• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1777-1783
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• 2006

일반적으로 펀드평가는 절대수익률이나 위험을 조정한 샤프지수 또는 트레이너 지수를 이용하고 있는데, 이러한 방법은 벤치마크 지수를 기준으로 평가하여 펀드규모, 비용 등을 고려한 펀드간의 상대적 성과는 측정하지 못하고 있다. 펀드간의 상대적 성과평가는 펀드의 실질적인 효율성을 측정할 수 있다는 측면에서 펀드평가의 유용한 수단이 될 수 있다. 본 연구에서는 샤프의 스타일 분석을 이용하여 펀드의 유형을 분류하고, DEA를 이용하여 펀드간의 상대적인 성과를 측정한다. 분석자료는 2000년 1월부터 2005년 12월 31일까지의 주식형 펀드의 월간수익률, 수익률 표준편차, 펀드비용, 펀드규모, 운용기간, 샤프지수 등을 이용한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.165-170
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• 2015

The unsharp mask technique emphasize the boundary of the image by adding the boundary of the original image. This technique improves quality by emphasize its boundaries but produce rough image from image noise. The multi channel unsharp mask is possible to enhance entire contrast of the image by applying at least two channels of unsharp mask. However, There is limitations to strengthen boundaries even if the scale strongly applies the multi channel unsharp mask technique. To solve this problem, linear scaling to nonlinear scaling by applying exponential function to existing multi channel unsharp mask technique. Experimental results show enhanced contrast for desired area because of control scaling in details compared with existing unsharp mask technique.

• 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.

• The Korean Journal of Financial Studies
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• v.13 no.1
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• pp.133-160
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• 2007

본 연구는 중국 뮤추얼펀드를 대상으로 폐쇄형(48개), 개방형(17개)으로 구분하여 총 65개 펀드에 대해 성과를 측정해보고, 이를 통해 중국 뮤추얼펀드가 지수대비 어떠한 성과를 보여주고 있는지를 살펴보고자 한 연구이다. 성과 평가 실증기간은 폐쇄형 펀드가 2002년 1월 4일부터 2004년 12월 31일까지 3년으로 하며 개방형 펀드가 2003년 1월 3일부터 2004년 12월 31일까지 2년으로 하였다. 실증연구방법들은 CAPM에 기반한 트레이너 모형, 샤프 모형, 젠센 모형과 장세판단능력 측정 모형인 트레이너-마주이 모형이다.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Korean Journal of Construction Engineering and Management
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• v.16 no.6
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• pp.144-155
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• 2015

This paper is to understand investment's efficiency and performance of commercial real estate assets diversified by use and district. To do so, this paper divides two different commercial real estate markets(office build market and retail real estate market) in Seoul city by district into "GBD(Gangnam Business District), YBD(Yeouido Business District), and CBD(Central Business District)" and "GBD(Gangnam Business District), SBD(Shinchon Business District), and CBD(Central Business District)" respectively, configures these districts each other to structure portfolios as its portion varies based on Markowitz's Mean-Variance principle, and looks at risk-return relationship of portfolios to find out efficiency, performance, and optimal investment chosen based upon Sharpe's Performance Index. As a result, the portfolio configured by "10 to 30% of office building asset at CBD" and "70 to 90% of retail real estate asset at CBD" is shown to be the most optimal, suggesting the highest quarterly Sharpe's performance index of 2.7118~2.7776 with quarterly rate of return of 1.826%~1.838% and quarterly standard deviation of 0.573~0.589. Furthermore, it is obvious that diversified portfolio configured by use(office-retail) shows better investment performance than that by district with same type of asset(office-office or retail-retail). Finally, results driven from this research will play an important role to stimulate real estate and construction markets through enlarging ideas as to diversified investment by use and district on real estate indirect investment products.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.691-702
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• 2022

