• Journal of Korea Port Economic Association
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• v.38 no.3
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• pp.87-104
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• 2022

Considering the complex structure and high volatility in the shipping market, it is important to investigate the connectedness amongst influencing factors. This study explores the dynamic relationship between supply-demand factors and shipping freight indices. We choose Capesize and Panamax in the bulk carrier market and use quarterly data of GDP, world fleet, BCI, and BPI from 1999 to 2021. Applying the wavelet analysis and wavelet Granger causality test, the simultaneous examination of co-movement and causality between two factors and the shipping market in both the time and frequency domains is achieved. We find that co-movement and causality vary across time and frequencies, thereby existing dynamic relationships between variables. Second, compared to multiple coherencies using demand and supply factors together, partial coherencies indicate noticeable causalities. It implies that analyzing demand and supply factors separately is essential. Finally, shipping freight indices show a high correlation with the demand factor in a good market and with the supply factor in a bad market. Generally, GDP positively leads shipping freights in the recovery phase while the world fleet negatively leads shipping freights in the downturn. The research is meaningful in that the rarely-applied wavelet analysis is adopted in the shipping market and that it gives a reasonable ground to explain the role of supply and/or demand factors in different phases of the market cycle.

• Journal of Korea Port Economic Association
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• v.35 no.2
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• pp.61-76
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• 2019

The purpose of this study is to use the EGARCH model and Granger causality test to analyze how the change in the BDI affects the Korean stock price volatility. The main analysis results are summarized as follows. First, according to the results of the mean equation, the change in the BDI is significant in large-cap stocks, as well as in the manufacturing, service, and chemistry indexes, but not in others. This implies that the Korean stock market does not respond appropriately to the maritime market situation; further, the increase in demand for raw materials has not led to a real economic recovery. Second, in the result of the variance equation, the coefficient on the change in the BDI is negative(-), and the change in the BDI is significant for all size indexes. Particularly, the change in the BDI has a greater impact on the volatility of small-cap stocks than that of large-cap stocks. The results of the analysis of the sector indexes were statistically significant for the service, financial, construction, and electric and electronics industries, but not for the manufacturing and chemical industries. In particular, the changes in the BDI have the greatest impact on the construction industry. Third, according to the Granger causality test results, the change in the BDI leads the financial industry and construction industry. There is, however, no relationship between the BDI and the other indexes. This shows that change in the shipping freight index can be used to predict the volatility in the Korean stock market. This can help investors and policymakers make better decisions.

• 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.28 no.4
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• pp.79-98
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• 2012

There is scant of research regarding the efficiency measurement of the ship management business. This paper aims to analyze the relative efficiency within the Korean Major Ship management corporations, to select the relatively low effective companies, and to suggest the improvement strategies for those. As a research methodology, Data Envelopment Analysis (DEA) applied to the top 20 corporations among Korean and Foreign Shipping Liners in Korea. To draw out the efficiency of targeted terminals, the number of ship managed is used as an input variables while, the number of crews and the total sales are utilized as an output variables. As a result. Haeyoung Maritime services is the most efficient corporations in Foreign Shipping Liners. Among Korean Shipping Liners, Panstar Shipping, Korea Lines, STX marine and Woolim Shipping are relatively efficient corporations which are scored BCC 1.

• Journal of Korea Port Economic Association
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• v.29 no.1
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• pp.67-76
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• 2013

It has been more than four years since the outbreak of global financial crisis. However, the world economy continues to be challenged with new crisis such as the European debt crisis and the fiscal cliff issue of the U.S. The global economic environment remains fragile and prone to further disappointment, although the balance of risks is now less skewed to the downside than it has been in recent years. It's no wonder that maritime business will be bearish since the global business affects the maritime business directly as well as indirectly. This paper, hence, aims to predict the Baltic Dry Index representing the shipping business using the ARIMA-type models and Hodrick-Prescott filtering technique. The monthly data cover the period January 2000 through January 2013. The out-of-sample forecasting performance is measured by three summary statistics: root mean squared percent error, mean absolute percent error and mean percent error. These forecasting performances are also compared with those of the random walk model. This study shows that the ARIMA models including Intervention-ARIMA have lower rmse than random walk model. This means that it's appropriate to forecast BDI using the ARIMA models. This paper predicts that the shipping market will be more bearish in 2013 than the year 2012. These pessimistic ex-ante forecasts are supported by the Hodrick-Prescott filtering technique.

• 해운
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• s.103
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• pp.8-21
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• 2013

