• Journal of Navigation and Port Research
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• v.46 no.5
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• pp.441-448
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• 2022

The aim of this study was to examine determinants of secondhand Bulk carrier and Oil tanker prices. This study compiled S& P transaction data taken from the Clarksons Research during J anuary 2018 to April 2022 to see how independent variables influenced secondhand ship prices. In the secondhand ship pricing model of entire segments, size, age, and LIBOR showed significant effects on prices. A vessel built in J apan and Korea was traded at a higher price than a vessel built in other countries. In the bulk segment, size, age, Clarksea index, LIBOR, and inflation were meaningful variables. In the Tanker segment, unlike Bulk carrier, only size and age were useful variables. This study performed regression analyses for various sizes of Bulk carriers and Oil tankers. It verified that impacts of variables other than ship size and age were significantly associated with ship type and size while macroeconomic variables had no influence except for bulk carriers. By applying diverse variables affecting secondhand ship price estimation according to various sizes of Bulk carriers and Oil tankers, this study will expand the scope of practical application for investors. It also reaffirms prior research findings that the secondhand ship market is primarily market-driven.

• The Journal of shipping and logistics
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• v.27 no.4
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• pp.719-746
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• 2011

This study attempted to analyse the results of investments from each individual ship investment company(SIC) in Korea which is operating under its ship investment company system. We analyzed investment result of ship investment company by means of Market Adjusted Return Method for measurement of abnormal return(AR) and cumulative abnormal return(CAR). Some implications from the results of this study are suggested. First, we find that the initial abnormal return of IPO, 30-day CAR and long-term CAR are not significantly different between A and B shipping fund management company. And then, the initial abnormal return of IPO and long-term CAR are not significantly different between newbuilding and secondhand ship SIC. But the 30-day CAR is significantly different between newbuilding and secondhand vessel SIC. Third, the 30-day CAR and long-term CAR are not significantly different between newbuilding and secondhand vessel SIC. But the 30-day AR is not significantly different between container and non-container ship SIC. Finally, newbuilding ship SCI is more stable than secondhand vessel SIC, and container ship SIC is more stable than non-container ship SIC in 3-month cumulative return over the past two and half years, from February 2008 to July 2011.

• 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 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.