• Journal of The Korean Association For Science Education
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• v.21 no.1
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• pp.22-29
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• 2001

The purpose of this study is to investigate the effects of lessons adopting portfolio assessment regarding feedback on elementary school student's scientific knowledges, inquiry abilities and their perceptions of it. For this study, two classes of 5th grade elementary school in suburb were selected. As an experimental group, one class was selected to apply the lessons adopting portfolio assessment regarding feedback, and the other class as a control group was selected to apply the lessons adopting portfolio assessment without feedback. The investigator taught and assessed both group students. The results showed a significant difference in scientific knowledge between the experimental group and the control group (p<.05). More detailed analysis of scientific knowledge found that the feedback effect was statistically positive in the memory and the understanding domain, but there was no effect in the application domain. No statistical difference was identified in inquiry abilities. The results of the questionnaire on the perceptions of portfolio assessment showed that students of the experimental group had higher positive responses on the 'perception about the effects of lesson' and on the 'perception in scientific attitudes' than the control group. However, the control group students had higher positive responses on the 'perception about self-evaluate of their own portfolio' and the 'perception about need of feedback' than the experimental group.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.210-212
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• 2015

The growth-share matrix is a portfolio planning tool developed by the Boston Consulting Group (BCG) to assist competitive positioning in the international market including those in the construction industry. This matrix is helpful in balancing the firm's cash-flow, and it can suggest strategic directions for each business unit. However, its effectiveness and applicability have long been debated in the academic field due to the complex and unique industrial context of construction. To solve the dispute, this research clarifies the applicability of theories underlying the growth-share matrix to the construction industry. Empirical research based on actual financial data of Korean construction firms is adopted for the statistical analysis including one-way analysis of variance and correlation analysis. The results of this research show that empirical findings on the relationship between performance variables. In this context, this research can provide important insights on the concept of portfolio management in the construction industry.

• Journal of the Korean association of regional geographers
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• v.16 no.1
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• pp.48-58
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• 2010

Currently, understanding the characters of Rural Industrial Parks' regional distribution is insufficient. Therefore, regional characters of the Rural Industrial Parks all over the country were studied through indications such as sales, worker-sales increase rate, worker increase rates. Portfolio analysis and IDW by using ArcView 3.2 were used as a method of analysis. As a result, most of the Rural Industrial Parks' size and size increase rate showed low figures. Respective regional analysis shows that there is an increase in the scale of the Kyungnam area using portfolio analysis, whereas the scale of Chonbuk is high using IDW. As a result, it shows that there is difference on the scale between Rural Industrial Parks when individual or Associated with peripheral. Therefore, not only do the Rural Industrial Parks need stimulation individually, but adjacent parks need to be supported and managed.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2017.11a
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• pp.129-129
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• 2017

In planning and evaluating government R&D programs, one of the first steps is to understand the government's current R&D investment portfolio - which fields or topics the government is now investing in in R&D. Analysis methods of an investment portfolio of government R&D tend traditionally to rely on keyword searches or ad-hoc two-dimensional classifications. The main drawback of these approaches is their limited ability to account for the characteristics of the whole government investment in R&D and the role of individual R&D program in it, which tends to depend on the relationship with other programs. This paper suggests a new method for mapping and analyzing government investment in R&D using a combination of methods from natural language processing (NLP) and network analysis. The NLP enables us to build a network of government R&D programs whose links are defined as similarity in R&D topics. Then methods from network analysis show the characteristics of government investment in R&D, including major investment fields, unexplored topics, and key R&D programs which play a role like a hub or a bridge in the network of R&D programs, which are difficult to be identified by conventional methods. These insights can be utilized in planning a new R&D program, in reviewing its proposal, or in evaluating the performance of R&D programs. The utilized (filtered) Korean text corpus consists of hundreds of R&D program descriptions in the budget requests for fiscal year 2017 submitted by government departments to the Korean Ministry of Strategy and Finance.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1449-1466
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• 2014

In this paper, we consider a hedge portfolio based on futures of underlying asset. A classical way to estimate a hedge ratio for a hedge portfolio of a spot and futures is a regression analysis. However, a regression analysis is not capable of reflecting long-run equilibrium between a spot and futures and volatility clustering in the conditional variance of financial time series. In order to overcome such defects, we analyzed KOSPI200 index and futures using VECM-CC-GARCH model and computed a hedge ratio from the estimated conditional covariance-variance matrix. In real data analysis, we compared a regression and VECM-CC-GARCH models in terms of hedge effectiveness based on variance, value at risk and expected shortfall of log-returns of hedge portfolio. The empirical results show that the multivariate GARCH models significantly outperform a regression analysis and improve hedging effectiveness in the period of high volatility.