발주잔량의 감소와 세계경기 회복기조 등을 감안할 때, 수급여건은 저점에 근접해 있다. 그러나, 해상물동량 증가율의 둔화, 대형선박 위주로 되살아난 발주 등을 감안할 때, 운임지수 등 시황회복은 상대적으로 느리게 진행될 전망이다. 2012년부터 상위선사의 뚜렷한 실적차별화가 나타나고 있으며, 국내선사는 상대적으로 취약한 선종다각화와 자본력, 계열 및 정부의 저조한 지원 등으로 금융위기 이후 재무구조가 가장 큰 폭으로 악화되었다. 상위선사의 실적우위는 일시적 차이가 아닌 선박의 대형화와 높은 연료효율성, 우수한 글로벌 네트워크 등 구조적 원가경쟁력의 차이에 기인하고 있다. 상위 3개 선사는 초대형선박의 추가인수와 P3 Network 구축으로 원가경쟁력이 더욱 향상될 전망이며, 재무여력을 갖춘 경쟁선사들도 선박가격이 낮은 상황에서 고효율의 대형선박을 발주, 원가경쟁력을 제고하고 있다. 반면에 호황기 고가에 선박을 확보한 국내선사는 과중한 재무부담으로 인해 선박대형화와 글로벌 네트워크 구축에 동침하지 못하고 있어 원가경쟁력의 차이는 더욱 심화될 전망이다. 더딘 시황회복과 상위선사의 단위당 운송비(Unit Cost) 하락 등을 감안할 때, 빠른 시일 내에 운임상승을 통한 큰 폭의 성과개선을 기대하기 어렵고, 과중한 재무부담은 투자여력의 위축으로 이어지고 있다. 여기에 중국 유럽선사가 정부로부터 대규모의 직접적 지원(대출, 지급보증)을 제공받고 있는데 반하여, 우리 정부는 장기적 관점의 지원이나 대책을 유보한 채, 제한된 유동성 지원만을 하고 있다. 재무부담에 따른 악순환을 깨고 원가경쟁력을 확보하기 위해선, 비핵심자산 매각, 자본유치 등 구조조정을 통한 재무구조 개선, 투자여력 확보를 통한 글로벌 경쟁력 회복, 정부차원의 지원과 조정 등 가능한 모든 방안을 총 동원하여 재무구조를 개선하고 투지에 나서는 것이 시급하다. 하지만, 불황으로 체력이 소진된 해운사의 자체적인 노력만으로는 한계가 있다. 기간산업의 국가경쟁력 차원에서 국내 선사의 자체노력은 물론, 정부 또는 금융기관 등 유관기관들의 확실한 지원이나 의사결정이 필요한 시점이다. 그렇지 않을 경우 국내 해운산업은 어두운 터널의 끝을 벗어나지 못하고 글로벌 경쟁사와의 격차는 더욱 벌어지게 될 것이다. 다음은 한국신용평가에서 발표한 "풍전등화 국내 해운업계, 본원적 대책 마련 시급"의 주요 내용을 요약 정리한 것이다.

• Korea Trade Review
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• v.44 no.2
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• pp.127-141
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• 2019

In this study, the relationship between Baltic Dry Index(BDI) and maritime trade volume in the dry cargo market was verified using the vector autoregressive (VAR) model. Data was analyzed from 1992 to 2018 for iron ore, steam coal, coking coal, grain, and minor bulks of maritime trade volume and BDI. Granger causality analysis showed that the BDI affects the trade volume of coking coal and minor bulks but the trade volume of iron ore, steam coal and grain do not correlate with the BDI freight index. Impulse response analysis showed that the shock of BDI had the greatest impact on coking coal at the two years lag and the impact was negligible at the ten years lag. In addition, the shock of BDI on minor cargoes was strongest at the three years lag, and were negligible at the ten years lag. This study examined the relationship between maritime trade volume and BDI in the dry bulk shipping market in which uncertainty is high. As a result of this study, there is an economic aspect of sustainability that has helped the risk management of shipping companies. In addition, it is significant from an academic point of view that the long-term relationship between the two time series was analyzed through the causality test between variables. However, it is necessary to develop a forecasting model that will help decision makers in maritime markets using more sophisticated methods such as the Bayesian VAR model.

• Journal of Korea Port Economic Association
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• v.39 no.1
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• pp.115-129
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• 2023

This study analyzed the risk spillover of BDI on shipping company stock prices through the Copula-CoVaR method based on daily data from January 4, 2010, to October 31, 2022. The main empirical analysis results and policy implications are as follows. First, copula results showed that there was a weak dependence between BDI and shipping company stock prices, and PAN, KOR, and YEN were selected as the most fitting model for dynamic Student-t copula, HMM was selected as the rotated Gumbel copula, and KSS was selected as the best model. Second, in the results of CoVaR, it was confirmed that the upside (downside) CoVaR was significantly different from the upside (downside) VaR in all shipping companies. This means that BDI has a significant risk spillover on shipping companies. In addition, as for the risk spillover, the downside risk is generally lower than the upside risk, so the downside and upside risk spillover were found to be asymmetrical. Therefore, policymakers should strengthen external risk supervision and establish differentiated policies suitable for domestic conditions to prevent systematic risks from BDI shocks. And investors should reflect external risks from BDI fluctuations in their investment decisions and construct optimal investment portfolios to avoid risks. On the other hand, investors propose that the investment portfolio should be adjusted in consideration of the asymmetric characteristics of up and down risks when making investment decisions.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.375-384
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• 2022

The shipping industry is cyclically impacted by complex variables such as various economic indicators, social events, and supply and demand. The purpose of this study was to analyze the operating profit of 13 Korean liner companies over 30 years, including the financial crisis of the late 1990s, the global financial crisis of the late 2000s, and the COVID-19 global pandemic. This study was conducted to also identify factors that impacted the profit ratio of Korea's liner shipping companies according to economic conditions. It was divided into ocean-going and short-sea shipping, reflecting the characteristics of liner shipping companies, and was analyzed by hierarchical multiple regression analysis. The time series data are based on the Korean International Financial Reporting Standards (K-IFRS) and comprise seaborne trade volume, fleet evolution, and macroeconomic indicators. The outliers representing the economic downturn due to social events were separately analyzed. As a result of the analysis, the China Container Freight Index (CCFI) positively impacted ocean-going as well as short-sea liner shipping companies. However, the Korean container shipping volume only impacted ocean-going liners positively. Additionally, world and Korea's GDP, world seaborne trade volume, and fuel price are factored in the operating profit of short sea liner shipping. Also, the GDP growth rate of China, exchange rate, and interest rate did not significantly impact both groups. Notably, the operating profitability of Korea's liner shipping shows an exceptionally high rate during the recessions of 1998 and 2020. It is paradoxical, and not correlated with the classical economic indicators. Unlike other studies, this paper focused on the operating profit before financial expenses, considering the complexity as well as difficulty in forecasting the shipping cycle, and rendered conclusions using relatively long-term empirical analysis, including three economic shocks.