• 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.

• 산업경영시스템학회지
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• 제45권3호
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• pp.123-130
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• 2022

Pair trading is a statistical arbitrage investment strategy. Traditionally, cointegration has been utilized in the pair exploring step to discover a pair with a similar price movement. Recently, the clustering analysis has attracted many researchers' attention, replacing the cointegration method. This study tests a clustering-driven pair trading investment strategy in the Korean stock market. If a pair detected through clustering has a large spread during the spread exploring period, the pair is included in the portfolio for backtesting. The profitability of the clustering-driven pair trading strategies is investigated based on various profitability measures such as the distribution of returns, cumulative returns, profitability by period, and sensitivity analysis on different parameters. The backtesting results show that the pair trading investment strategy is valid in the Korean stock market. More interestingly, the clustering-driven portfolio investments show higher performance compared to benchmarks. Note that the hierarchical clustering shows the best portfolio performance.

• 경영과정보연구
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• 제34권1호
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• pp.65-80
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• 2015

본 연구는 완전자본시장이 성립하는 경우 시장참가자들이 소유 및 거래하는 포트폴리오의 형태가 시장포트폴리오여야 한다는 논리를 바탕으로 그들이 거래하는 포트폴리오가 시장포트폴리오의 모습과 다르다면 이는 그들만이 가지고 있는 정보를 가지고 거래를 하였다는 가정에서 출발한다. 매수-매도 거래별로 시장포트폴리오로부터의 이격정도를 측정하는 선택적 종목거래활동 강도 지표를 구성하고 가격비율과의 회귀분석을 통해 특정 투자자집단의 거래가 정보거래인지를 판단하였다. 연구결과 개인 투자자집단의 종목선택행위가 가장 높게 나타났으나 회귀계수의 통계적 유의성이 일관적이지 못 하고 그 크기 또한 경제적 의미를 부여할만큼 크지 못 하기에 이들의 거래는 정보거래와는 무관한 거래라고 판단된다. 기관 투자자집단의 경우 회귀계수가 유의적인 음(-)으로 나와 그들의 거래는 정보거래와는 거리가 멀다고 판단된다. 외국인 투자자집단의 경우 매도 거래행위에서 일관적인 양(+)의 회귀계수가 나타남을 통해 정보거래를 행하고 있음을 확인할 수 있었다. 이는 Yoo(2008)에서 언급한 바와 같이 신흥시장에서는 외국인투자자가 상위 정보거래자, 기관투자자가 하위 정보거래자, 개인투자자는 비정보거래자의 역할을 한다고 보는 견해와 일치된다.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2005년도 추계학술대회
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• pp.537-557
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• 2005

The estimate on volatility of stock price is related with optimum of portfolio and Important for allocation of capital asset. If the volatility of stock price is varied according to macroeconomic variables on monetary policy and industrial production, it will assist capital asset to allocate. This paper is related with stock market volatilities on macroeconomic variables in U.S. and Europe, Korea. And, it Is pertain to vary in time of this variables. Thus, this paper is related with volatilities of monetary and physical macroeconomic variables on basis of statistics. And, it is ranged front capital investment to portfolio allocation. Also, this paper takes out of sample forecast and study more after this. In case Germany, France, Italy and the Netherlands, the relative importance of monetary policy and Industrial production Is different from these countries. In case Italy and the Netherlands, monetary policy is primary factor at stabilizing for volatility of stock price. In case Korea, increasing monetary policy and industrial production is positively affected stock market. It is that the positive effect of stock price is caused by mollifying monetary policy and economic growth. Specially, this conclusion is similar to US. In Korea, gradual increase in monetary and industrial production is necessary to stability of stock market. It is different to previous results on basis of increasing stock price of money in long period.

• The Journal of Asian Finance, Economics and Business
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• 제9권9호
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• pp.351-360
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• 2022

This study aims to determine the factors that can influence investors in selecting stocks in the Indonesian capital market to establish an optimal portfolio, and find phenomena that occurred during the COVID-19 pandemic so that buying interest / the number of investors increased in the Indonesian capital market. This study collection technique uses primary data obtained from the survey questionnaire and secondary data which is market data, stock price movement data sourced from the Indonesia Stock Exchange, Indonesian Central Securities Depository, and Bank Indonesia, as well as empirical literature on behavior finance, investment decision, and interest in buying stock. The method used in this research is the survey questionnaire analysis with the SEM (statistical approach). The results of the analysis using SEM show that investor behavior influences the stock-buying interest, investor behavior, and the stock-buying interest influences investor decision-making. However, risk management does not influence investor-decision making. This occurs when the investigator's psychological capacity produces more decision information by decreasing all potential biases, allowing the best stock selection model to be selected. When the investigator's psychological capacity creates more decision information by reducing biases, the optimum stock selection model can be chosen.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2007년도 추계학술대회 및 정기총회
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• pp.134-137
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• 2007

