• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.63-75
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• 2023

This study conducted empirical analysis on the factors affecting the investment performance of 205 domestic venture funds (with a total liquidation amount of 7.25 trillion KRW) newly formed from 2007 to 2017 and completely liquidated as of the end of 2022. Due to the nature of private equity funds, obtaining empirical data is extremely challenging, especially for data post-COVID-19 era liquidations. Nevertheless, despite these challenges, it is meaningful to analyze the impact on the investment returns of domestic venture funds using the most recent data available from the past 10 years. This study categorized the factors influencing venture fund performance into external environmental factors and internal factors. External environmental factors included "economic cycles," "stock markets," "venture markets," and "exit markets," while internal factors included the fund management company's capabilities in terms of "experience," "professional personnel," and "assets under management (AUM)." The fund structure was also categorized into "fund size" and "fund length" for comparative analysis. In summary, the analysis yielded the following results: First, the 3-year government bond yield, which represents economic cycles well, was found to have a significant impact on fund performance. Second, the average 3-month KOSDAQ index return after fund formation had a statistically significant positive effect on fund performance. Third, the number of IPOs, indicating the competition intensity at the time of venture fund liquidation, was shown to have a negative effect on fund performance. Fourth, it was observed that the larger the AUM of the fund management company, the better the fund's returns. Finally, venture fund returns showed variations depending on the year of formation (Vintage). Therefore, when individuals consider investing in venture funds, it is considered a highly effective investment strategy to construct an investment portfolio taking into account not only external environmental factors and internal fund factors but also the vintage year.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.337-345
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• 2018

The purpose of this study is to analyze the relationship between the characteristics of Korean family firms and the impact of debt financing. The analysis period was 10 years from 2004 to 2013, and the sample consisted of 4,008 non-financial firms listed on the Korea Exchange. For the analysis, the unbalanced panel data with time - series, cross - section data were formed and analyzed using panel data regression analysis. The results are as follows. First, Korean family firms use relatively less debt than non - family firms. It can be understood that family firms in which the dominant family owns and dominates the corporation are less likely to increase their debt because the agent problem is alleviated and the need for the control effect of Jensen (1986) is lowered. Second, in the verification of the packing order theory using the model proposed by Shyam-Sunder and Myers (1999), family firms have higher compliance with the packing order theory than non-family firms do. When financing is needed, debt is preferred over equity issuance. However, for Korean family firms, 24.38% of the deficit funds are financed through the issuance of net debt, which is relatively low compared to the 75% shown in the analysis of Shyam-Sunder and Myers (1999). These results reveal the limit to the strong claim that the Korean family firms follow the packing order theory.

• Proceedings of the KAIS Fall Conference
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• 2004.06a
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• pp.324-326
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• 2004

