• 한국경영과학회지
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• 제39권2호
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• pp.83-95
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• 2014

In this paper, we develop a portfolio selection model that can be used to invest in markets with margin requirements such as the foreign exchange market. An investment algorithm to implement the proposed portfolio selection model based on objective historical data is also presented. We further conduct empirical analysis on the performance of a hypothetical investment in the foreign exchange market, using the proposed portfolio selection model and investment algorithm. Using 7 currency pairs that recorded the highest trading volume in the foreign exchange market during the most recent 10 years, we compare the performance of 1) the Dollar Index, 2) a 1/N Portfolio which equally allocates capital to all N assets considered for investment, and 3) a hypothetical investment portfolio selected and managed according to the portfolio selection model and investment algorithm proposed in this paper. Performance is compared in terms of accumulated returns and Sharpe ratios for the 10-year period from January 2003 to December 2012. The results show that the hypothetical investment portfolio outperforms both benchmarks, with superior performance especially during the period following financial crisis. Overall, this paper suggests that a mathematical approach for selecting and managing an optimal investment portfolio based on objective data can achieve outstanding performance in the foreign exchange market.

• 지식경영연구
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• 제23권1호
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• pp.89-109
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• 2022

최근 COVID-19, 동학개미운동 등 투자환경의 변화로 시스템 처리 허용 수준을 상회하는 트랜잭션이 발생하고 이로 인해 전산장애가 자본시장에서 빈번하게 나타나고 있다. 자본시장 IT시스템들은 장애 영향도가 매우 큰 시스템들로서, 2020년에 예측하지 못한 큰 규모의 트랜잭션이 상당한 기간 유입되어 전산장애가 급증하였다. 다수의 기업들이 높은 수준의 IT시스템 용량계획 정책을 유지하고 있던 상황임에도 불구하고, 이를 상회하는 트랜잭션이 유입된 것은 용량계획에 대한 새로운 접근 방법이 필요함을 시사하고 있다. 이에 본 연구는 다양한 머신러닝 기법을 활용하여 자본시장 IT시스템 용량계획 모델들을 개발하고 성능을 비교 분석한다. 또한, 동학개미운동과 같이 예측하기 힘든 투자자의 행동을 반영할 수 있는 심리지수를 예측에 활용함으로써 용량계획 모델의 성능을 높인다. COVID-19 기간을 포함한 실증데이터를 이용하여 본 연구에서 개발한 용량계획 모델은 실무에서 활용 가능한 수준의 높은 성능과 안정성을 가질 수 있다. 본 연구는 기업의 비용 효율성과 IT시스템 용량 변경에 수반되는 운영상의 제약을 모두 고려한 최적의 파라미터를 제시하였는데, 이것은 자본시장 도메인에서 유용하게 사용될 수 있다. 또한, 본 연구는 투자자의 심리를 반영하는 심리지수가 IT 시스템 용량계획에 중요한 예측요인이 될 수 있는 것을 입증함으로써, 심리지수가 다양한 수요예측에 적극적으로 활용될 수 있음을 보여준다.

• International Journal of Contents
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• 제15권2호
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• pp.44-52
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• 2019

This paper uses Delphi Method and statistics provided by the State Administration of Market Regulation of China, attempts to develop the scale index of language service industry in China. Coupled with practical investigation and theoretical framework of SCP paradigm, a deep analysis on market behavior, market structure, and market performance of the industry have been explored. First, the study indicates that the scale index of Chinese language services industry has experienced an upward trend from 10.481million RMB in 2008 to 351.403 million RMB in 2017. Second, majority of language services enterprises are situated in Chinese coastal provinces and there are variations in demand for language services. Third, the standardization of language services are minimal while most of the talents involve a single discipline background. Fourth, most enterprises utilize language tools while there is lack of technological innovation for utilization of language resources and enhancement of service quality. The author mainly suggests four strategies which include: cultivating multilingual services, strengthening the development of industrial informatization and technical innovation, and optimizing the industrial talents structure while also adjusting for industrial distribution and regional coordination, which propose the meaningful implications for the development of language service industry in China.

