• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.2
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• pp.899-904
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• 2013

This paper proposes an efficient portfolio selection methodology for the listed construction corporations in KOSPI and KOSDAQ. For the construction industrial sector classified by KRX(Korea Exchange), the proposed method carries out an efficiency analysis using DEA (Data envelopment analysis) approach and for the efficient corporations filtered by DEA, construct portfolio using Markowitz's Model. In order to show the effectiveness of the proposed method, we constructed annually portfolios for 5 years (2007-2011) out of 53 listed corporations in KOSPI and KOSDAQ, and proved that our portfolios are superior to benchmark portfolios in terms of rate of returns.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.1113-1122
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• 2020

The purpose of this study is to examine how the Indian banks have adjusted their risk-based capital ratios during 2009-2018 to meet the regulatory requirements. Banks can, in principle, increase their risk-based regulatory capital ratio, either by increasing their levels of regulatory capital or by shrinking their risk-weighted assets by adjusting asset growth or risk in the portfolio. We investigate banks' capital behavior by decomposing the change in the capital ratio into the contribution of its components and analyzing their variance across regulatory regimes and banks' ownerships. We further investigate how each component of the capital ratio is adjusted by the banks by breaking down them into balance sheet items. We find that the banks' capital behavior significantly differed between public and private sector banks and between the two regulatory regimes. During Basel II, banks, in general, followed a strategy of aggressive asset growth with increased risk-taking. The decline in the CRAR because of such an expansionary strategy was adjusted by augmenting additional capital. However, during Basel III, due to higher capital requirements, both in terms of quantity and quality, banks followed a strategy of cutting back their asset growth and reducing the risk in their portfolio to maintain their CRAR.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.37-50
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• 2020

Information security has become an important issue in the world. Various information and communication technologies, such as the Internet of Things, big data, cloud, and artificial intelligence, are developing, and the need for information security is increasing. Although the necessity of information security is expanding according to the development of information and communication technology, interest in information security investment is insufficient. In general, measuring the effect of information security investment is difficult, so appropriate investment is not being practice, and organizations are decreasing their information security investment. In addition, since the types and specification of information security measures are diverse, it is difficult to compare and evaluate the information security countermeasures objectively, and there is a lack of decision-making methods about information security investment. To develop the organization, policies and decisions related to information security are essential, and measuring the effect of information security investment is necessary. Therefore, this study proposes a method of constructing an investment portfolio for information security measures using game theory and derives an optimal defence probability. Using the two-person game model, the information security manager and the attacker are assumed to be the game players, and the information security countermeasures and information security threats are assumed as the strategy of the players, respectively. A zero-sum game that the sum of the players' payoffs is zero is assumed, and we derive a solution of a mixed strategy game in which a strategy is selected according to probability distribution among strategies. In the real world, there are various types of information security threats exist, so multiple information security measures should be considered to maintain the appropriate information security level of information systems. We assume that the defence ratio of the information security countermeasures is known, and we derive the optimal solution of the mixed strategy game using linear programming. The contributions of this study are as follows. First, we conduct analysis using real performance data of information security measures. Information security managers of organizations can use the methodology suggested in this study to make practical decisions when establishing investment portfolio for information security countermeasures. Second, the investment weight of information security countermeasures is derived. Since we derive the weight of each information security measure, not just whether or not information security measures have been invested, it is easy to construct an information security investment portfolio in a situation where investment decisions need to be made in consideration of a number of information security countermeasures. Finally, it is possible to find the optimal defence probability after constructing an investment portfolio of information security countermeasures. The information security managers of organizations can measure the specific investment effect by drawing out information security countermeasures that fit the organization's information security investment budget. Also, numerical examples are presented and computational results are analyzed. Based on the performance of various information security countermeasures: Firewall, IPS, and Antivirus, data related to information security measures are collected to construct a portfolio of information security countermeasures. The defence ratio of the information security countermeasures is created using a uniform distribution, and a coverage of performance is derived based on the report of each information security countermeasure. According to numerical examples that considered Firewall, IPS, and Antivirus as information security countermeasures, the investment weights of Firewall, IPS, and Antivirus are optimized to 60.74%, 39.26%, and 0%, respectively. The result shows that the defence probability of the organization is maximized to 83.87%. When the methodology and examples of this study are used in practice, information security managers can consider various types of information security measures, and the appropriate investment level of each measure can be reflected in the organization's budget.

• Journal of Technology Innovation
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• v.19 no.3
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• pp.1-29
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• 2011

Korean government built "2040 Science and Technology Future Vision" in order to show positive future scenarios and suggest a long-term guideline for a progress in science and technology. The S&T Future Vision was built based on an analysis of global megatrends and a prospect of domestic social change. After building S&T Future Vision, the "Government R&E Strategy"s was established as a follow-up action plan. The Government R&D Strategy consists of lists of future emerging technologies for future leadership, government R&D investment status and investment portfolio plans. Exploring future emerging technologies aggressively and making a governmental R&D strategic policy are requirements for national competitiveness, leadership in the world. Therefore search and selection for future emerging technologies is getting more and more important recently. Generally qualitative methodologies have been used such as expert-panel discussion method and portfolio analysis with expert valuation method in order to explore future technologies. These experts-based qualitative methodologies are well defined but lacking in some objectivity because size of expert-panels has limitations. We suggest a quantitative methodology, science mapping method to compensate this shortcoming in this study. There is another limitation related governmental R&D strategy which is that general R&D portfolios are static until a point of technology realization. We also propose a dynamic R&D investment portfolio which present different portfolios at a intermediate point and a point of technology realization. We expect this try with science mapping method and a dynamic R&D portfolio could strengthen strategic aspect of government R&D policy.

