• East Asian Economic Review
• /
• 제25권3호
• /
• pp.310-336
• /
• 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.

• 기술혁신연구
• /
• 제26권4호
• /
• pp.29-56
• /
• 2018

최근 글로벌 기업들은 신기술 확보를 위해 사내벤처캐피탈(Corporate Venture Capital, CVC)을 설립하여 기술벤처에 투자하고 있다. 본 연구의 목적은 CVC의 투자 포트폴리오 운영방식 차이가 모기업의 기술혁신 효과에 영향을 주는지 통계적으로 실증 분석하기 위함에 있다. 구체적으로 CVC의 '시드(Seed)', '초기(Early)', '확장(Expansion)', '후기(Late)' 4가지 투자 단계별로 투자된 금액비중에 따라 매년 투자 포트폴리오 성장잠재성과 리스크 수준이 달라진다는 것을 발견하였고, 포트폴리오의 공격적인 투자성향과 외부 파트너십이 모기업 기술 혁신효과에 미치는 영향에 대해 분석하였다. 연구를 위해 글로벌 70개 CVC들이 21년간 투자한 실적 데이터를 음이항 패널 회귀분석(negative binomial panel regression)을 통해 검증하였다. 연구의 결과, 벤처 포트폴리오 내 시드/초기 단계 기업들에 투자한 금액이 클수록 기술혁신 효과는 증가하지만, 일정 수준 이상부터는 오히려 효과가 감소하는 Inverted U형 관계를 확인하였다. 또한, 각 투자단계별 벤처기업들에 공동 투자한 외부 파트너 수가 포트폴리오 운영성향과 기술혁신 효과 사이의 Inverted U형 관계를 약화시키는 조절효과를 통계적으로 실증하였다. 본 논문은 기업이 투자포트폴리오를 구성할 때 투자 단계와 경과시점을 고려할 경우 투자성과를 극대화할 수 있다는 점에서 기획 담당자, 벤처 투자자, 정책 관리자 등에 시사점을 제공할 수 있다.

• 지식경영연구
• /
• 제19권1호
• /
• pp.97-118
• /
• 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.

• 한국기술혁신학회:학술대회논문집
• /
• 한국기술혁신학회 2000년도 추계 학술대회(The 2000 Autumn Conference of korea Technology Inovation Society)(한국기술혁신학회)
• /
• pp.259-277
• /
• 2000

In this paper, we suggest theoretical grounds on the problem of R&D portfolio with different option premiums utilizing the Real Options Model, which has received intensified attention as the method of assessment of R&D project with high risk. Even though there have been many studies focused on the evaluation of option value of single project from technology valuation's perspective. there are few study on the portfolio of multiple technology investment by option value using. This paper bears practical importance by showing simple examples with the option value of investment alternatives and the valuation of related risk, the construction of optimum portfolio in technology investment alternatives.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
• /
• 제8권1호
• /
• pp.17-28
• /
• 2019

금융투자 관리 전략 중에서 여러 금융 상품을 선택하고 조합하여 분산 투자하는 것을 포트폴리오 관리 이론이라 부른다. 최근, 블록체인 기반 금융 자산, 즉 암호화폐들이 몇몇 유명 거래소에 상장되어 거래가 되고 있으며, 암호화폐 투자자들이 암호화폐에 대한 투자 수익을 안정적으로 올리기 위하여 효율적인 포트폴리오 관리 방안이 요구되고 있다. 한편 딥러닝이 여러 분야에서 괄목할만한 성과를 보이면서 심층 강화학습 알고리즘을 포트폴리오 관리에 적용하는 연구가 시작되었다. 본 논문은 기존에 발표된 심층강화학습 기반 금융 포트폴리오 투자 전략을 바탕으로 대표적인 비동기 심층 강화학습 알고리즘인 Asynchronous Advantage Actor-Critic (A3C)를 적용한 효율적인 금융 포트폴리오 투자 관리 기법을 제안한다. 또한, A3C를 포트폴리오 투자 관리에 접목시키는 과정에서 기존의 Cross-Entropy 함수를 그대로 적용할 수 없기 때문에 포트폴리오 투자 방식에 적합하게 기존의 Cross-Entropy를 변형하여 그 해법을 제시한다. 마지막으로 기존에 발표된 강화학습 기반 암호화폐 포트폴리오 투자 알고리즘과의 비교평가를 수행하여, 본 논문에서 제시하는 Deterministic Policy Gradient based A3C 모델의 성능이 우수하다는 것을 입증하였다.

• 경영과학
• /
• 제32권1호
• /
• pp.15-33
• /
• 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.

• Agribusiness and Information Management
• /
• 제8권2호
• /
• pp.9-15
• /
• 2016

In several industries, including the agriculture industry, information and communication technology (ICT) expenditure has been gradually increasing. This study explores the ICT investment of Korean agricultural corporations, and examines the effect of ICT investment on their profitability using an IT portfolio framework. As the organizational capabilities and environment in which ICT is used is critical in examining its impact, the IT-savvy level is used as a moderator. An increase in ICT investment size results in a significantly positive effect on profitability in organizations with higher IT-savvy levels, whereas there is no effect in organizations with lower IT-savvy levels. This study shows the necessity of understanding the structure of ICT investments in the agriculture industry, and suggests the importance of organizational capabilities and environment in making best use of ICT.

• 경영과학
• /
• 제26권1호
• /
• pp.37-51
• /
• 2009

Korean IT industry has been given much weight in national R&D management. A negative side of this fact is that Korean economy is likely to become vulnerable to a condition of the export business in certain items of IT industry which has a serious influence on the national economy. A customized investment strategy through the analysis of technology competitiveness and R&D status in each technology of IT field is required in order to rectify the structural vulnerability and pursue a continuous growth. In this research, a strategic direction to set up an efficient investment strategy is presented. In this process, it draws a portfolio analysis with two axes of technology level and technology life cycle. It also derives a priority order of the national investment considering the degree of technological impact, marketability, and adequacy of public support from AHP (Analytic Hierarchy Process) method by a survey of IT experts. A portfolio analysis in the prior stage helps the respondents in AHP become more familiar with the alternatives' characteristics so that their decision making process more corresponds with national R&D strategies.

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

• 한국경영과학회지
• /
• 제38권4호
• /
• pp.35-52
• /
• 2013

Markowitz's portfolio selection model is used to construct an optimal portfolio which has minimum variance, while satisfying a minimum required expected return. The model uses estimators based on analysis of historical data to estimate the returns, standard deviations, and correlation coefficients of individual stocks being considered for investment. However, due to the inaccuracies involved in estimations, the true optimality of a portfolio constructed using the model is questionable. To investigate the effect of estimation inaccuracy on actual portfolio performance, we study the changes in a portfolio's realized return and standard deviation as the accuracy of the estimations for each stock's return, standard deviation, and correlation coefficient is increased. Furthermore, we empirically analyze the portfolio's performance by comparing it with the performance of active mutual funds that are being traded in the Korean stock market and the KOSPI benchmark index, in terms of portfolio returns, standard deviations of returns, and Sharpe ratios. Our results suggest that, among the three input parameters, the accuracy of the estimated returns of individual stocks has the largest effect on performance, while the accuracy of the estimates of the standard deviation of each stock's returns and the correlation coefficient between different stocks have smaller effects. In addition, it is shown that even a small increase in the accuracy of the estimated return of individual stocks improves the portfolio's performance substantially, suggesting that Markowitz's model can be more effectively applied in real-life investments with just an incremental effort to increase estimation accuracy.