• Journal of Navigation and Port Research
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• v.43 no.1
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• pp.72-78
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• 2019

The second-hand ship market provides immediate access to the freight market for shipping investors. When introducing second-hand vessels, the precise estimate of the price is crucial to the decision-making process because it directly affects the burden of capital cost to investors in the future. Previous studies on the second-hand market have mainly focused on the market efficiency. The number of papers on the estimation of second-hand vessel values is very limited. This study proposes an artificial neural network model that has not been attempted in previous studies. Six factors, freight, new-building price, orderbook, scrap price, age and vessel size, that affect the second-hand ship price were identified through literature review. The employed data is 366 real trading records of Panamax second-hand vessels reported to Clarkson between January 2016 and December 2018. Statistical filtering was carried out through correlation analysis and stepwise regression analysis, and three parameters, which are freight, age and size, were selected. Ten-fold cross validation was used to estimate the hyper-parameters of the artificial neural network model. The result of this study confirmed that the performance of the artificial neural network model is better than that of simple stepwise regression analysis. The application of the statistical verification process and artificial neural network model differentiates this paper from others. In addition, it is expected that a scientific model that satisfies both statistical rationality and accuracy of the results will make a contribution to real-life practices.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2020.11a
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• pp.108-110
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• 2020

본 연구의 목적은 딥러닝 기법의 하나인 인공신경망 모델을 활용하여 선박의 가치평가 모델을 개발하는 것이다. 선박의 가치는 해운시장 변화와 밀접한 관계가 있으며, 경기 변동성이 크고 시장 민감성이 높은 해운시장의 특성상 가치의 불확실성 역시 높게 나타나고 있다. 이러한 선박가치의 중요성에도 불구하고 국내외적으로 선박가치평가의 체계 개선 및 평가모델의 객관성과 신뢰성을 제고시키기 위한 연구는 부족한 실정이다. 따라서 본 연구에서는 딥러닝 방법을 통해 선박의 가치를 산출하는 새로운 평가모델을 제시하고자 한다. 가치평가의 대상은 중고 VLCC선이며, 선행연구를 통해 선박의 가치 변화를 유발하는 주요 요인들을 선별하여 변수를 설정하고 2010년 1월부터 현재까지의 해당 데이터를 확보하였다. 교차검증을 통해 파라미터들을 추정하여 인공신경망의 최적 구조를 식별하고 이에 대한 객관성과 신뢰성을 검증한 결과 인공신경망 모델의 가치평가 정확성이 우수함을 확인하였다. 본 연구는 선박가치평가의 전통적 방법론에서 탈피하여 기계학습 기반의 딥러닝 모델을 활용한 측면에서 독창적인 의미가 있다.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2001.05a
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• pp.43-48
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• 2001

Price of Used Vessel is Key-point of Ship trading but it is very troublesome part. Because it is different from the Seller and the Buyer's caculated price, It is appropriated by The Sellers and The Buyers' mutual agreement. In case of the Buyers. it is difficult in calculating price of used ship without entrusting the ship broker, beca- use evaluation method of secondhanded vessel has not formulated and the ship broker has experientially computed Remain Value of used vessel. For this work, structure of ship trading market, trading flow, the factor of price composition and Affecting factor of price is reviewed, and it examined relationship with price. On these base, a computer software integrated database system and object-oriented technique is developed. The developed system is expected helpful to evaluation of remain value of the used vessel.

• Journal of Korea Port Economic Association
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• v.31 no.2
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• pp.55-67
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• 2015

This study analyzes the relationship between shipping profit and market return in the tramp trade from January 2000 to October 2014. First, we carry out the causality test and find a causal relationship between the studied variables. Second, the estimates from the Johansen cointegration test show that shipping profit is cointegrated with market return, which implies that a long-run relationship exists among the variables. The empirical results thus imply that shipping firms need diverse risk management strategies.