20세기 말까지만 해도 경제발전은 자원고갈과 자연환경파괴를 통한 대량생산 및 대량소비를 전제로 하여 이루어 졌다고 평가할 수 있다. 그 결과 세계의 자연환경은 급속히 훼손되었으며, 환경오염은 이제 인류의 생존을 위협하는 단계에 이르렀다. 이 같은 위기상황에 대처하기 위하여 지난 1980년대부터 선진국을 중심으로 환경경영에 대한 인식이 확산되기 시작하였다. 무엇보다도 자연환경 의 보존을 요구하는 사회적 압력은 기업으로 하여금 환경경영 의 필요성을 깨닫게 하였다. 환경 경영이란 기업들이 새로운 비교 우위를 창출하기 위하여 경 영 방식의 혁신에 있어서 자연환경을 초점으로 삼는 것이다. 환경경영이란 환경보전을 요구하는 이해 관계자들로부터의 요구에 기업이 이에 적극적으로 대응함으로써 한경보호와 경영성과를 동시에 달성하는 종합적인 경영을 의미한다. 환경경영은 이업의 전 활동에 걸친 전사적인 전략적 차원의 활동으로 기업경영이 어느 한 기능분야에 국한된 개념이 아니다. 궁극적으로 환경보호와 성장의 조화라는 기업의 목표달성을 위해 기업의 생산, 재무, 인사조직, 마케팅, 회계정보시스템등의 활동이 모두 통합되어야 할 것이다. (김종대, 이의훈:2003) 최근 들어 환경경영이 기업의 가치에 미치는 영향에 대한 연구가 활발히 전개되고 있는 가운데 선진국의 경우 기업의 가치가 대체적으로 정확하게 주가에 반영되고 있는 가운데 선진국의 경우 기업의 가치가 대체적으로 정확하게 주가에 반영되고 있어 우리기업들이게 시사하는 바가 크다 하겠다. 환경경영과 기업가치와의 상관관계를 조사한 연구결과에 따르면 우수한 환경경영을 실천하고 있는 기업의 주식을 중심으로 포트폴리오를 구성한 펀드의 수익율이 상대적으로 높게 나타나고 있어 환경경영의 중요성을 뒷받침하고 있다. 이를 위하여 본 논문은 우선적으로 기업의 환경경영에 기본이 되는 중요한 환경경제 유인정 책과 규제들을 중심으로 살펴보고자 하였다.학적 합성이 아주 까다로운 약제물질 등을 천연상태에서 합성하고 있기 때문이다. 또 식물은 lipoxygenase 효소계가 있어서 마치 천연물 석유제조공장과 같은 제조공정 capacity를 가지고 있다. 그러면 식물/식품 GMO는 안전한 것인가? 아니, KBS의 한 사회자가 말했듯이, 그리고 많은 소비자들이 믿는 것처럼 GMO는 위험한가? GMO에 대한 일반 사람들의 공포감은 Green Peace 당원들뿐만 아니라 일부 과학자들에 의해서도 조장되고 있다. 이러한 분위기 속에서 GMO에 의한 제2 녹색혁명은 Africa 대륙에서의 제1 녹색혁명이 지금도 지연되는 것과 같다고도 볼 수 있다. GMO의 환경에 대한 악영향은 과대 선전되어있는 것이 아닌가? 마치 GMO가 화학비료, 농약제보다 더 위험하다고 믿는 사람들도 많다. 나는 이러한 GMO 공포증이 과학적으로 그리고 "Risk Assessment"의 견지에서 볼 때 그 근거가 희박하다고 보여주는 몇 몇 실험 및 경험 사실들을 인용하려 한다. 그리고 올바른 Risk Assessment야 말로 한국의 21세기 BT 산업을 경쟁력 있게 하고 국민 년 소득 2만불 달성에 중요한 기여를 하게 될 것이라고 생각한다. 한국은 농토가 적고 천연자원이 빈약하다. GMO는 21세기의 생존 경쟁 산업이다. 제2의 녹색혁명은 얼마든지 가능하며, 한국은 부족한 농토와 빈약한 자원에도 불구하고 능력 있는 인적자원이 풍부하여 GMO 개발 연구에 국제적 경쟁력을 키울 수 있다. 그러나 GMO에 대한 논쟁만 하고 있으면 이미 때가 늦는다. 미국은 이미 GMO-BT 시장을 거의 완전 독점했으며, 타국에서의 논쟁과 불합리적으로 엄격한 GMO 관련 규정을 조장하고 환영한다.이상의 결과와 같이 인삼 saponin 성분들은 arachidonic acid로부터 cyclooxygenase를 통해 일단 생성된 endoperoxide에서 각각의 prostagland

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.29 no.3
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• pp.153-161
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• 2023

The worldwide effects of COVID-19 have led to a surge in online shopping and contactless services. The consumption pattern has caused the issues such as the environmental pollution together with the increase of plastic waste. Reducing the reliance on the petroleum based plastic use for the package and replacing it with environmentally friendly material are the simple ways in order to solve those problems. Paper is an eco-friendly product with high recyclability as the food packaging materials but has still poor barrier properties. A barrier coating on surface of the paper can be achieved with the proper packaging materials featuring water, gas and grease barrier. Polyethylene (PE) or polypropylene (PP) coatings which are generally laminated or coated to paper are widely used in food packaging applications to protect products from moisture and provide water or grease resistance. However, recycling of packaging containing PE or PP matrix is limited and costly because those films are difficult to degrade in the environment. This study investigated the recyclability of modified acrylic emulsion coating papers compared to PE and PP polymer matrixes as well as their mechanical and gas barrier properties. The results showed that PE or modified acrylic emulsion coated papers had better mechanical properties compared to the uncoated paper as a control. PE or PP coating papers showed strong oil resistance property, achieving a kit rating of 12. Those papers also had a significantly higher percentage of screen reject during the recycling process than modified acrylic coated paper which had a screen rejection rate of 6.25%. In addition an uncoated paper had similar value of a screen rejection rate. It may suggest that modified acrylic emulsion coating paper can be more easily recycled than PE or PP coating papers. The overall results of the study found that modified acrylic emulsion coating paper would be a viable alternative to suggest a possible solution to an environmental problem as well as enhancing the weak mechanical and poor gas barrier properties of the paper against moisture.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• The Journal of Society for e-Business Studies
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• v.23 no.3
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• pp.13-32
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• 2018

