• 산업융합연구
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• 제2권2호
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• pp.127-147
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• 2004

This paper examines the time-series relations among expected return, risk, and book-to-market(B/M) at the portfolio level. The time-series analysis is a natural alternative to cross-sectional regressions. An alternative feature of the time-series regressions is that they focus on changes in expected returns, not on average returns. Using the time-series analysis, we can directly test whether the three-factor model explains time-varying expected returns better than the characteristic-based model. These results should help distinguish between the risk and mispricing stories. We find that B/M is strongly associated with changes in risk, as measured by the Fama and French(1993) three-factor model. After controlling for changes in risk, B/M contains little additional information about expected returns. The evidence suggests that the three-factor model explains time-varying expected returns better than the characteristic-based model.

• Journal of Information Processing Systems
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• 제18권5호
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• pp.637-649
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• 2022

Investors aim to increase their profitability by investing in the stock market. An adroit strategy for minimizing related risk lies through diversifying portfolio operationalization. In this paper, we propose a six-step stocks portfolio selection model. This model is based on data mining clustering techniques that reflect the ensuing impact of the political, economic, legal, and corporate governance in Mongolia. As a dataset, we have selected stock exchange trading price, financial statements, and operational reports of top-20 highly capitalized stocks that were traded at the Mongolian Stock Exchange from 2013 to 2017. In order to cluster the stock returns and risks, we have used k-means clustering techniques. We have combined both k-means clustering with Markowitz's portfolio theory to create an optimal and efficient portfolio. We constructed an efficient frontier, creating 15 portfolios, and computed the weight of stocks in each portfolio. From these portfolio options, the investor is given a choice to choose any one option.

• 아태비즈니스연구
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• 제13권2호
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• pp.123-138
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• 2022

Purpose - This study compares the performances of dynamic asset allocation strategies using Korean stocks and U.S. dollar, which have been negatively correlated for a long time, to examine the diversification effects in the portfolios of them. Design/methodology/approach - In the current study, we use KOSPI200 index, as a proxy of the aggregated portfolio of Korean stocks, and USDKRW foreign exchange rate to implement various portfolio management strategies. We consider the equally-weighted, risk-parity, minimum variance, most diversified, and growth optimal portfolios for comparison. Findings - We first find the enhancement of risk adjusted returns due to risk reduction rather than return increasement for all the portfolios of consideration. Second, the enhancement is more pronounced for the trading strategies using correlations as well as volatilities compared to those using volatilities only. Third, the diversification effect has become stronger after the global financial crisis in 2008. Lastly, we find that the performance of the growth optimal portfolio can be improved by utilizing the well-known momentum phenomenon in stock markets to select the length of the sample period to estimate the expected return. Research implications or Originality - This study shows the potential benefits of adding the U.S. dollar to the portfolios of Korean stocks. The current study is the first to investigate the portfolio of Korean stocks and U.S. dollar from investment perspective.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2000년도 추계학술대회 및 정기총회
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• pp.89-92
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• 2000

The purpose of this thesis is to investigate the information content of commercial paper credit rating changes of Korean firms. The result shows neither sinificant daily abnormal returns nor significant cumulative daily abnormal returns over the test window. This ind icates that commercial paper rating changes are not informative to investors. A sensitivity analysis conducted for the portfolio of subsample shows a similar result. This thesis, however, may contribute to the better operation of Korean financial market by providing several directions to establish credit-based financial transactions.

• 지식경영연구
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• 제19권1호
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• pp.97-118
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• 2018

The finance-investment industry is currently focusing on research related to artificial intelligence and big data, moving beyond conventional theories of financial engineering. However, the case of equity optimization portfolio by using an artificial intelligence, big data, and its performance is rarely realized in practice. Thus, the purpose of this study is to propose process improvements in equity selection, information analysis, and portfolio composition, and lastly an improvement in portfolio returns, with the case of an equity optimization model based on quantitative research by an artificial intelligence. This paper is an empirical study of the portfolio based on an artificial intelligence technology of "D" asset management, which is the largest domestic active-quant-fiduciary management in accordance with the purpose of this paper. This study will apply artificial intelligence to finance, analyzing financial and demand-supply information and automating factor-selection and weight of equity through machine learning based on the artificial neural network. Also, the learning the process for the composition of portfolio optimization and its performance by applying genetic algorithms to models will be documented. This study posits a model that the asset management industry can achieve, with continuous and stable excess performance, low costs and high efficiency in the process of investment.

• 자원ㆍ환경경제연구
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• 제20권2호
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• pp.335-356
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• 2011

본 연구에서는 Markowitz (1952)의 평균-분산 모형과 지배원리에 입각하여 원유, 석탄, 천연가스로 대표되는 화석에너지원의 최적 소비조합을 구축하려 하였다. 이를 위해 1달러당 열량으로 정의된 화석에너지원들의 편익변동을 동태은닉공통인자 모형을 이용하여 동행부분과 개별 에너지원의 특이적 수급상황에 기초한 변동으로 분해한 후, 그 결과에 기초하여 최적 화석에너지원의 최적 소비조합을 구성하였다. 분석결과, 평균-분산 모형에서 최적 소비조합을 의미하는 효율적 프론티어 선상의 소비조합들에서는 사회적으로 도달 가능한 최저 수준의 원유소비 비중을 유지하면서 석탄보다는 천연가스의 소비비중을 높여야 하는 것으로 나타났다. 이와 같은 결과는 현재 우리나라에서 추구하고 있는 원유 및 석탄의 소비비중 축소전략과도 일치하는 결과라 할 수 있으며, 원유소비의 비중축소가 화석에너지원의 소비로부터 얻을 수 있는 편익향상과 함께 편익변동에 따르는 경제활동의 불안정성을 축소시킬 수 있는 방법임을 지적하는 것이라 할 수 있다.

