• Title/Summary/Keyword: portfolio investment

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A Study on the Analysis of Optimal Asset Allocation and Welfare Improvemant Factors through ESG Investment (ESG투자를 통한 최적자산배분과 후생개선 요인분석에 관한 연구)

  • Hyun, Sangkyun;Lee, Jeongseok;Rhee, Joon-Hee
    • Journal of Korean Society for Quality Management
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    • v.51 no.2
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    • pp.171-184
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    • 2023
  • Purpose: First, this paper suggests an alternative approach to find optimal portfolio (stocks, bonds and ESG stocks) under the maximizing utility of investors. Second, we include ESG stocks in our optimal portfolio, and compare improvement of welfares in the case with and without ESG stocks in portfolio. Methods: Our main method of analysis follows Brennan et al(2002), designed under the continuous time framework. We assume that the dynamics of stock price follow the Geometric Brownian Motion (GBM) while the short rate have the Vasicek model. For the utility function of investors, we use the Power Utility Function, which commonly used in financial studies. The optimal portfolio and welfares are derived in the partial equilibrium. The parameters are estimated by using Kalman filter and ordinary least square method. Results: During the overall analysis period, the portfolio including ESG, did not show clear welfare improvement. In 2017, it has slightly exceeded this benchmark 1, showing the possibility of improvement, but the ESG stocks we selected have not strongly shown statistically significant welfare improvement results. This paper showed that the factors affecting optimal asset allocation and welfare improvement were different each other. We also found that the proportion of optimal asset allocation was affected by factors such as asset return, volatility, and inverse correlation between stocks and bonds, similar to traditional financial theory. Conclusion: The portfolio with ESG investment did not show significant results in welfare improvement is due to that 1) the KRX ESG Leaders 150 selected in our study is an index based on ESG integrated scores, which are designed to affect stability rather than profitability. And 2) Korea has a short history of ESG investment. During the limited analysis period, the performance of stock-related assets was inferior to bond assets at the time of the interest rate drop.

Investment strategy using AESG rating: Focusing on a Korean Market

  • KIM, Eunchong;JEONG, Hanwook
    • The Journal of Industrial Distribution & Business
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    • v.13 no.1
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    • pp.23-32
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    • 2022
  • Purpose: This study used ESG grade, but defined AESG, adjusted to the size of a company and examines whether it can be used as an investment strategy. Research design, data and methodology: The analysis sample in this study is a company that has given an ESG rating among companies listed on the Korea Stock Exchange. We examine the results through portfolio analysis and Fama-macbeth regression analysis. Results: As result of examining the long-only performance and the long-short performance by constructing quintile portfolios, it was observed that a significant positive return was shown. It was observed that there was an alpha that could not be explained in asset pricing models. Also, AESG had a return prediction effect in the result of a Fama-Macbeth regression that controlled corporate characteristic variables in individual stocks. Next, we confirmed AESG's usage through various portfolio composition. In the portfolio optimization, the Risk Efficient method was the most superior in terms of sharpe ratio and the construct multi-factor model with Value, Momentum and Low Vol showed statistically significant performance improvement. Conclusions: The results of this study suggest that it can be helpful in ESG investment to reflect the ESG rating of relatively small companies more through the scale adjustment of the ESG rating (i.e.AESG).

A Study on DRL-based Efficient Asset Allocation Model for Economic Cycle-based Portfolio Optimization (심층강화학습 기반의 경기순환 주기별 효율적 자산 배분 모델 연구)

  • JUNG, NAK HYUN;Taeyeon Oh;Kim, Kang Hee
    • Journal of Korean Society for Quality Management
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    • v.51 no.4
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    • pp.573-588
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    • 2023
  • Purpose: This study presents a research approach that utilizes deep reinforcement learning to construct optimal portfolios based on the business cycle for stocks and other assets. The objective is to develop effective investment strategies that adapt to the varying returns of assets in accordance with the business cycle. Methods: In this study, a diverse set of time series data, including stocks, is collected and utilized to train a deep reinforcement learning model. The proposed approach optimizes asset allocation based on the business cycle, particularly by gathering data for different states such as prosperity, recession, depression, and recovery and constructing portfolios optimized for each phase. Results: Experimental results confirm the effectiveness of the proposed deep reinforcement learning-based approach in constructing optimal portfolios tailored to the business cycle. The utility of optimizing portfolio investment strategies for each phase of the business cycle is demonstrated. Conclusion: This paper contributes to the construction of optimal portfolios based on the business cycle using a deep reinforcement learning approach, providing investors with effective investment strategies that simultaneously seek stability and profitability. As a result, investors can adopt stable and profitable investment strategies that adapt to business cycle volatility.

