• Journal of Families and Better Life
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• v.20 no.6
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• pp.151-162
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• 2002

The instability in the current financial market caused consumers a lot of difficulties in their financial decision making. The purpose of this study is to classify the changes in household portfolios during the economic crisis under IMF-trusteeship (IMF Crisis hereafter), and to examine the characteristics of the households according to the types of household portfolio changes. The data were taken from 1996 and 1999 Korean Household Panel Studies, and 1,293 households were selected for the final analysis. Methods of analysis included frequencies, percentages, Chi-square tests, F-tests, and t-tests. Major findings are as follows: 1. In the midst of the financial market changes during the period of the IMF crisis, consumers tended to manage their household portfolio differently according to their household characteristics. 2. The changes of household portfolio can be classified into two different types: the changed type (44.4%) and the unchanged type(55.6%). There are significant differences in the level of wealth, family life cycle stage, housing tenure, and the household head's job, between the changed type and the unchanged type. The family members of the unchanged type are more likely to be older and relatively wealthy compared with the families in the changed type. 3. The changes of household portfolio can be further classified into six different types: the unchanged-liquidity type (21%), the unchanged-multiplication type (24.6%), the unchanged-insurance type (9.8%), the changed-to-liquidity type (13.9%), the changed-to-multiplication type (13.0%), and the changed-to-insurance type (17.5%). There are significant differences in income level, wealth level, family life cycle stage, housing tenure, and the job of household head among the six types of changes.

• Korean Journal of Rural Living Science
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• v.6 no.2
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• pp.173-183
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• 1995

On the basis of intertemporal utility maximization theory and stock-adjustment hypothesis, a multivariate stock-adjustment credit demand model, which included on- and cross-adjustment effects of credit and cross-adjustment effects of assets was developed. With weighted four-year panel data from 1983 and 1986 Surveys of Consumer Finances, the theoretical model was tested using two-stage estimation method for tobit model. The results supported the hypothesis that, in general, the household demand for a certain type of credit was related to the demand for other types of credit and asset components in the portfolio. The household demand for mortgage credit, installment credit and revolving credit card debt depended not only on the disequilibrium of itself but on the disequilibrium of the other types of credit and asset components in the portfolio. The household demand for non-installment credit was related not to the disequilibrium of itself and other types of credit but to the disequilibria of asset components in the portfolio.

• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.107-117
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• 2014

The main purpose of this study is to propose a portfolio investment strategy based on investor types information. For improvement of investment performance, artificial intelligence techniques are used to construct a portfolio. Among many artificial intelligence techniques, cluster analysis is applied to select securities and genetic algorithm is applied to assign the respective weight within the portfolio. Empirical experiments in the Korean stock market show that proposed portfolio investment strategy is practicable and superior strategy. This result implies that analysis of investor's trading behavior may assist investors to make an investment decision and to get superior performance.

• Management Science and Financial Engineering
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• v.10 no.1
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• pp.25-41
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• 2004

There have been many studies to build a model that can help investors construct optimal portfolio. Most of the previous models, however, are based upon the path-breaking Markowitz model (1959) which is a quantitative model. One of the most important problems with that kind of quantitative model is that, in reality, most of the investors use not only quantitative, but also qualitative information when they select their optimal portfolio. Since collecting both types of information from the markets are time consuming and expensive, making a set of target assets smaller, without suffering heavy loss in the rate of return, would attract investors. To extract only desired assets among all available assets, we need knowledge that identifies investors' preference for the risk of the assets. This study suggests two-layer decision-making rules capable of identifying an investor's risk preference and an architecture applying them to a quantitative portfolio model based on risk and expected return. Our knowledge-based portfolio system is to build an investor's preference-oriented portfolio. The empirical tests using the data from Korean capital markets show the results that our model contributes significantly to the construction of a better portfolio in the perspective of an investor's benefit/cost ratio than that produced by the existing portfolio models.

• 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.

