we used the ClarkSea Index, Clarksons Average Bulker Earnings, and Clarksons Average Tanker Earnings provided by the Shipping Intelligence as substitute variables for the dependent variable, ocean freight. The following ndependent variables were selected: World Seaborne Trade, World Fleet, Brent Crude Oil Price, World GDP Growth Rate, Industrial Production (IP OECD) Growth Rate, Interest Rate (US$ LIBOR 6 Months), and Inflation (CP I OECD) through previous studies. The time series data comprise annual data (1992-2020), and a regression analysis was conducted. Results of the regression analysis show that the World Seaborne Trade and Brent Crude Oil P rice impacted the ClarkSea Index. Only the World Seaborne Dry Bulk Trade impacted the Clarksons Average Bulker Earnings, World Seaborne Oil Trade, Brent Crude Oil Price, IP, and CP I on the Clarksons Average Tanker Earnings.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.49
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• pp.213-236
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• 2011

Korea Shipping Act admits shipping conferences' joint actions like rate agreement, sailing agreement in some degree for development of shipping transport industries for decades. Meanwhile, EU has prohibited all kinds of shipping conferences' joint actions since October 2008, and many advanced countries also have similar position on shipping conference. The balance development between shippers and ship owners is very important in terms of national economic growth. So it is appropriate time to revise related laws such as Shipping Act and Monopoly Regulation and Fair Trade Act. First, It is direction for revision of Korean Shipping Act. The act has to define precisely the criteria of "unfairness" in case of admitting of shipping conferences' joint actions. Shipping conferences have a conference with shipper or shipper's delegation substantially on freight and transport conditions and so on. Second, It is direction for revision of Monopoly Regulation and Fair Trade Act. The fair trade commission has to perform fair roles between shippers and ship owners. The judgement of fairness has to confirm according to the spirit of not Korea Shipping Act but Korea Monopoly Regulation and Fair Trade Act itself.

• Journal of Navigation and Port Research
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• v.48 no.1
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• pp.62-77
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• 2024

In the maritime shipping industry, imbalance between supply and demand has persistently increased, leading to the utilization of blank sailings by major shipping companies worldwide as a key means of flexibly adjusting vessel capacity in response to shipping market conditions. Traditionally, blank sailings have been frequently implemented around the Chinese New Year period. However, due to unique circumstances such as the global pandemic starting in 2020 and trade tensions between the United States and China, shipping companies have recently conducted larger-scale blank sailings compared to the past. As blank sailings directly impact freight transport delays, they can have negative repercussions from perspectives of both businesses and consumers. Therefore, this study employed Poisson regression models and negative binomial regression models to analyze the influence of maritime freight rate determinants on shipping companies' decisions regarding blank sailings, aiming to proactively address potential consequences. Results of the analysis indicated that, in Poisson regression analysis for 2M, significant variables included global container shipping volume, container vessel capacity, container ship scrapping volume, container ship newbuilding index, and OECD inflation. In negative binomial regression analysis, ocean alliance showed significance with global container shipping volume and container ship order volume, the alliance with container ship capacity and interest rates, non-alliance with international oil prices, global supply chain pressure index, container ship capacity, OECD inflation, and total alliance with container ship capacity and interest rates.

• Journal of Korea Port Economic Association
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• v.39 no.2
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• pp.41-57
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• 2023

The drybulk shipping market has high freight rate volatility in the chartering market and various and complex factors affecting the market. In the unstable economic situation caused by the COVID-19 pandemic in 2020, the BDI plunged due to a decrease in trade volume, but turned from the end of 2020 and maintained a booming period until the end of 2022. The main reason for the market change is the decrease in the available fleet that can actually be operated for cargo transport due to port congestion by the COVID-19 pandemic, regardless of the fleet and trade volume volatility that have affected the drybulk shipping market in the past. A decrease in the actual usable fleet due to vessel waiting at port by congestion led to freight increase, and the freight increase in charting market led to an increase in second-hand ship and new-building ship price in long-term equilibrium relationship. In the past, the drybulk shipping market was determined by the volatility of fleet and trade volume. but, in the future, available fleet volume volatility by pandemics, environmental regulations and climate will be the important factors affecting BDI. To response to the IMO carbon emission reduction in 2023, it is expected that ship speed will be slowed down and more ships are expected to be needed to transport the same trade volume. This slowdown is expected to have an impact on drybulk shipping market, such as a increase in freight and second-hand ship and new-building ship price due to a decrease in available fleet volume.

• Journal of Digital Convergence
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• v.17 no.4
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• pp.65-73
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• 2019

This study performed Panel Regression Analysis (PRA) with the debt ratio as a dependent variable and the ROE (return on equity), sales volume, current ratio, total capital, and Shanghai Containerized Freight Index (SCFI) as an independent variable. According to the GLS analysis, the current ratio to liabilities ratio was negative, and for sales, the ratio of liabilities was positive. Capital totals also had a negative impact on the debt ratio. However, ROE, unlike the hypothesis, had negative effects on the liability ratio, and the SCFI index was not significant. As implications of this research, the company confirmed that its sales increased as the debt ratio of global shipping companies rose, achieving economies of scale. However, it was confirmed that the actual size of the economy through the injection of other capital would help increase sales but not affect net profit. Shipping companies should expand their business power and secure large container vessels to secure credibility of shippers. In the future research, an analysis considering exchange rate, global economic growth rate, and manufacturing production index is needed.