Btcoin has made a big progress through anonymity, decentralized authority, sharing economy, multi-ledger book-keeping, block-technology and the convenient financial vehicle. Bitcoin has the characteristics of mining and supply by decentralized suppliers, limited supply quantity and the partial money-like function as well as gold. The paper studies the hedge and safe-haven of Bitcoin and gold on daily frequency data over the period of July 20, 2010-Dec. 27, 2017 employing Asymmetric Vector GARCH. It finds that gold has the hedge and safe-haven against inflation and capital markets while Bitcoin has the weak hedge and the weak safe-haven. It shows insignificant effects of inflations of US and Korea on the volatilities of Bitcoin and gold. It also suggests the necessity of clearing of vagueness behind the anonymity for fair and transparent trade through the law application in the absence or fault in law (Lucken im Recht). following the spirit of the living constitution (lebendige gutes Recht oder Vorschrift). The relevant institutions are hoped to be given some of obligations such as registration, minimum required capital. report, disclosure, explanation, compliance and governance with autonomous corresponding rights. The study also suggests the reestablishment of the relevant financial law and taxation law. The hedge would not be successfully accomplished without the vigilant cautions of investors.

• Management & Information Systems Review
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• v.30 no.2
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• pp.237-255
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• 2011

This empirical study is focused on practical application of Range-Based Volatility which is estimated by opening, high, low, closing price of overall asset. Especially proper forecasting period is what I want to know. There is four useful Range-Based Volatility(RV) such as Parkinson(1980; PK), Garman and Klass(1980; GK) Rogers and Satchell(1991; RS), Yang and Zhang(2008; YZ). So, four RV of KOPSI 200 index during 2000.5.22-2009.9.18 was used for empirical test. The emprirical result as follows. First, the best RV which shows the best forecasting performance is PK volatility among PK, GK, RS, YZ volatility. According to estimating period forcasting performance of RV shows delicate difference. PK has better performance in the period with financial crisis of sub-prime mortgage loan. if not, RS is better. Second, almost result shows better performance on forecasting volatility without sub-prime mortgage loan period. so we can say that forecasting performance is lower when historical volatiltiy is comparatively high. Finally, I find that longer estimating period in AR(1) and MA(1) model can reduce forecasting error. More interesting point is that the result shows rapid decrease form 60 days to 90 days and there is no more after 90 days. So, if we forecast the volatility using Range-Based volaility it is better to estimate with 90 trading period or over 90 days.

• Journal of Distribution Science
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• v.13 no.9
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• pp.37-45
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• 2015

Purpose - This paper's aim is to investigate whether or not gross profitability explains the cross-sectional variation of the stock returns in the Korean stock market. Gross profitability is an alternative profitability measure proposed by Novy-Marx in 2013 to predict cross-sectional variation of stock returns in the US. He shows that the gross profitability adds explanatory power to the Fama-French 3 factor model. Interestingly, gross profitability is negatively correlated with the book-to-market ratio. By confirming the gross profitability premium in the Korean stock market, we may provide some implications regarding the well-known value premium. In addition, our empirical results may provide opportunities for the fund distribution industry to promote brand new styles of funds. Research design, data, and methodology - For our empirical analysis, we collect monthly market prices of all the companies listed on the Korea Composite Stock Price Index (KOSPI) of the Korea Exchanges (KRX). Our sample period covers July1994 to December2014. The data from the company financial statementsare provided by the financial information company WISEfn. First, using Fama-Macbeth cross-sectional regression, we investigate the relation between gross profitability and stock return performance. For robustness in analyzing the performance of the gross profitability strategy, we consider value weighted portfolio returns as well as equally weighted portfolio returns. Next, using Fama-French 3 factor models, we examine whether or not the gross profitability strategy generates excess returns when firmsize and the book-to-market ratio are controlled. Finally, we analyze the effect of firm size and the book-to-market ratio on the gross profitability strategy. Results - First, through the Fama-MacBeth cross-sectional regression, we show that gross profitability has almost the same explanatory power as the book-to-market ratio in explaining the cross-sectional variation of the Korean stock market. Second, we find evidence that gross profitability is a statistically significant variable for explaining cross-sectional stock returns when the size and the value effect are controlled. Third, we show that gross profitability, which is positively correlated with stock returns and firm size, is negatively correlated with the book-to-market ratio. From the perspective of portfolio management, our results imply that since the gross profitability strategy is a distinctive growth strategy, value strategies can be improved by hedging with the gross profitability strategy. Conclusions - Our empirical results confirm the existence of a gross profitability premium in the Korean stock market. From the perspective of the fund distribution industry, the gross profitability portfolio is worthy of attention. Since the value strategy portfolio returns are negatively correlated with the gross profitability strategy portfolio returns, by mixing both portfolios, investors could be better off without additional risk. However, the profitable firms are dissimilar from the value firms (high book-to-market ratio firms); therefore, an alternative factor model including gross profitability may help us understand the economic implications of the well-known anomalies such as value premium, momentum, and low volatility. We reserve these topics for future research.