Long Term Impact of Distribution Information Technology Investment on Firm Value (무선인식 유통정보기술 투자가 장기 주가수익률에 미치는 영향에 관한 연구)

  • Son, Sam-Ho
    • Journal of Distribution Science
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    • v.17 no.3
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    • pp.69-83
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    • 2019
  • Purpose - This paper investigates the long term impact of RFID investment on firm value in Korea. We wand to find out why the long term performance of some firm's RFID investment is better than others. To understand the dynamics of the long term returns from RFID investment announcements, we divide our events into groups for each of the independent firm characteristic variable such as investment time period, kind of markets, industries, solvency and growth potential. We composed portfolios based on the RFID investment announcement date for each group and evaluate the monthly abnormal excess returns. Research design, data, and methodology - Based on these calendar-time portfolios, we measure the long term returns from 86 RFID investment announcements of 46 firms from 2003 to 2017. We construct the calendar-time portfolio for 3, 6, 9, 12 months of holding periods. Using the weighted least squares method, we regress the raw monthly returns of the portfolios on the Fama-French model and Carhart(1997) model. As a result, we can get the estimated risk adjusted mean monthly abnormal excess return αP for each of the calendar-time portfolio. Results - We found that early adopters, large firms, non-manufacturing firms have very significant excess returns. We also found modestly significant excess returns for financially stable firms and slow growing firms. Put together, top managers of the firms which plan to invest RFID should understand the strategic role of RFID adoption and the generalized business process of distribution information technology investment in Korea. Moreover, the findings of this paper provide useful trading strategies to the managers of large funds who are considering on investing in RFID adopting firms. Conclusions - Put together, the results of this paper give us a new insight into how the RFID and IT technology in general and other characteristic factors' interactions affect the long term performance of firms. Using the unbiased estimates of long term returns of the calendar-time portfolios, this paper extends the understandings on short term impact of RFID adoption of existing studies. This paper also extends the current understandings of firm characteristics that affect the long term performance of RFID adopting firms.

국가연구개발사업 평가에서 사회연결망 분석 활용 방안

  • Gi, Ji-Hun
    • Proceedings of the Korea Technology Innovation Society Conference
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    • 2017.11a
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    • pp.129-129
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    • 2017
  • In planning and evaluating government R&D programs, one of the first steps is to understand the government's current R&D investment portfolio - which fields or topics the government is now investing in in R&D. Analysis methods of an investment portfolio of government R&D tend traditionally to rely on keyword searches or ad-hoc two-dimensional classifications. The main drawback of these approaches is their limited ability to account for the characteristics of the whole government investment in R&D and the role of individual R&D program in it, which tends to depend on the relationship with other programs. This paper suggests a new method for mapping and analyzing government investment in R&D using a combination of methods from natural language processing (NLP) and network analysis. The NLP enables us to build a network of government R&D programs whose links are defined as similarity in R&D topics. Then methods from network analysis show the characteristics of government investment in R&D, including major investment fields, unexplored topics, and key R&D programs which play a role like a hub or a bridge in the network of R&D programs, which are difficult to be identified by conventional methods. These insights can be utilized in planning a new R&D program, in reviewing its proposal, or in evaluating the performance of R&D programs. The utilized (filtered) Korean text corpus consists of hundreds of R&D program descriptions in the budget requests for fiscal year 2017 submitted by government departments to the Korean Ministry of Strategy and Finance.

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Selecting Information Technology Projects in Non-linear Risk/Return Relationships of IT Investment

  • Cho, Wooje;Song, Minseok
    • Journal of Information Technology and Architecture
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    • v.9 no.1
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    • pp.21-31
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    • 2012
  • We focus on the issues of the non-linear return/risk relationship of IT investment and the balance between return and risk of IT portfolio. We develop an IT project selection model by integrating DEA models with Markowitz portfolio selection theory. The project data collected from a Fortune 100 company are used to illustrate the implementation of the model. In addition, computational experiments are conducted to demonstrate the validity of the proposed model.

An Empirical Study on the Risk Diversification Effect of REITs (리츠의 투자위험 분산화 효과에 대한 실증연구)

  • Cho, Kyu-Su;Lee, Sang-Hyo;Kim, Jae-Jun
    • Korean Journal of Construction Engineering and Management
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    • v.14 no.1
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    • pp.23-31
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    • 2013
  • Following the U.S sub-prime mortgage crisis and a slump in properties market, the probability is rising that housing investment would not yield high profit as it used to do until early 2000s. For this reason, the nature of properties market is undergoing a change from a source of lucrative investment to a source of a relatively low but stable profit, such as profit-oriented real estate. This trend is likely to promote REITs market, which is a leading product for indirect investment. Until now, the REITs market has been growing slowly compared to a general housing market or financial markets. However, as the importance of risk management based on portfolio theories increases, stable profit generation of REITs can be effective in risk management. This study conducts an empirical analysis on how investment risks can be diversified by including REITs-a source of relatively stable profit in the equity market-in investment portfolio. The analysis results showed that, similar to food and beverage stocks of highly defensive nature, REITs has a relatively weak correlation with KOSPI that reflects the overall market performance. It also showed very low standard deviation in case of minimum variance portfolio. This suggests that including REITs in investment portfolio can be as effective as including food and beverage stocks for risk diversification. Due to uncertainties, investment always accompanies risks, and balancing potential profits and risks is essential.

