• Title/Summary/Keyword: maritime freight index

Search Result 17, Processing Time 0.023 seconds

A Study on the Productivity Changes of the Korean Container Shipping Lines using MPI (MPI를 활용한 국적 외항 컨테이너 선사의 생산성 변화 분석 연구)

  • Sung Sub, Shin;Chi Yeol, Kim;Min-Ho, Ha
    • Journal of Navigation and Port Research
    • /
    • v.46 no.6
    • /
    • pp.547-553
    • /
    • 2022
  • This study analyzed the changes in the operational productivity of fourteen Korean container lines from 2019 to 2021 using MP I(Malmquist Productivity Index). The results indicated that the operational productivity of the shipping companies has increased by 38.4% annually, representing the TCI (Technical Change Index) increasing by 58.3% and the TECI (Technical Efficiency Change Index) decreasing by 12.6%. The increase in the operational productivity of the container shipping lines was mainly attributed to the high rise in ocean freight rates rather than an increase in fleet size or ship technical efficiency. However, the deep-sea shipping lines (i.e. HMM and SM lines) experienced increases in both the TCI and TECI, which was not the case for other shipping lines(i.e. Intra-Asian short-sea shipping lines). The intra-Asian short-sea shipping lines enhance their productivity due to the TCI but failed to appreciate the cost savings of the increased fleet effects due to the low SECI(Scale Efficiency Change Index) values.

Predicting the Baltic Dry Bulk Freight Index Using an Ensemble Neural Network Model (통합적인 인공 신경망 모델을 이용한 발틱운임지수 예측)

  • SU MIAO
    • Korea Trade Review
    • /
    • v.48 no.2
    • /
    • pp.27-43
    • /
    • 2023
  • The maritime industry is playing an increasingly vital part in global economic expansion. Specifically, the Baltic Dry Index is highly correlated with global commodity prices. Hence, the importance of BDI prediction research increases. But, since the global situation has become more volatile, it has become methodologically more difficult to predict the BDI accurately. This paper proposes an integrated machine-learning strategy for accurately forecasting BDI trends. This study combines the benefits of a convolutional neural network (CNN) and long short-term memory neural network (LSTM) for research on prediction. We collected daily BDI data for over 27 years for model fitting. The research findings indicate that CNN successfully extracts BDI data features. On this basis, LSTM predicts BDI accurately. Model R2 attains 94.7 percent. Our research offers a novel, machine-learning-integrated approach to the field of shipping economic indicators research. In addition, this study provides a foundation for risk management decision-making in the fields of shipping institutions and financial investment.

Study on the Forecasting and Effecting Factor of BDI by VECM (VECM에 의한 BDI 예측과 영향요인에 관한 실증연구)

  • Lee, Sung-Yhun;Ahn, Ki-Myung
    • Journal of Navigation and Port Research
    • /
    • v.42 no.6
    • /
    • pp.546-554
    • /
    • 2018
  • The Bulk market, unlike the line market, is characterized by stiff competition where certain ship or freight owners have no influence on freight rates. However, freights are subject to macroeconomic variables and economic external shock which should be considered in determining management or chartering decisions. According to the results analyzed by use of ARIMA Inventiom model, the impact of the financial crisis was found to have a very strong bearing on the BDI index. First, according to the results of the VEC model, the libor rate affects the BDI index negatively (-) while exchange rate affects the BDI index by positively (+). Secondly, according to the results of the VEC model's J ohanson test, the order ship volume affects the BDI index by negatively (-) while China's economic growth rate affects the BDI index by positively (+). This shows that the shipping company has moved away from the simple carrier and responded appropriately to changes in macroeconomic variables (economic fluctuations, interest rates and exchange rates). It is believed that the shipping companies should be more aggressive in its "trading" management strategy in order to prevent any unfortunate situation such as the Hanjin Shipping incident.

A Study on the Early Warning Model of Crude Oil Shipping Market Using Signal Approach (신호접근법에 의한 유조선 해운시장 위기 예측 연구)

  • Bong Keun Choi;Dong-Keun Ryoo
    • Journal of Navigation and Port Research
    • /
    • v.47 no.3
    • /
    • pp.167-173
    • /
    • 2023
  • The manufacturing industry is the backbone of the Korean economy. Among them, the petrochemical industry is a strategic growth industry, which makes a profit through reexports based on eminent technology in South Korea which imports all of its crude oil. South Korea imports whole amount of crude oil, which is the raw material for many manufacturing industries, by sea transportation. Therefore, it must respond swiftly to a highly volatile tanker freight market. This study aimed to make an early warning model of crude oil shipping market using a signal approach. The crisis of crude oil shipping market is defined by BDTI. The overall leading index is made of 38 factors from macro economy, financial data, and shipping market data. Only leading correlation factors were chosen to be used for the overall leading index. The overall leading index had the highest correlation coefficient factor of 0.499 two months ago. It showed a significant correlation coefficient five months ago. The QPS value was 0.13, which was found to have high accuracy for crisis prediction. Furthermore, unlike other previous time series forecasting model studies, this study quantitatively approached the time lag between economic crisis and the crisis of the tanker ship market, providing workers and policy makers in the shipping industry with an framework for strategies that could effectively deal with the crisis.

A Study on the Ship Recycling in Northeast Asia for Sustainable Future (동북아 역내의 지속가능한 선박해체에 관한 연구)

  • Sung-Kuk Kim;Jin-Uk Lee
    • Korea Trade Review
    • /
    • v.46 no.2
    • /
    • pp.121-140
    • /
    • 2021
  • The ship recycling or scrap is a phenomenon in the process of vessels life cycle has ended in the shipping industry. Scrap are greatly affected by freight rates due to ship demands. Not only that, environmental regulation and economic scale vessel demand are processes that must exist in the shipping industry as they obtain management for existing vessels. In the past, shipbreaking yard had tried to work without protection for poverty, without poor working conditions and facilities to prevent the emission of harmful substances. However, the issue of environmental pollution has been raised the Basel and Hong Kong Convention have been adopted, and a new replacement of the ship scrap that induces serious pollution is required. In this study, 165 countries were analyzed to confirm the importance of determining the ship solution. As a result of the analysis, it was found that the Environmental Performance Index, which is a measure of environmental regulation, is the most influential factor of ship scrapped volume. The determinant of whether lower labor cost can be secured is more correlated with population than GDP per capita. The implications of the results of the regression analysis mean that if environmental regulations for ship scrap of the future are strengthened, the status of Bangladesh and Pakistan, which currently account for half of the world's ship recycling, may change.

The Effect of Baltic Dry Index on the Korean Stock Price Volatility (발틱운임지수가 한국 주가 변동성에 미치는 영향)

  • Choi, Ki-Hong;Kim, Dong-Yoon
    • Journal of Korea Port Economic Association
    • /
    • v.35 no.2
    • /
    • pp.61-76
    • /
    • 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.

The Economic Cycle and Contributing Factors to the Operating Profit Ratio of Korean Liner Shipping (경기순환과 우리나라 정기선 해운의 영업이익률 변동 요인)

  • Mok, Ick-soo;Ryoo, Dong-keun
    • Journal of Navigation and Port Research
    • /
    • v.46 no.4
    • /
    • pp.375-384
    • /
    • 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.