• Management & Information Systems Review
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• v.37 no.1
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• pp.41-53
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• 2018

This study validates the trading rules based market anomalies and technical analysis in the Korean stock market. For the analysis, we built decile portfolios on the basis of corporate characteristics factors that clearly demonstrate specific patterns of stock returns including the firm size, book-to-market equity, and accruals. This portfolio was used to develop a portfolio based on the moving average trading strategy which was used for popular technical analysis tools, and then that was evaluated using the Sharpe ratio. We also created a zero-cost portfolio to identify the profitability and success rate of the moving average trading strategy. We lastly sought to ensure a more robust evaluation by calculating the Sortino ratio of the portfolio based on the moving average trading strategy with various lags. Key findings from this validation are as follows. First, a smaller firm size, a higher book-to-market equity, and lower accruals led to larger average returns. Second, the risk-adjusted performance of the moving average trading strategy was the highest in terms of the firm size, followed by book-to-market equity and accruals. Third, the returns of the zero-cost portfolios all had a positive value, with its overall success rate hovering over 68.8%, demonstrating the successfulness of the moving average trading strategy. Fourth, various evaluations revealed the economic usefulness of our trading strategy that used market anomalies and technical analysis.

• Communications for Statistical Applications and Methods
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• v.20 no.2
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• pp.115-127
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• 2013

This paper provides an effective stock portfolio screening tool for socially responsible investment (SRI) based upon corporate social responsibility (CSR) and financial performance. The proposed approach utilizes nonparametric frontier models. Data envelopment analysis (DEA) has been used to build SRI portfolios in a few previous works; however, we show that free disposal hull (FDH), a similar model that does not assume the convexity of the technology, yields superior results when applied to a stock universe of 253 Korean companies. Over a four-year time span (from 2006 to 2009) the portfolios selected by the proposed method consistently outperform those selected by DEA as well as the benchmark.

• Korean Management Science Review
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• v.26 no.3
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• pp.101-115
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• 2009

In this paper, we propose a technology mining framework for mobile communication industry. We develop a two phase approach of new technology identification and service enhancement. The new technology identification process consists of R&D issues analysis, technology theme design, and emerging technology sampling. On the other hand, existing service enhancement process has technology landscaping, keyword based search, and technological growth analysis. By implementing these two phase frameworks, we develop a technology portfolio for mobile communication industry.

• The Research Journal of the Costume Culture
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• v.16 no.2
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• pp.369-381
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• 2008

The objectives of this study are to observe the theoretical background of brand extension, to compare & analyze the cases of brand extension in Domestic and abroad based on the existing studies to present the characteristics of brand extension strategies, and to contribute to the establishment of marketing strategies of brand portfolio for the globalization of national brands. As for the methods of research, literature review and case study were combined. As a result of the case analysis, fashion business possessing a lot of brands have powerful competitiveness when they consider the brands as one unit and manage them with definition and insight to produce mutual synergy. Given that brand environment is being complicated and diversified with market segmentation, brand extension, various product groups, numbers of competitors, and complex distribution structure, the hierarchical structure of brand may have even more significance as a strategy.

• Communications for Statistical Applications and Methods
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• v.25 no.6
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• pp.605-618
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• 2018

Risk management has been a crucial part of the daily operations of the financial industry over the past two decades. Value at Risk (VaR), a quantitative measure introduced by JP Morgan in 1995, is the most popular and simplest quantitative measure of risk. VaR has been widely applied to the risk evaluation over all types of financial activities, including portfolio management and asset allocation. This paper uses the implementations of multivariate GARCH models and copula methods to illustrate the performance of a one-day-ahead VaR prediction modeling process for high-dimensional portfolios. Many factors, such as the interaction among included assets, are included in the modeling process. Additionally, empirical data analyses and backtesting results are demonstrated through a rolling analysis, which help capture the instability of parameter estimates. We find that our way of modeling is relatively robust and flexible.