• The Journal of the Korea Contents Association
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• v.7 no.12
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• pp.83-94
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• 2007

The portfolio can be used as a methodology supporting the learning of constructivism. Recently, the use of portfolios has been increased gradually in the education field, but a study on the current state analysis and design direction of portfolios leaves much to be desired. In this paper, we analyze statistical data on the portfolio application of teachers in domestic elementary, middle, and high school. We also propose a design direction of e-portfolio needed in the society of knowledge information based on this analysis. The results of research show that the following problems will be improved: understanding portfolio, analyzing the current state according to the types of portfolio application, designing a distinguished system according to the level of school, expanding education of teachers with high career, and developing a guide helper. The design of total system that combines the learning and evaluation is needed to improve a problem that spends lots of time to make portfolio, and operates temporally and formally achievement evaluation. In addition, the design of e-portfolio supporting efficiently interaction and self-directed teaming is required.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.4
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• pp.260-270
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• 2013

This paper proposes a strategic portfolio model for managing performance of online games. The portfolio matrix is composed of two dimensions: financial performance and non-financial performance. Financial performance is measured by the conventional measure, average revenue per user (ARPU). In terms of non-financial performance, five non-financial key performance indicators (KPIs) that have been widely used in the online game industry are utilized: RU (Register User), VU (Visiting User), TS (Time Spent), ACU (Average Current User), MCU (Maximum Current User). Data envelopment analysis (DEA) is then employed to produce a single performance measure aggregating the five KPIs. DEA is a linear programming model for measuring the relative efficiency of decision making unit (DMUs) with multiple inputs and outputs. This study employs DEA as a tool for multiple criteria decision making (MCDM), in particular, the pure output model without inputs. Combining the two types of performance produces the online game portfolio matrix with four quadrants: Dark Horse, Stop Loss, Jack Pot, Luxury Goods. A case study of 39 online games provided by company 'N' is provided. The proposed portfolio model is expected to be fruitfully used for strategic decision making of online game companies.

• Asian Journal of Business Environment
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• v.7 no.4
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• pp.17-25
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• 2017

Purpose - The purpose of this study is to present a framework for determining the most appropriate business model for e-learning. Research design, data, and methodology - The Electronics Branch of Azad University has been elected as a case study in this research. This study conducted using a descriptive method. The information was obtained using interviews with experts including managers, faculty and students at the Electronics Branch of Azad University. Results - Three service-product system (product oriented system, use an oriented and result oriented system) approaches determined a framework for the formation of a portfolio. This portfolio is including three types of e-learning business models. Examining the relevant characteristics, correspondence of behaviorism learning theory with a product-oriented approach, correspondence of cognitivism theory with a user-oriented approach and in finally match correspondence of constructivist learning theory with a results-oriented approach which is evident. Conclusions - After reviewing the literature on the fields of e-learning, business model and product - service systems, we have achieved three types of e-learning business models. Then the variables in any of the business models were defined by using business model canvas tool and thus a portfolio consisting of three types of e-learning business model canvas was obtained.

• Journal of Families and Better Life
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• v.22 no.6 s.72
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• pp.165-175
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• 2004

The purpose of this study was to classify the household financial strategies and investigate major determinants of the household financial strategies and financial performance. The data of 3,994 households is from the Korean Labor and Income Panel Stud?. The major findings were as follows. (1) The classified household financial strategies types were Residual ($44.6\%$), Informal Institutional ($13.3\%$), Financial Assets ($16.7\%$), Real Estate ($13.4\%$), and Diversified Portfolio ($12.0\%$). (2) The criteria of classification of the household financial strategies were relative, not absolute. (3) The household financial strategy types changed largely during a short period(1999-2000). (4) In all households, the variables that affected changes in household financial strategies were education, occupation, number of children, residential location and home ownership. (5) Households that employed a diversified portfolio strategy had the greatest financial performance (2,316,000 won net gain). (6) In all households, the variables that had the greatest influence on financial performance were the number of children, assets and debts. 1'he financial performance was significantly different according to changes in the household financial strategy.

• Journal of Families and Better Life
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• v.25 no.3 s.87
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• pp.25-44
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• 2007

The purpose of this study was to classify the financial strategies and investigate major determinants of the financial performance in elderly households. This study used the data of 4,577households with all ages and 1,255 elderly households were 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 regression. The major 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, elderly households that employed a financial assets had the greatest financial performance (62,320,000 won net gain). Households with all ages that employed a diversified portfolio strategy had the greatest financial performance (98,360,000 won net gain). Forth, the determinants of the financial performance were significantly different according to the types of financial strategy.