• Korean Journal of Human Ecology
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• v.16 no.1
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• pp.75-87
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• 2007

The purpose of this study was to classify the financial strategies in elderly households. The data of 4,577 households with all ages and 1255 elderly households is from the Korean Labor and Income Panel Study(2000, 2003). The data were analyzed by various statistical methods such as frequency, mean-test, Duncan's multiple range test, k-mean cluster analysis and logistic regression. Findings were as follows; First, the classified household financial strategy types were Residual(44.3%), Financial Assets(24.0%), Informal Institutional(19.7%), Diversified Portfolio(7.6%), Real Estate(4.5%). Second, the criteria of classification of the financial strategies were relative, not absolute. Third, households(both elderly households and all households) that employed a diversified portfolio strategy had the greatest net wealth.

• Cartoon and Animation Studies
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• s.40
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• pp.287-314
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• 2015

This study tries to analyze the portfolio of production budget related to Hollywood animation movies released during the five years between 2010 and 2014, in order to investigate how blockbuster strategy made the box office performance. The analysis shows that this animation genre invested more than one thousand million dollars as the average budget for each film. It increased threefold in the box office result. In the production of Hollywood animation genre, 72.2% of its whole production money was found to use for movies investing more than one thousand million dollars. It is to show how the production of animation aimed for profit-making via blockbuster strategy recognized as the most successful portfolio strategy in the recent Hollywood film industry.

• Journal of the Korean Data and Information Science Society
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• v.23 no.1
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• pp.151-159
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• 2012

This paper proposes to develop multi-currencies portfolio strategy using principal component analysis (PCA) and logistic regression (LR) in foreign exchange market. While there is a great deal of literature about the analysis of exchange market, there is relatively little work on developing trading strategies in foreign exchange markets. There are two objectives in this paper. The first objective is to suggest portfolio allocation method by applying PCA. The other objective is to determine market timing which is the strategy of making buy or sell decision using LR. The results of this study show that proposed model is useful trading strategy in foreign exchange market and can be desirable solution which gives lots of investors an important investment information.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.2
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• pp.73-83
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• 2014

Many recent theoretical developments in the field of machine learning and control have rapidly expanded its relevance to a wide variety of applications. In particular, a variety of portfolio optimization problems have recently been considered as a promising application domain for machine learning and control methods. In highly uncertain and stochastic environments, portfolio optimization can be formulated as optimal decision-making problems, and for these types of problems, approaches based on probabilistic machine learning and control methods are particularly pertinent. In this paper, we consider probabilistic machine learning and control based solutions to a couple of portfolio optimization problems. Simulation results show that these solutions work well when applied to real financial market data.

• Industrial Engineering and Management Systems
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• v.16 no.1
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• pp.118-128
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• 2017

Uncertain factors in finical markets make the prediction of future returns and risk of asset much difficult. In this paper, a model,assuming the admissible errors on expected returns and risks of assets, assisted in the multiperiod mean variance portfolio selection problem is built. The model considers transaction costs, upper bound on borrowing risk-free asset constraints, cardinality constraints and threshold constraints. Cardinality constraints limit the number of assets to be held in an efficient portfolio. At the same time, threshold constraints limit the amount of capital to be invested in each stock and prevent very small investments in any stock. Because of these limitations, the proposed model is a mix integer dynamic optimization problem with path dependence. The forward dynamic programming method is designed to obtain the optimal portfolio strategy. Finally, to evaluate the model, our result of a meaning example is compared to the terminal wealth under different constraints.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.19 no.4
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• pp.417-428
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• 2015

Although, in general, the random fluctuation of interest rates gives a limited impact on portfolio optimization, their stochastic nature may exert a significant influence on the process of selecting the proportions of various assets to be held in a given portfolio when the stochastic volatility of risky assets is considered. The stochastic volatility covers a variety of known models to fit in with diverse economic environments. In this paper, an optimal strategy for portfolio selection as well as the smoothness properties of the relevant value function are studied with the dynamic programming method under a market model of both stochastic volatility and stochastic interest rates.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.878-884
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• 2012

This study presents a portfolio selection strategy focusing on construction corporations by taking into accounts managerial efficiency and growth potential of a company. Data envelopment analysis(DEA) methodology and dividend scoring table are adopted for evaluating the managerial efficiency and growth potential of a company respectively. In order to show the effectiveness of the portfolios selected by the strategies proposed in this study, we constructed 3 portfolios for every 4 years (2007-2010) out of 56 listed construction corporations in KOSPI and KOSDAQ, and proved that our portfolios are superior to benchmark portfolios in terms of portfolio evaluation measures.

• The Journal of the Korea Contents Association
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• v.19 no.6
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• pp.204-213
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• 2019

This study examines the ePortfolio structure of IT company design interns and the differences among companies in 'Cofolios' site for employment of design major students. First, we examine the common configuration steps of ePortfolios [1. Project Brief${\rightarrow}$2-1. Investigation and Analysis${\rightarrow}$2-2. Strategy development${\rightarrow}$2-3. Virtualization, Final Design${\rightarrow}$2-4. Presentation, Evaluation, and Improvement${\rightarrow}$3. Read More]. Secondly, all the sub-items used in the ePortfolio were organized into words and classified into 6 stages. Finally, this was analyzed by majors and companies. Through this, the interns of the IT companies can [2-2. Strategy development] and that they are actively utilizing the 'connectivity' attribute linking the links. In addition, interns confirmed that the ePortfolio was structured differently depending on their major and the desired company.

• Journal of Information Processing Systems
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• v.18 no.5
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• pp.637-649
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• 2022

Investors aim to increase their profitability by investing in the stock market. An adroit strategy for minimizing related risk lies through diversifying portfolio operationalization. In this paper, we propose a six-step stocks portfolio selection model. This model is based on data mining clustering techniques that reflect the ensuing impact of the political, economic, legal, and corporate governance in Mongolia. As a dataset, we have selected stock exchange trading price, financial statements, and operational reports of top-20 highly capitalized stocks that were traded at the Mongolian Stock Exchange from 2013 to 2017. In order to cluster the stock returns and risks, we have used k-means clustering techniques. We have combined both k-means clustering with Markowitz's portfolio theory to create an optimal and efficient portfolio. We constructed an efficient frontier, creating 15 portfolios, and computed the weight of stocks in each portfolio. From these portfolio options, the investor is given a choice to choose any one option.

• 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).