• The Journal of Information Technology
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• v.1 no.2
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• pp.209-227
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• 1998

This study examines the relation between accruals components of earnings and stock return. Earnings are decomposed into four components: discretionary accruals, nondiscretionary accruals, nondiscretionary income and cash flow from operations. Because reported earnings in financial statement consist of cash flow from operations plus total accruals. We decompose total accruals into a discretionary accruals and a nondiscretionary accruals separately, This paper examines the incremental informational content of discretionary accruals and nondiscretionary accruals components of net income by regressing return on earnings'components in multivariate models. The empirical analysis is conducted on a sample of 1,580 firm-years comprising 158 firms during 1984-1995. Discretionary accruals are obtained by decomposing total accruals into discretionary and nondiscretionary accruals components, using a pooled variation of the Jones model(1991). These findings suggest that the discretionary accruals(measured using a variation the Jones model) is priced by the stock market. Specifically, the discretionary accruals and cash flow from operations are positively associated with the stock return, and also nondiscretionary income, discretionary accruals are positively associated with the stock return. While this result is consistent with the market prices the discretionary accruals because it captures value-relevant information. Additional test report evidence consistent with nondiscretionary accruals conveying information about the stock return.

• Journal of Distribution Science
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• v.13 no.5
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• pp.71-82
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• 2015

Purpose - The purpose of this study is to investigate risk price implied from the pricing kernel of Korean stock distribution market. Recently, it is considered that the quantitative easing programs of major developed countries are contributing to a reduction in global uncertainty caused by the 2007~2009 financial crisis. If true, the risk premium as compensation for global systemic risk or economic uncertainty should show a decrease. We examine whether the risk price in the Korean stock distribution market has declined in recent years, and attempt to provide practical implications for investors to manage their portfolios more efficiently, as well as academic implications. Research design, data and methodology - To estimate the risk price, we adopt a non-parametric method; the minimum norm pricing kernel method under the LOP (Law of One Price) constraint. For the estimation, we use 17 industry sorted portfolios provided by the KRX (Korea Exchange). Additionally, the monthly returns of the 17 industry sorted portfolios, from July 2000 to June 2014, are utilized as data samples. We set 120 months (10 years) as the estimation window, and estimate the risk prices from July 2010 to June 2014 by month. Moreover, we analyze correlation between any of the two industry portfolios within the 17 industry portfolios to suggest further economic implications of the risk price we estimate. Results - According to our results, the risk price in the Korean stock distribution market shows a decline over the period of July 2010 to June 2014 with statistical significance. During the period of the declining risk price, the average correlation level between any of the two industry portfolios also shows a decrease, whereas the standard deviation of the average correlation shows an increase. The results imply that the amount of systematic risk in the Korea stock distribution market has decreased, whereas the amount of industry-specific risk has increased. It is one of the well known empirical results that correlation and uncertainty are positively correlated, therefore, the declining correlation may be the result of decreased global economic uncertainty. Meanwhile, less asset correlation enables investors to build portfolios with less systematic risk, therefore the investors require lower risk premiums for the efficient portfolio, resulting in the declining risk price. Conclusions - Our results may provide evidence of reduction in global systemic risk or economic uncertainty in the Korean stock distribution market. However, to defend the argument, further analysis should be done. For instance, the change of global uncertainty could be measured with funding costs in the global money market; subsequently, the relation between global uncertainty and the price of risk might be directly observable. In addition, as time goes by, observations of the risk price could be extended, enabling us to confirm the relation between the global uncertainty and the effect of quantitative easing. These topics are beyond our scope here, therefore we reserve them for future research.