• The Korean Journal of Financial Management
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• v.26 no.1
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• pp.165-188
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• 2009

This paper has suggested the methodology for the frontier portfolios and the optimal portfolio under the mean-VaR framework, not assuming the normal distribution and considering the investor's preferences for the higher moments of return distributions. It suggested the grid and rank approach which did not need an assumption about return distributions to find the frontier portfolios. And the optimal portfolio was selected using the utility function that considered the 3rd and the 4th moments. For the application of the methodology, weekly returns of the developed countries index, the emerging market index and the KOSPI index were used. After the frontier portfolios of the mean-variance framework and the mean-VaR framework were selected, the optimal portfolios of each framework were compared. This application compared not only the difference of the standard deviation but also the difference of the utility level and the certainty equivalent expressed by weekly expected returns. In order to verify statistical significances about the differences between the mean-VaR and the mean-variance, this paper presented the statistics which were obtained by the historical simulation method using the bootstrapping. The results showed that an investor under the mean-VaR framework had a tendency to select the optimal portfolio which has bigger standard deviation, comparing to an investor under the mean-variance framework. In addition, the more risk averse an investor is, the bigger utility level and certainty equivalent he achieves under the mean-VaR framework. However, the difference between the two frameworks were not significant in statistical as well as economic criterion.

• Journal of Information Technology Applications and Management
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• v.30 no.5
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• pp.83-105
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• 2023

The purpose of this study was to investigate the impact of investment fund attributes such as fund product characteristics, returns on fund investment (ROI), internal controls, and after service on fund investor behavior based on investment information technology. In addition, we also examined how customers reinvest through emotional immersion, company trust and company satisfaction of investment firms in the context of fund investment. First, empirical results show that fund product characteristics, returns on fund investment, and financial firms' internal controls and after service act as signals to fund investors to shape their reinvestment intentions. Second, while investors are generally perceived to be interested only in investment returns, this study also shows that they consider both fund product characteristics and fund investment returns, which are core attributes of funds, as well as financial firms' internal control and after service, which are non-core attributes. Third, we find that company trust is an important factor in investors' reinvestment intentions, showing that investors are more likely to reinvest in a fund if they perceive the financial firm to be trustworthy and reliable. Finally, these findings emphasize that investors consider not only tangible aspects of fund products, such as fund product characteristics and returns on fund investment, but also intangible factors, such as financial firms' internal control and after service, and trustworthiness. Taken together, another implication is that the more advanced the investment information technology of financial firms, the more trust, satisfaction, immersion, and reinvestment intentions of investors will increase.

• The Journal of Industrial Distribution & Business
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• v.13 no.12
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• pp.23-31
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• 2022

Purpose: This research is to answer the following research questions because of the importance of learning how retired businesspeople increase their financial security and quality of life. (1) how does an entrepreneur contribute to economic development? (2) what types of investments are performed by businesspeople after retirement? (3) how entrepreneurial financial attainment capacity and anticipated net income after retirement are related? Research design, data and methodology: This research has conducted the qualitative analysis (QCA) using the current literature review. In the traditional positivist research paradigm, the quality of research is evaluated based on issues of validity, reliability, and objectivity. Contrary to the positivist approach, QCA focuses on the underlying meaning of the data. Results: This research found that finance management is increasingly challenging for businesspeople. The solutions based on the literature investigation suggest four categories. (1) Planned spending and revenue allocation, (2) Investing in the stock market, (3) Create a culture of saving, (4) Get Informed. Conclusions: This research puts forth a model to describe the connection between an investor's financial achievement potential and their desired net profits in retirement. The results of this study support the idea that the ability to achieve financial success as an entrepreneur has a salutary effect on the amount of money saved for retirement.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.2
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• pp.471-480
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• 2015

The market of public-private partnership (PPP) projects has reduced from 9.4 trillion won in 2007 to 4.5 trillion won in 2012. However, the need of PPP projects is brought up by a massive down scale of government financial business. Previous studies regarding PPP projects mostly evaluate profitability from the financial perspective or analyze risk factors as a whole. Although PPP projects generally have complex structure involving diverse stakeholders, such as contractor, financial investor, and special purpose company (SPC) operators, existing studies have rarely considered the different viewpoints of PPP project stakeholders. Therefore, purpose of this study is to develop a structural equation model (SEM) considering the diverse stakeholders of PPP projects. To this end, the authors first reviewed the organizational structure of PPP projects. Next, the identification of the factors affecting project profitability are done via comprehensive literature reviews. After that, we conducted in-depth interviews and questionnaire surveys to reflect stakeholders' perspectives (contractors, financial investors, and SPC operators). As a result, a SEM model is developed to analyze direct and indirect effect on the PPP project performances. Finally, using the analysis results, relevant implications and directions for improvements are discussed. The prediction of the business performance of contractor, financial investor, and SPC operator is expect to be possible through the model developed and supports the strategy deduction that is appropriate for the participants.