This study verifies the diversification effect when non-financial asset such as fractional music royalties investment which is recently get interest from masses, is included in traditional global asset allocation portfolio. From Jan 2019 when Music Royalties index is announced to Jun 2022, compared traditional global asset allocation portfolio and the portfolio included with music royalties. To eliminate the enhancement effect from portfolio strategy itself rather than including non-financial asset, used the four basic portfolio strategy such as buy & hold, constant rebalanced, mean variance, risk parity. As a result, all the portfolios included with music royalties shows less risk with higher returns. This means the sharpe ratio has enhanced and that results the portfolio diversification effect is placed. The empirical analysis of the study found academic significance in that the portfolio included with music royalties investment has diversification effect, and show the possibilities the not only on the music royalties, other non-financial asset can be shown the portfolio diversification effect.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.215-218
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• 2004

제품 발생 소음의 음질 (sound qualify)에 대한 관심이 높아지면서, 음질 제어가 제품 경쟁력 향상에 중요한 고려 요소가 되었다. 이러한 음질에 대한 객관적인 분석을 위하여 다수의 상용 프로그램이 개발되고 있지만 라우드니스 (loudness)를 제외한 음질인자 (sound quality metrics)들은 아직 표준화 작업이 이루어지지 않았기 때문에 프로그램에 따라 차이가 발생하고 있다. 본 연구에서는 음질 분석을 위한 4 개의 상용 프로그램을 이용하여 일정 신호의 라우드니스, 샤프니스 (sharpness), 러프니스(roughness), 변동강도 (fluctuation strength)를 계산하고, 그 결과를 비교, 분석하였고, 이미 표준화 된 라우드니스를 포함한 음질인자들의 계산 결과는 프로그램에 따라 무시할 수 없는 차이가 나타남을 확인하였다. 이는 제품의 음질 평가 시 사용된 분석 프로그램 따라 그 결과가 다를 수 있음을 의미한다. 본 연구를 통해서 얻은 결과는 향후 음질 인자의 표준화 및 음질 지수 개발에 중요한 자료로 사용 될 수 있다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.409-412
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• 2006

펀드의 성과 평가는 펀드선택 의사결정시 가장 중요한 고려요인이다. 전통적인 펀드 성과평과 지표인 샤프비율이나 트레이너 비율은 운용비용과 거래비용 등과 같은 다양한 요소들을 반영하지 못하고 있다. 펀드의 여러 수익과 비용요인들을 반영하기 위해, 본 연구에서는 DEA를 이용하여 펀드의 상대적인 효율성을 측정하였다. 분석자료는 2005년 12월 31일까지 국내에 존재하는 3년 이상 운용된 67개의 장기펀드를 대상으로 분석하였다. 입력변수는 비용과 관련된 총 보수율, 월수익률의 표준편차, 펀드 규모를 나타내기 위한 평균설정좌수를 이용하였고 출력변수는 이익과 관련된 예상 월평균수익률과 시장포트폴리오의 월수익률을 상회한 기간의 비율을 사용하였다. 본 연구결과, DEA를 통해 수익률만으로는 평가할 수 없는 펀드의 운용능력을 평가할 수 있었다.

• The Korean Journal of Financial Management
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• v.26 no.1
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• pp.189-220
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• 2009

This study tests the significance of momentum and contrarian strategy which challenge the weak efficient market hypothesis (EMH). If momentum and contrarian strategy can make extra return above the market, this can be a significant critics to the weak EMH. By using Monte Carlo simulation we have found that many existing returature, which test the significance of momentum and contrarian strategy, have a significance distortion problem. We test the significance of momentum and contrarian strategy by using reality check test of White(2000) which solve the problem of data snooping bias. The results are following. When we use the KOSPI index as the benchmark portfolio, we can get the best strategy of momentum strategy in the case of mean return. But in the case of Sharp ratio which is the performance measure adjusting risk, we find that the best strategy in the momentum and contrarian strategy can not dominate the performance of benchmark portfolio. Therefore we argue that weak EMH can not be rejected because of superior performance of momentum and contrarian strategy when we consider risk.