• 지능정보연구
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• 제27권1호
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• pp.65-82
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• 2021

주식시장에 참여하는 투자자들은 크게 외국인투자자, 기관투자자, 그리고 개인투자자로 구분된다. 외국인투자자 같은 전문투자자 집단은 개인투자자 집단과 비교하여 정보력과 자금력에서 우위를 보이고 있으며, 그 결과 시장 참여자들 사이에는 외국인투자자들이 좋은 투자 성과를 보이는 것으로 알려져 있다. 외국인 투자자들은 근래에는 인공지능을 이용한 투자를 많이 하고 있다. 본 연구의 목적은 투자자별 거래량 정보와 머신러닝을 결합하는 투자전략을 제안하고, 실제 주가와 투자자별 거래량 데이터를 이용하여 제안 모형의 포트폴리오 투자 성과를 분석하는 것이다. 일별 투자자별 매수 수량과 매도 수량 정보는 한국거래소에서 공개하고 있는 자료를 활용하였으며, 여기에 인공신경망을 결합하여 최적의 포트폴리오 전략을 도출하고자 하였다. 본 연구에서는 자기 조직화 지도 모형 인공신경망을 이용하여 투자자별 거래량 데이터를 그룹화하고 그룹화한 데이터를 변환하여 오류역전파 모형을 학습하였다. 학습 후 검증 데이터 예측결과로 매월 포트폴리오 구성을 하도록 개발하였다. 성과 분석을 위해 포트폴리오의 벤치마크를 지정하였고 시장 수익률 비교를 위해 KOSPI200, KOSPI 지수 수익률도 구하였다. 포트폴리오의 동일배분 수익률, 복리 수익률, 연평균 수익률, MDD, 표준편차, 샤프지수, 벤치마크로 지정한 시가총액 상위 10종목의 Buy and Hold 수익률 등을 사용하여 성과 분석을 진행하였다. 분석 결과 포트폴리오가 벤치마크 대비 2배 수익률을 올렸으며 시장 수익률보다 좋은 성과를 보였다. MDD와 표준편차는 포트폴리오와 벤치마크가 비슷한 결과로 성과 대비 비교한다면 포트폴리오가 좋은 성과라고 할 수 있다. 샤프지수도 포트폴리오가 벤치마크와 시장 결과보다 좋은 성과를 내었다. 이를 통해 머신러닝과 투자자별 거래정보 분석을 활용한 포트폴리오 구성 프로그램 개발의 방향을 제시하였고 실제 주식 투자를 위한 프로그램 개발에 활용할 수 있음을 보였다.

• 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.

• 한국산학기술학회논문지
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• 제13권4호
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• pp.1551-1556
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• 2012

본 연구에서는 KOSPI에 상장된 기업을 대상으로 기업의 효율성을 고려하여 포트폴리오를 구성하는 방안을 제시한다. 이를 위해 한국거래소(KRX)에서 구분하는 산업 업종별로 DEA(Data Envelopment Analysis) 기법을 이용하여 기업 효율성 분석을 실시하고 효율성이 우수한 기업들을 대상으로 마코위츠 모형을 통해 포트폴리오를 구성한다. 본 연구에서 제안한 포트폴리오 구성 방안의 성능 실험을 위해 KOSPI에 상장된 약 600개의 기업의 주식을 대상으로 4년 (2007~2010) 동안 매해 포트폴리오를 구성하였고 각각의 포트폴리오 수익률을 경영 효율성을 고려하지 않고 구성한 포트폴리오 및 시장 수익률과의 비교 분석을 통해 그 우수성을 입증하였다.

• 아태비즈니스연구
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• 제11권4호
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• pp.37-48
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• 2020

Purpose - This study empirically investigates whether the risk property included in fat-tails of return distributions is systematic or unsystematic based on the devised statistical methods. Design/methodology/approach - This study devised empirical designs based on two traditional methods: principal component analysis (PCA) and the testing method of portfolio diversification effect. The fatness of the tails in return distributions is quantitatively measured by statistical probability. Findings - According to the results, the risk property in the fat-tails of return distributions has the economic meanings of eigenvalues having a value greater than 1 through PCA, and also systematic risk that cannot be removed through portfolio diversification. In other words, the fat-tails of return distributions have the properties of the common factors, which may explain the changes of stock returns. Meanwhile, the fatness of the tails in the portfolio return distributions shows the asymmetric relationship of common factors on the tails of return distributions. The negative tail in the portfolio return distribution has a much closer relation with the property of common factors, compared to the positive tail. Research implications or Originality - This empirical evidence may complement the existing studies related to tail risk which is utilized in pricing models as a common factor.