• Journal of information and communication convergence engineering
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• v.9 no.5
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• pp.491-499
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• 2011

In this paper, we offer a new strategic portfolio model for national IT R&D project selection in Korea. A risk and return (R-R) portfolio model was developed using an objectively quantified index on the two axes of risk and return, in order to select a strategic project and allocate resources in compliance with a national IT R&D strategy. We strategize using the R-R portfolio model to solve the non-strategy and subjectivity problems of the existing national R&D project selection model. We also use the quantified evaluation index of the IT technology road map (TRM) and the technical level reports (TLR) for the subjectivity of project selection, and try to discover the weights using the analytic hierarchy process (AHP). In addition, we intend to maximize the chance for a successful national IT R&D project, by selecting a strategic portfolio project and balancing the allocation of resources effectively and objectively.

• IE interfaces
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• v.23 no.4
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• pp.300-310
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• 2010

This paper is about an optimal investment portfolio strategy. Financial data of stocks, bonds, and savings from January 2. 2001 through October 30. 2009 were utilized in order to suggest the optimal portfolio strategies. Fundamental analysis and technical analysis were used in stocks-related strategy, whereas passive investment strategy and active investment strategy were used in bond-related strategy. The score is assigned to each stock index according to the suggested strategies and set trading rules are based on the scores. The simulation has been executed about each 29,400-portfolios and we figured out with the simulation result that 26.75% of 7,864 portfolios are more profitable than average stock market profit (22.6%, Annualized). The outcome of this research is summarized in two parts. First, it's the rebalancing strategy of portfolio. The result shows that value-oriented investment(long-term investment) strategy yields much higher than short-term investment strategies of stocks or active investment of bonds. Second, it's about the rebalancing cycle forming the portfolios. The result shows that the rate of return for the portfolio is the best when rebalancing cycle is 12 or 18 months.

• East Asian Economic Review
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• v.25 no.3
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• pp.310-336
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• 2021

We use iterative numerical procedures combined with analytical methods due to Rapach and Wohar (2009) to solve for the dynamic asset allocation strategy for optimal portfolio demand. We compare different optimal portfolio demands when investors in each country have different access to overseas and domestic investment opportunities. The optimal dynamic asset allocation strategy without foreign investment opportunities leads domestic investors in Korea, Hong Kong, and Singapore to allocate more funds to domestic bonds than to domestic stocks. However, the U.S. investors allocate more wealth to domestic stocks than to domestic bonds. Investors in all countries short bills at a low level of risk aversion. Next, we investigate dynamic asset allocation strategy when domestic investors in Korea have access to foreign markets. The optimal portfolio demand leads investors in Korea to allocate most resources to domestic bonds and foreign stocks. On the other hand, the portfolio weights on foreign bonds and domestic stocks are relatively low. We also analyze dynamic asset allocation strategy for the investors in the U.S., Hong Kong, and Singapore when they have access to the Korean markets as overseas investment opportunities. Compared to the results when the investors only have access to domestic markets, the investors in the U.S. and Singapore increase the portfolio weights on domestic stocks in spite of the overseas investment opportunities in the Korean markets. The investors in the U.S., Hong Kong, and Singapore short domestic bills to invest more than initial funds in risky assets with a varying degree of relative risk aversion coefficients without exception.

• Proceedings of the Korea Association of Information Systems Conference
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• 2004.11a
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• pp.201-208
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• 2004

Many organizations experience that the Performance they gained from IT portfolio is lower than they expected values. As with any investment, executives are concerned with maximizing the performance from their investment in IT. This study focused on the relationship or fit between orientations of IT strategy and directions of IT portfolio to maximize IT performance. A field survey of chief information officers of Korea manufacturing sector was conducted in 2003. Complete data of 147 firms was analyzed to determine relationship among the three research constructs that are orientations of IT strategy, directions IT portfolio, and IT performance. In this study, the orientations of IT strategy have two dimensions that are operation orientation and market orientation. The directions of IT portfolio have two dimension that are internal system focused and external system focused. And the IT performance has divided into operational performance and competitive performance. As a result of this study, the companies that are putting a focus with operation orientation were concentrated on internal information systems than external information systems. On the other hand, the other companies that are focused on market orientation were concentrated on external information systems than internal information systems. Consequently, the companies that are focused on operation orientation were operational performance higher than competitive performance and the other companies that are focused on market orientation were competitive performance higher than operational performance. More importantly, the research results provide empirical evidence that supports the hypothesis related to closer fit between IT strategy and IT portfolio does lead to increase operational and competitive performance of IT. And the results emphasize manager's efforts of fit between orientations of IT strategy and directions of IT portfolio to be realized IT performance.

• Journal of Korean Society for Quality Management
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• v.45 no.3
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• pp.427-445
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• 2017

Purpose: This paper provides a method to identify cost-effective standards by analyzing the relationships between certified company and standards. It also aims to provide a evaluation model to establish a certification portfolio strategy of institutions. Methods: By analysing the networks of certified company and certification standards, this paper developed an evaluation model of standards. The evaluation model uses an index(Certificated Standard Evaluation Index; CSEI) to assess the value of standards. Results: To verify the applicability of the evaluation model, the proposed model and the CSEL index have been applied to certification standards of Korean Standard Association. The results show that the evaluation model can effectively identify potential customers and thereby establish a certification portfolio strategy. Conclusion: The main contribution of this study is a provision of a new approach to certification portfolio strategy by evaluating the value of standards. The proposed model is expected to provide implications for the certification portfolio strategy.

• 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.