• The Journal of Asian Finance, Economics and Business
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• 제8권2호
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• pp.725-735
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• 2021

This study investigates whether the Islamic Exchange-Traded Funds (ETFs) provide significant benefit to investors relative to conventional ETFs. Six pairs of Islamic and conventional ETFs with 10-year daily price data from 2010 to 2019 have been selected from major market indices like MSCI World Index, MSCI Emerging Markets, MyETF Dow Jones Islamic Market Malaysia, MSCI South East Asia and Wahed FTSE Shariah USA Index for this study. For ETFs that are launched after 2010, the price data from launch date to 2019 are used. Our results show: First, Islamic ETFs are more likely to trade at a premium rather than at a discount, implying the investors are willing to pay a premium. Second, it is also found that Islamic ETFs have a relatively shorter period of price deviation from the benchmark, implying more price stability. Third, conventional ETFs have higher return and lower tracking errors relative to Islamic ETFs. These new findings add to the stylized facts of Islamic ETFs in the extant literature for investors, plan sponsors and regulators as to the differences between the ETFs. As policy suggestion, asset management companies can design new investment products to bridge the gap between conventional and Islamic finance.

• Journal of Contemporary Eastern Asia
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• 제20권2호
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• pp.63-84
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• 2021

The present study was conducted to understand the turmoil effects of COVID-19 pandemic on the Malaysian stock market during the different periods of the Movement Control Order (MCO). The present study was based on the secondary data extracted from the DataStream and Bloomberg from 2nd January 2020 to 29th May 2020 to evaluate the effects of COVID-19 pandemic on the Malaysian stock market. The findings suggested that during the different periods of the Movement Control Order (MCO) from the 1st January to 29th May 2020, the COVID-19 pandemic adversely affected the performance of KLCI index and all sectoral indices. The weakest performance indices were energy, property, and finance while the least affected indices were healthcare, technology, telecommunications, and media. This paper provides a review of the impacts of COVID-19 pandemic on the Malaysian stock market throughout the different periods of MCO.

• The Journal of Asian Finance, Economics and Business
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• 제8권4호
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• pp.741-749
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• 2021

The research paper endeavors to investigate the presence of seasonal anomalies in the Indian equity market. It also aims to verify the notion that equity markets are for long-term investors. The study employs daily index data of Sensex, Bombay Stock Exchange, to understand its volatility for the period ranging from January 2001 to August 2020. To analyze the seasonal effects in the stock market of India, multiple regression techniques along with descriptive analysis, graphical analysis and various statistical tests are used. The study also employs the rolling returns at different time intervals in order to understand the underlying risks and volatility involved in equity returns. The results from the analysis reveal that daily and monthly seasonality is not present in Sensex returns i.e., investors cannot earn abnormal returns by timing their investment decisions. Hence, the major finding of this study is that the Indian stock market performance is random, and the returns are efficient. The other major conclusion of the research is that the equity returns are profitable in the long run providing investors a hope that they can make gains and compensate for the loss in one period by a superior performance in some other periods.

• 산업경영시스템학회지
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• 제41권3호
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• pp.154-161
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• 2018

This study conducted to predict the stock market prices based on the assumption that internet news articles might have an impact and effect on the rise and fall of stock market prices. The internet news articles were tested to evaluate the accuracy by comparing predicted values of the actual stock index and the forecasting models of the companies. This paper collected stock news from the internet, and analyzed and identified the relationship with the stock price index. Since the internet news contents consist mainly of unstructured texts, this study used text mining technique and multiple regression analysis technique to analyze news articles. A company H as a representative automobile manufacturing company was selected, and prediction models for the stock price index of company H was presented. Thus two prediction models for forecasting the upturn and decline of H stock index is derived and presented. Among the two prediction models, the error value of the prediction model (1) is low, and so the prediction performance of the model (1) is relatively better than that of the prediction model (2). As the further research, if the contents of this study are supplemented by real artificial intelligent investment decision system and applied to real investment, more practical research results will be able to be developed.