Unlike the mean-variance approach, the stochastic dominance approach is to form a portfolio that stochastically dominates a predetermined benchmark portfolio such as KOSPI. This study is to search a set of portfolio weights for the first degree stochastic dominance with maximum expected return by managing the constraint set and the objective function separately. An algorithm was developed and tested with promising results against Korean stock market data sets.

• 한국경영과학회지
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• 제28권1호
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• pp.25-36
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• 2003

Unlike the mean-variance approach, the stochastic dominance approach Is to form a portfolio that first-degree stochastically dominates a predetermined benchmark portfolio, e.g. KOSPI. Analytically defining the first derivative of the objective function, an optimal algorithm of nonlinear programming was developed to search a set of optimal weights systematically and tested with promising results against veal data sets from Korean stock market.

• The Journal of Asian Finance, Economics and Business
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• 제8권6호
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• pp.543-552
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• 2021

The study examines how foreign capital inflows affect stock market development in Pakistan for the period from July 2008 to June 2018. Several components of foreign capital inflows were used for empirical analysis, namely, foreign direct investment, foreign portfolio investment, and remittances. Further, market capitalization was used as a proxy for stock market development. The study uses an ARDL model for examining the long-run and short-run relationships between variables. We also analyze the bi-directional causality between the variables through the Granger causality test. Further, the presence of structural breaks was analyzed through the CUSUM and CUSUM Square test. The results suggest that in the long run, remittances have a positive and significant relationship with stock market development. However, foreign direct investment, foreign portfolio investment, and USD-PKR exchange rate do not have a significant impact on stock market development. The results also suggest that in the short run there is a negative relationship between FDI, USD-PKR exchange rate and market capitalization. Contrarily, we found a positive relationship between FPI and market capitalization. The results of Granger causality test suggest that remittances and USD-PKR exchange rate have a causal relationship with stock market development. Finally, we found no evidence of structural breaks in the dataset.

• 아태비즈니스연구
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• 제12권1호
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• pp.121-134
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• 2021

Purpose - This study examines whether flight-to-liquidity (FTL) explains the dynamic liquidity risk on stock returns, and whether it has a significant influence on determinants the cross-section of stock returns. Design/methodology/approach - This study suggests a new risk factor, dynamic liquidity hedge portfolio (DLP), to reflect the dynamic impact of liquidity risk on stock returns and the Fama-MacBeth 2 stage regression analysis is employed in order to analyze the data. Findings - First, the DLP factor shows more positive and significant beta for the small or illiquidity stocks. Second, the DLP shows a different influence than SMB (size risk factor), HML (value risk factor), NMP (liquidity risk factor), FTVOL (total volatility factor) in determining the cross-section of stock returns. In addition, the DLP has a statistically significant risk premium of around 5%, which is relatively larger than other risk factors. Research implications or Originality - This study has academic value in terms of newly confirming that the DLP factor has a more significant impact on cross-sectional determination of stock returns than other risk factors by proposing a conditional liquidity factor that can explain the FTL phenomenon.

• 경영과학
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• 제32권1호
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• pp.15-33
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• 2015

Under complete information, introducing additional constraints to a portfolio will have a negative impact on performance. However, real-life investments inevitably involve use of error-prone estimations, such as expected stock returns. In addition to the reality of incomplete data, investments of most Korean domestic equity funds are regulated externally by the government, as well as internally, resulting in limited maximum investment allocation to single stocks and risk free assets. This paper presents an investment framework, which takes such real-life situations into account, based on a newly developed portfolio selection model considering realistic constraints under incomplete information. Additionally, we examined the effects of additional constraints on portfolio's performance under incomplete information, taking the well-known Samsung and SK group stocks as performance benchmarks during the period beginning from the launch of each commercial fund, 2005 and 2007 respectively, up to 2013. The empirical study shows that an investment model, built under incomplete information with additional constraints, outperformed a model built without any constraints, and benchmarks, in terms of rate of return, standard deviation of returns, and Sharpe ratio.