• Asia-Pacific Journal of Business
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• v.10 no.3
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• pp.37-51
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• 2019

In this paper, we investigate the performance of anomaly factors in Asia-Pacific Stock market and show the higher Sharpe ratio of the volatility managed smart beta portfolio. The smart beta portfolio combines the benefit of passive strategy and active strategy. However, the smart beta portfolios are seems to be exposed to the risk of anomaly factors from the perspective of traditional financial equilibrium model. Therefore, the smart beta strategy may generate negatively skewed returns unappealing to investors having lower risk tolerance. Our empirical investigations find that the return of the Asia-Pacific region stock market is more volatile than other regions with the lower efficiency ratio. However, the value factor and the momentum factor of Asia-Pacific region both show good performances. More interestingly, we also find that managing the volatility of the momentum factor in Asia-Pacific stock market almost doubles the efficiency ratio.

• Korean Management Science Review
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• v.30 no.3
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• pp.1-16
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• 2013

In this paper, we deal with an enhanced index fund strategy by implementing the exchange trade funds (ETFs) within the context of the Black-Litterman approach. The KOSPI200 index ETF is used to build risk-controlled portfolio that tracks the benchmark index, while the proposed Black-Litterman model mitigates estimation errors in incorporating both active investment views and equilibrium views. First, we construct a Black-Litterman model portfolio with the active market perspective based on the momentum strategy. Then, we update the portfolio with the KOSPI200 index ETF by using the equilibrium return ratio and weighted averages, while devising optimization modeling for improving the information ratio (IR) of the portfolio. Finally, we demonstrate the empirical viability of the proposed enhanced index strategies with KOSPI 200 data.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.59-71
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• 2014

System trading is becoming more popular among Korean traders recently. System traders use automatic order systems based on the system generated buy and sell signals. These signals are generated from the predetermined entry and exit rules that were coded by system traders. Most researches on system trading have focused on designing profitable entry and exit rules using technical indicators. However, market conditions, strategy characteristics, and money management also have influences on the profitability of the system trading. Unexpected price deviations from the predetermined trading rules can incur large losses to system traders. Therefore, most professional traders use strategy portfolios rather than only one strategy. Building a good strategy portfolio is important because trading performance depends on strategy portfolios. Despite of the importance of designing strategy portfolio, rule of thumb methods have been used to select trading strategies. In this study, we propose a SVM-based strategy portfolio management system. SVM were introduced by Vapnik and is known to be effective for data mining area. It can build good portfolios within a very short period of time. Since SVM minimizes structural risks, it is best suitable for the futures trading market in which prices do not move exactly the same as the past. Our system trading strategies include moving-average cross system, MACD cross system, trend-following system, buy dips and sell rallies system, DMI system, Keltner channel system, Bollinger Bands system, and Fibonacci system. These strategies are well known and frequently being used by many professional traders. We program these strategies for generating automated system signals for entry and exit. We propose SVM-based strategies selection system and portfolio construction and order routing system. Strategies selection system is a portfolio training system. It generates training data and makes SVM model using optimal portfolio. We make $m{\times}n$ data matrix by dividing KOSPI 200 index futures data with a same period. Optimal strategy portfolio is derived from analyzing each strategy performance. SVM model is generated based on this data and optimal strategy portfolio. We use 80% of the data for training and the remaining 20% is used for testing the strategy. For training, we select two strategies which show the highest profit in the next day. Selection method 1 selects two strategies and method 2 selects maximum two strategies which show profit more than 0.1 point. We use one-against-all method which has fast processing time. We analyse the daily data of KOSPI 200 index futures contracts from January 1990 to November 2011. Price change rates for 50 days are used as SVM input data. The training period is from January 1990 to March 2007 and the test period is from March 2007 to November 2011. We suggest three benchmark strategies portfolio. BM1 holds two contracts of KOSPI 200 index futures for testing period. BM2 is constructed as two strategies which show the largest cumulative profit during 30 days before testing starts. BM3 has two strategies which show best profits during testing period. Trading cost include brokerage commission cost and slippage cost. The proposed strategy portfolio management system shows profit more than double of the benchmark portfolios. BM1 shows 103.44 point profit, BM2 shows 488.61 point profit, and BM3 shows 502.41 point profit after deducting trading cost. The best benchmark is the portfolio of the two best profit strategies during the test period. The proposed system 1 shows 706.22 point profit and proposed system 2 shows 768.95 point profit after deducting trading cost. The equity curves for the entire period show stable pattern. With higher profit, this suggests a good trading direction for system traders. We can make more stable and more profitable portfolios if we add money management module to the system.

• Asia Marketing Journal
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• v.15 no.4
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• pp.187-200
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• 2014

The case study of OB shows dramatic market dynamics between leader brand vs. follower brand similar to Kirin vs. Asahi in Japan for two decades. Almost 20yrs ago, the brand status of OB was dramatically fallen because of the environmental pollution of subsidiary company and harsh competition of rivalry brand. But OB made a ground change in its brand strategy. OB departed from the pride in its past to bet on the new. OB decided to vitalize Cass brand through brand portfolio strategy. They deployed 3 phase articulated marketing plans; Phase I, Acquisition of Cass brand through M&A and strategic segmentation/targeting (1993-2005), Phase 2 - Mega Brand Strategy through Line Extension(2006-2009), Phase 3 - Experiential Marketing focused on Young Culture (2010- present). Finally, OB restored not only brand reputation of Cass and other brands but dominant market position in beer market. Now Cass has been growing rapidly in the last 20 years achieving 50% M/S. The three phases shows the typical successful process of brand management and revitalization adopting brand concept management and S-T-P strategy of manufacturing company.