Development and Evaluation of an Investment Algorithm Based on Markowitz's Portfolio Selection Model : Case Studies of the U.S. and the Hong Kong Stock Markets (마코위츠 포트폴리오 선정 모형을 기반으로 한 투자 알고리즘 개발 및 성과평가 : 미국 및 홍콩 주식시장을 중심으로)

  • Choi, Jaeho;Jung, Jongbin;Kim, Seongmoon
    • Korean Management Science Review
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    • v.30 no.1
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    • pp.73-89
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    • 2013
  • This paper develops an investment algorithm based on Markowitz's Portfolio Selection Theory, using historical stock return data, and empirically evaluates the performance of the proposed algorithm in the U.S. and the Hong Kong stock markets. The proposed investment algorithm is empirically tested with the 30 constituents of Dow Jones Industrial Average in the U.S. stock market, and the 30 constituents of Hang Seng Index in the Hong Kong stock market. During the 6-year investment period, starting on the first trading day of 2006 and ending on the last trading day of 2011, growth rates of 12.63% and 23.25% were observed for Dow Jones Industrial Average and Hang Seng Index, respectively, while the proposed investment algorithm achieved substantially higher cumulative returns of 35.7% in the U.S. stock market, and 150.62% in the Hong Kong stock market. When compared in terms of Sharpe ratio, Dow Jones Industrial Average and Hang Seng Index achieved 0.075 and 0.155 each, while the proposed investment algorithm showed superior performance, achieving 0.363 and 1.074 in the U.S. and Hong Kong stock markets, respectively. Further, performance in the U.S. stock market is shown to be less sensitive to an investor's risk preference, while aggressive performance goals are shown to achieve relatively higher performance in the Hong Kong stock market. In conclusion, this paper empirically demonstrates that an investment based on a mathematical model using objective historical stock return data for constructing optimal portfolios achieves outstanding performance, in terms of both cumulative returns and Sharpe ratios.

The Relationships among Orientations of IT Strategy, Directions of IT Portfolio, and IT Performance

  • Kang Taegyung;Park Sanghyuk
    • Proceedings of the Korea Association of Information Systems Conference
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    • 2004.11a
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    • pp.201-208
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    • 2004
  • Many organizations experience that the Performance they gained from IT portfolio is lower than they expected values. As with any investment, executives are concerned with maximizing the performance from their investment in IT. This study focused on the relationship or fit between orientations of IT strategy and directions of IT portfolio to maximize IT performance. A field survey of chief information officers of Korea manufacturing sector was conducted in 2003. Complete data of 147 firms was analyzed to determine relationship among the three research constructs that are orientations of IT strategy, directions IT portfolio, and IT performance. In this study, the orientations of IT strategy have two dimensions that are operation orientation and market orientation. The directions of IT portfolio have two dimension that are internal system focused and external system focused. And the IT performance has divided into operational performance and competitive performance. As a result of this study, the companies that are putting a focus with operation orientation were concentrated on internal information systems than external information systems. On the other hand, the other companies that are focused on market orientation were concentrated on external information systems than internal information systems. Consequently, the companies that are focused on operation orientation were operational performance higher than competitive performance and the other companies that are focused on market orientation were competitive performance higher than operational performance. More importantly, the research results provide empirical evidence that supports the hypothesis related to closer fit between IT strategy and IT portfolio does lead to increase operational and competitive performance of IT. And the results emphasize manager's efforts of fit between orientations of IT strategy and directions of IT portfolio to be realized IT performance.

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A Simulation Study of the Investment Strategy in Stocks on Fundamental Analysis (기본적 분석방법을 통한 주식 투자 전략에 관한 시뮬레이션 연구)

  • Gu, Seung-Hwan;Jang, Seong-Yong
    • Korean Management Science Review
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    • v.29 no.2
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    • pp.53-64
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    • 2012
  • This paper is about the investment strategy in stocks on Fundamental analysis. Financial data of stocks from January 2. 2001 through October 30. 2009 were utilized in order to suggest the investment strategies. Fundamental analysis was used in stocks-related strategy. The portfolios are composed of 3 criteria such as the buying criteria score, exchange cycle and selling conditions. The buying criteria score is determined assigned to each stock index according to the satisfaction condition of 15 parameters selected considering the grue's criteria. The stock buying alternatives has two options with buying stocks over 13 points and over 14 points of buying criteria score. The seven exchange cycles and three selling methods are considered. So total number of portfolios is 42($2{\times}7{\times}3=42$). The simulation has been executed about each 42 portfolios and we figured out with the simulation result that 83.33% of 35 portfolios are more profitable than average stock market profit(203.43%). The outcome of this research is summarized in two parts. First, it's the exchange strategy of portfolio. The result shows that value-oriented investment (long-term investment) strategy yields much higher than short-term investment strategies of stocks. Second, it's about the exchange cycle forming the portfolios. The result shows that the rate of return for the portfolio is the best when exchange cycle is 18 months.