• Journal of Navigation and Port Research
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• v.37 no.1
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• pp.113-121
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• 2013

IMO(International Maritime Organization) is existed the movement for revising ISM Code so that the maintenance history and the trouble information given trading in a ship can be transferred. An empirical analysis was made on the influence that will have upon shipping industry through surveying on the recognition on ISM Code revision in employees of the relevant field and on the expected problems given being amended ISM Code as the above. In conclusion, the positive effect is judged to be more in the aspect of ship safety, which is the aim of ISM Code, rather than the negative effect, which may take place given being revised ISM Code. In other words, the clean market can be formed through this because fairness is maintained on both sides given trading in a ship by which opening the maintenance record and the trouble history is applied equally to a buyer and a seller. Ships can be reduced a loss of time and cost in preventing similar problems and seeking solution that may appear in important equipments, through this maintenance record. Also, based on these materials, it comes to be available for analyzing a risk of ship and preventing and managing a risk, thereby being increased ability of maintenance and repair in a ship, resulting in being judged to likely contributing to ship safety and environmental-pollution prevention.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.13-21
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• 2021

The purpose of this study is to develop the ship valuation model by utilizing the neural network model. The target of the valuation was secondhand VLCC. The variables were set as major factors inducing changes in the value of ship through prior research, and the corresponding data were collected on a monthly basis from January 2000 to August 2020. To determine the stability of subsequent variables, a multi-collinearity test was carried out and finally the research structure was designed by selecting six independent variables and one dependent variable. Based on this structure, a total of nine simulation models were designed using linear regression, neural network regression, and random forest algorithm. In addition, the accuracy of the evaluation results are improved through comparative verification between each model. As a result of the evaluation, it was found that the most accurate when the neural network regression model, which consist of a hidden layer composed of two layers, was simulated through comparison with actual VLCC values. The possible implications of this study first, creative research in terms of applying neural network model to ship valuation; this deviates from the existing formalized evaluation techniques. Second, the objectivity of research results was enhanced from a dynamic perspective by analyzing and predicting the factors of changes in the shipping. market.

• Journal of Digital Convergence
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• v.14 no.7
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• pp.145-154
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• 2016

The purpose of this study was to carry out comparative analysis on the world major liner shipping companies' ship investment strategy using Fuzzy-AHP model. In this study, the ship investment factors were firstly selected by literature review and finally adopted them by in-depth interview with experts who had working experiences over 15 years in the field of shipping business. As suggested in the previous research, the liner shipping companies have been classified into four types such as 'ship investment irrelevant to market trend'(Type1), 'ship investment before market rise'(Type2), 'market decline after participation in excessive orders'(Type3), 'avoidance of ship investment during market rise'(Type4) and the comparative analysis were conducted among four ship investment types. According to the results of analysis, ship investment priority in Type1 was freight rates(0.132), price of used ship(0.121) and fleet(0.103). The priority in Type2 was freight rates(0.134), need for ship owner(0.113) and public funding(0.109). Type3 put its priority in freight rates(0.173), fleet(0.169) and the changes in international circumstances(0.121). Type4 considered freight rates(0.239), fleet(0.232) and oil price(0.150) as its priority.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2013.06a
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• pp.163-165
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• 2013

IMO(International Maritime Organization) is existed the movement for revising ISM Code so that the maintenance history and the trouble information given trading in a ship can be transferred. An empirical analysis was made on the influence that will have upon shipping industry through surveying on the recognition on ISM Code revision in employees of the relevant field and on the expected problems given being amended ISM Code as the above. In conclusion, the positive effect is judged to be more in the aspect of ship safety, which is the aim of ISM Code, rather than the negative effect, which may take place given being revised ISM Code. In other words, the clean market can be formed through this because fairness is maintained on both sides given trading in a ship by which opening the maintenance record and the trouble history is applied equally to a buyer and a seller. Ships can be reduced a loss of time and cost in preventing similar problems and seeking solution that may appear in important equipments, through this maintenance record. Also, based on these materials, it comes to be available for analyzing a risk of ship and preventing and managing a risk, thereby being increased ability of maintenance and repair in a ship, resulting in being judged to likely contributing to ship safety and environmental-pollution prevention.

• 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.