• The Journal of Information Systems
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• v.20 no.1
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• pp.127-146
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• 2011

Coping with the rapid change of competition in retail industry, retail firms have dreamed various differentiation strategy to obtain their added value and their life. And they have considered CRM strategy that can differentiate with other retail firms in order to develop some new differentiation factors. So we searched new factors that is best for "T store" and found CRM strategy such as the optimization for product portfolio considering private-brand products and the optimization for product display for customer demands. This study is meaningful in that it has suggested a new CRM strategy model, which can manage new various differentiation factors of a retail firms considering its core competence. We verified and altered retail firm's business model using system dynamics. By simulation results, CRM strategy need long time to obtain visible and satisfactory performance of "T store".

• Smart Media Journal
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• v.10 no.3
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• pp.39-47
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• 2021

Enhanced index tracking is a problem of optimizing the objective function to generate returns above the index based on the index tracking that follows the market return. In order to avoid problems such as large transaction costs and illiquidity, we used a method of constructing a portfolio by selecting only some of the stocks included in the index. Commonly used enhanced index tracking methods tried to find the optimal portfolio with only one objective function in all tested periods, but it is almost impossible to find the ultimate strategy that always works well in the volatile financial market. In addition, it is important to improve generalization performance beyond optimizing the objective function for training data due to the nature of the financial market, where statistical characteristics change significantly over time, but existing methods have a limitation in that there is no direct discussion for this. In order to solve these problems, this paper proposes ensemble learning that composes a portfolio by combining several objective functions and a 3-stage portfolio selection algorithm that can select a portfolio by applying criteria other than the objective function to the training data. The proposed method in an experiment using the S&P500 index shows Sharpe ratio that is 27% higher than the index and the existing methods, showing that the 3-stage portfolio selection algorithm and ensemble learning are effective in selecting an enhanced index portfolio.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.1
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• pp.17-28
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• 2019

In the financial investment management strategy, the distributed investment selecting and combining various financial assets is called portfolio management theory. In recent years, the blockchain based financial assets, such as cryptocurrencies, have been traded on several well-known exchanges, and an efficient portfolio management approach is required in order for investors to steadily raise their return on investment in cryptocurrencies. On the other hand, deep learning has shown remarkable results in various fields, and research on application of deep reinforcement learning algorithm to portfolio management has begun. In this paper, we propose an efficient financial portfolio investment management method based on Asynchronous Advantage Actor-Critic (A3C), which is a representative asynchronous reinforcement learning algorithm. In addition, since the conventional cross-entropy function can not be applied to portfolio management, we propose a proper method where the existing cross-entropy is modified to fit the portfolio investment method. Finally, we compare the proposed A3C model with the existing reinforcement learning based cryptography portfolio investment algorithm, and prove that the performance of the proposed A3C model is better than the existing one.

• Journal of The Korean Association of Information Education
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• v.12 no.2
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• pp.223-234
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• 2008

Educating qualified elementary school teachers depends on excellent pre-service education. The high quality of education is accomplished by various interactions between teachers and learners, as well as active participation by students. In the present study, online problem-based learning and an e-portfolio were used to examine the effect on the computer-curriculum education to reflect social and individual needs, and to enhance the quality of instruction at universities. Students (n=105) participated in six different problem-based learning sessions. At the same time, they developed Blog e-portfolios as individual and group products, and wrote reflective journals that focused on their learning processes and results. A qualitative analysis method was employed to analyze the reflective journals. The results of the analyses showed the following: 1) Increasing the understanding of the computer-curriculum education, 2) enhancing students' competence in using ICT potentially, 3) cultivating student-centered teaching and learning strategies on ICT, and 4) enhancing competence of future teaching activities through experiencing e-portfolio as a performance-assessment tool.

• Korean Journal of Construction Engineering and Management
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• v.10 no.3
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• pp.122-129
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• 2009

Strategic planning is an essential function of senior management in any business firm. Planning involves the firm's behavior in an competitive market and adaptation of the company's resources towards the selected market strategy. This study presents a methodological procedure for strategic planning in global top-tier construction firms. This procedure consists of the following stages. First, analyzed growth of revenue in which weight of total construction firms' revenue shown in Global Top 225 Contractors(ENR). Second, analyzed specialty of construction products. The products are General Building, Power, Water Supply, Industrial/Petroleum Process, and Transportation. Third, analyzed business the portfolio plan. The business portfolio plan includes both local/overseas market and specification/diversification of construction products. It affects the subsequent choice of a benchmarking for development of each construction company. The choice of the benchmarking firm, among several available alternatives, should follow a careful analysis of the characteristics and benefits inherent in the implementation of each.