• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2013.06a
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• pp.301-303
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• 2013

IMO는 선박의 안전항해와 해양환경보호를 위해 e-Navigation의 개념을 채택하였고 이를 위한 구체적인 전략이행계획(SIP, Strategic Implementation Plan)작업을 수행하고 있다. IALA는 IMO의 NAV의 e-Navigation 실행계획을 완성하기 위해 7개의 작업반(WG)을 운용하고 있다. e-Navigation의 개념을 구현하기 위해서는 첨단 IT 전자장비의 개발도 필요하지만 이러한 장비를 이용하여 항해안전을 향상시킬 수 있는 다양한 IT 서비스, 즉 MSP(Maritime Service Portfolio)가 필요하다. 모든 선박에서 MSP을 이용하기 위하여서는 MSP의 구조와 데이터가 표준화되어야 한다. 또한 항해안전에 효과적인가를 검증할 수 있는 방법이 제시되어야 하며, MSP가 남용되지 않도록 관리되어야 한다. 본 연구에서는 선박의 사고사례와 기존 항해통신시스템과 e-Navigation SIP의 갭 목록, 갭 분석 및 갭 해결책을 활용하여 선박의 안전과 보안에 입각한 MSP 구조에 대해서 고찰해 본다.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.2_2
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• pp.467-473
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• 2024

Metaheuristics' impact is profound across many fields, yet domestic financial portfolio optimization research falls short, particularly in asset allocation. This study delves into metaheuristics for portfolio optimization, examining theoretical and practical benefits. Findings indicate portfolios optimized via metaheuristics outperform the Dow Jones Index in Sharpe ratios, underscoring their potential to enhance risk-adjusted returns significantly. Tabu search, in comparison to Simulated Annealing, demonstrates superior performance by efficiently navigating the search space. Despite these advancements, practical application remains challenging due to the complexities in metaheuristic implementation. The study advocates for broader algorithmic exploration, including population-based metaheuristics, to refine asset allocation strategies further. This research marks a step towards optimizing portfolios from an extensive array of financial assets, aiming for maximum efficacy in investment outcomes.

• Management & Information Systems Review
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• v.28 no.1
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• pp.25-44
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• 2009

This study examines long term performance of initial public offerings(IPO) after book building was introduced in KOSDAQ market. We use event time portfolio approach and calendar time portfolio approach to test if the performance of IPO is fair or not in long term. We estimate the performance by using the BHAR(buy and hold abnormal return), CAR(cumulative abnormal return), WR(wealth relatives) model in event time portfolio approach. And we calculate the performance by using Fama-French three factor model, CTAR(calendar time abnormal return), RATS(Return Across Time and Securities approach) model in calendar time portfolio approach. This study shows that the long term performance of IPO is positive with statistical significance as the results of the analysis through the various research method and all windows in all kinds of firms and total firms.

• The Journal of the Korea Contents Association
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• v.11 no.2
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• pp.495-506
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• 2011

Portfolio has recently come to gain more attention from school as an alternative evaluation tool and a self-reflective learning tool for learning. After literature reviews about the case studies on the use of portfolio in higher education including both universities in Korea and abroad, this study attempted, first, to analyze the current e-portfolio system running in Kyung Hee University for the undergraduate students starting from the spring semester, 2010, and then, suggested the ways the system can be more actively utilized among the students, and simultaneously, acquiring more interest and participation from both the faculty members and the school administrators. The data collected from the survey and reflective journals of the students suggested 1) more user-friendly, easy-to-edit version of the system, 2) more diverse modes and functions of the system which, therefore, are able to adjust well to the specific and unique features of subjects or majors of the students, and 3) collaborative learning environments among the students and between the students and the faculty members from which students can share, participate, interact with each other, getting useful feedback from those co-learners and faculty members. Eventually the study aimed to enhance the recognition of the participants about the importance of portfolio as a learning tool for self-reflective learning and authentic evaluation of the students.