• Journal of information and communication convergence engineering
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• 제6권3호
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• pp.323-326
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• 2008

Data Envelopment Analysis (DEA) is a theoretically sound framework for performance analysis that offers many advantages over traditional methods such as performance ratios and regression analysis. Largely the result of multidisciplinary research during the last three decades in economics, engineering and management, DEA is best described as an effective new way of visualizing and analyzing performance data. Besides, overseas information technology companies have aggressively tried to enter the domestic market. In the age of globalization and high competition, it is imperative that the system integration (SI) companies need to introduce the performance evaluation models of SI projects, including Capability Maturity Model and Software Process Improvement and Capability Determination, to gain a competitive advantage. Therefore, it makes our research regarding evaluation of SI projects very opportune. The purpose of the study is not only to evaluate efficiency of each project by DEA but also to gain insight into various factors such as project complexity, team members' man-months structure, and process index(project management index) that link to the projects performance.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2008년도 추계학술대회 및 정기총회
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• pp.76-94
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• 2008

본 논문은 마코위츠의 포트폴리오 선정 이론을 한국 주식 시장에 실제 적용할 경우 투자 성과를 평가해 본 실증적 연구이다. 이를 위해서 대중적으로 인기가 있었던 삼성그룹주펀드 5종 및 KOSPI지수 변화율을 마코위츠의 모형과 비교 분석하였다. 2007년 3월부터 2008년 9월까지 최근 1년 6개월의 기간에 대하여, KOSPI 지수는 0.1%로 거의 변화를 보이지 않은 반면, 삼성그룹주펀드 5종의 평균수익률은 20.54%였고, 삼성그룹주펀드를 구성하는 동일한 17개 종목으로 마코위츠의 모형에 따라 투자한 방식은 52%의 수익률을 올렸다. 수익률을 극대화하기 위하여 데이터 수집 기간 및 포트폴리오 교체 주기에 대하여 민감도 분석을 수행하였다. 결론적으로, 투자자 개인의 주관이나 감정에 의한 판단을 완전히 배제하고 객관적 데이터에 의하여 포트폴리오를 수리적으로 변경하는 마코위츠의 모형에 의한 투자 방식이, 상대적으로 우월한 시장 정보를 가지고 주관적 판단에 의해 능동적으로 포트폴리오를 변경하는 시중 펀드매니저의 운영 성과에 비해 월등하였음을 본 연구에서는 삼성그룹주펀드의 실증적 연구를 통하여 보이고 있다.

• 한국산학기술학회논문지
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• 제16권10호
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• pp.6534-6542
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• 2015

본 연구에서는 4개 뮤추얼펀드 유형을 대상으로 한국시장에서의 펀드 성과와 펀드 현금흐름 간의 관계를 분석하였다. 주별 및 월별 자료를 사용한 분석결과는 다음과 같다. 첫 번째, 양자 간의 관계는 펀드의 유형에 따라 다르게 나타나고 있으며, 같은 주식형 펀드인 일반주식형 펀드와 인덱스형 펀드 역시 다른 결과를 보여주고 있다. 두 번째, 양자 간의 관계는 펀드시장의 구조변화 이전/이후 기간에서 다른 양상을 보여 시장의 구조변화가 동 관계에 무시할 수 없는 영향을 미쳤음을 보여주었다. 세 번째, 수익률을 추구하는 현금흐름(return chasing flow)은 채권형 펀드에서 가장 강하게 나타났으며, 일반주식형펀드 및 MMF에서는 구조변화 이후 기간에서만 나타났다. 그러나 인덱스형 펀드에서는 전혀 관측되지 않았다. 네 번째, 펀드현금흐름이 향후의 펀드 성과에 미치는 영향은 오직 MMF에서만, 그리고 구조변화 이후의 기간에서만 관측되었다.