• 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.

• East Asian Economic Review
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• v.21 no.2
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• pp.147-165
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• 2017

This study quantifies the dynamic interrelationship between the KOSPI index return and search query data derived from the Naver DataLab. The empirical estimation using a bivariate GARCH model reveals that negative contemporaneous correlations between the stock return and the search frequency prevail during the sample period. Meanwhile, the search frequency has a negative association with the one-week- ahead stock return but not vice versa. In addition to identifying dynamic correlations, the paper also aims to serve as a test bed in which the existence of profitable trading strategies based on big data is explored. Specifically, the strategy interpreting the heightened investor attention as a negative signal for future returns appears to have been superior to the benchmark strategy in terms of the expected utility over wealth. This paper also demonstrates that the big data-based option trading strategy might be able to beat the market under certain conditions. These results highlight the possibility of big data as a potential source-which has been left largely untapped-for establishing profitable trading strategies as well as developing insights on stock market dynamics.

• The Korean Journal of Financial Management
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• v.26 no.4
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• pp.103-140
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• 2009

This paper investigates various channels through which liquidity can affect stock returns and examines whether behavioral explanation for liquidity risk is reasonable. First, we examine whether liquidity level (average liquidity) plays a significant role in determining asset returns. The result is consistent with the hypothesis that a stock with higher average illiquidity will have a higher expected return. Second, we focus on the argument that liquidity has a non-diversifiable systematic component. If systemic liquidity has a different impact across individual securities, a stock that is more sensitive to systematic liquidity will have a higher expected return. The results of various tests are inconsistent with each other, not completely supporting the argument. Finally, the intra-market tests in Korea support the behavioral explanation for the liquidity premium, and the effect is stronger in the liquidity level than in the liquidity beta related to systematic liquidity.

• Proceedings of the KSR Conference
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• 2004.10a
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• pp.965-970
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• 2004

The private investment on the SOC facilities is a worldwide tendency since it can supplement the insufficient investment of public finance in the construction of infrastructures. Alter the formulation of private investment law, private sector's investment on roads, harbors and environmental facilities are being progressed considerably. However, railway construction by private sector is not active comparing to the former areas because of huge investment for construction but relatively low and unpredictable benefit in operation. This paper reviews the financial, social and institutional aspects on the private investment for SOC projects, especially railway projects. Also, this paper tries to find the desirable way to expedite the private investment on railway project,. Conclusively, the paper propose that the private sector in railway projects is better constituted with financial investor and the private financing could be. activated and settled if a stable minimum benefit on their investment being ensured institutionally, for example, by BTL.

• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.889-896
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• 2012

In this paper, we propose a statistic to measure investor sentiment. It is a usual phenomenon that an asymmetric volatility (referred to as the leverage effect) is observed in financial time series and is more sensitive to bad news rather than good news. In a bubble state, investors tend to continuously speculate on financial instruments because of optimism about the future; subsequently, prices tend to abnormally increase for a long time. Estimators of the transformation parameter and the skewness based on Yeo-Johnson transformed GARCH models are employed to check whether a bubble or abnormality exist. We verify the appropriacy of the proposed interpretation through analyses of KOSPI and NIKKEI.

• Journal of Digital Convergence
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• v.18 no.7
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• pp.135-148
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• 2020

Even after successful technology development, there are many cases where commercialization fails due to difficulties in financing in the early stages of commercialization. The purpose of this study is to give practical implications to technology-based founders. At the beginning of commercialization, 7 companies that succeeded in procuring different types of external funds were selected to conduct case analysis. The results are as follow. First, it was confirmed that the excellence of technology is the most important. Second, it was confirmed that they were majors in the relevant technology field or have worked in related fields, and concluded that greater synergy effect can be created by adding the founder's business will and active attitude. Third, even if the company's internal capabilities were insufficient, it was possible to succeed in financing by identifying and utilizing external financial information. Fourth, it is necessary to utilize a linked financial system that receives both loans and investments. Fifth, systematic IR (Investor Relation) should be continued.