• Journal of Korea Technology Innovation Society
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• v.14 no.2
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• pp.279-300
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• 2011

Given the huge increase in interest in biotechnology, whose applications are being expanded as a new growth engine, investment and agency participation are also increasing. In 2008, the level of investment by the national R&D programs in future emerging technologies (6T) in the field of biotechnology was as great as that in IT, and six agencies and many relevant research institutes are now carrying out various related projects. This paper intends to review the status of investment in biotechnology by analyzing the portfolio and positioning of the national R&D biotechnology programs, which address global issues such as the quality of life, the aging society, and environment and energy, and to propose a new investment strategy and direction for the efficient implementation of the national R&D programs.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.1
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• pp.23-30
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• 2019

As deep learning with the network-based algorithms evolve, artificial intelligence is rapidly growing around the world. Among them, finance is expected to be the field where artificial intelligence is most used, and many studies have been done recently. The existing financial strategy using deep-run is vulnerable to volatility because it focuses on stock price forecasts for a single stock. Therefore, this study proposes to construct ETF products constructed through portfolio methods by calculating the stocks constituting funds by using deep learning. We analyze the performance of the proposed model in the KOSPI 100 index. Experimental results showed that the proposed model showed improved results in terms of returns or volatility.

• The Journal of Industrial Distribution & Business
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• v.13 no.1
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• pp.23-32
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• 2022

Purpose: This study used ESG grade, but defined AESG, adjusted to the size of a company and examines whether it can be used as an investment strategy. Research design, data and methodology: The analysis sample in this study is a company that has given an ESG rating among companies listed on the Korea Stock Exchange. We examine the results through portfolio analysis and Fama-macbeth regression analysis. Results: As result of examining the long-only performance and the long-short performance by constructing quintile portfolios, it was observed that a significant positive return was shown. It was observed that there was an alpha that could not be explained in asset pricing models. Also, AESG had a return prediction effect in the result of a Fama-Macbeth regression that controlled corporate characteristic variables in individual stocks. Next, we confirmed AESG's usage through various portfolio composition. In the portfolio optimization, the Risk Efficient method was the most superior in terms of sharpe ratio and the construct multi-factor model with Value, Momentum and Low Vol showed statistically significant performance improvement. Conclusions: The results of this study suggest that it can be helpful in ESG investment to reflect the ESG rating of relatively small companies more through the scale adjustment of the ESG rating (i.e.AESG).

• Journal of Korean Society for Quality Management
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• v.51 no.4
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• pp.573-588
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• 2023

Purpose: This study presents a research approach that utilizes deep reinforcement learning to construct optimal portfolios based on the business cycle for stocks and other assets. The objective is to develop effective investment strategies that adapt to the varying returns of assets in accordance with the business cycle. Methods: In this study, a diverse set of time series data, including stocks, is collected and utilized to train a deep reinforcement learning model. The proposed approach optimizes asset allocation based on the business cycle, particularly by gathering data for different states such as prosperity, recession, depression, and recovery and constructing portfolios optimized for each phase. Results: Experimental results confirm the effectiveness of the proposed deep reinforcement learning-based approach in constructing optimal portfolios tailored to the business cycle. The utility of optimizing portfolio investment strategies for each phase of the business cycle is demonstrated. Conclusion: This paper contributes to the construction of optimal portfolios based on the business cycle using a deep reinforcement learning approach, providing investors with effective investment strategies that simultaneously seek stability and profitability. As a result, investors can adopt stable and profitable investment strategies that adapt to business cycle volatility.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.447-448
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• 2022

Studies on autonomous ships has received a lot of attention, recently. However, a study on autonomous navigation assistance service for Navigation Assistance Service(NAS) which is second item of Maritime Service Portfolio(MSP) suggested by IMO was not studied. Therefore, in this paper, we derive information items for autonomous navigation assistance service and research on a display system for displaying the items.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2014.10a
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• pp.699-711
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• 2014