• The Journal of Society for e-Business Studies
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• v.22 no.4
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• pp.117-128
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• 2017

The increased national utilization of Bitcoin results in multiple complications. Therefore, there are continuous debates on the subject, the main point being how to characterize Bitcoin's asset nature. The following study bases, focusing on the function value, justifies Bitcoin's asset characterization. Using regression analysis to construct relations between gold and indexes such as CPI, DXY, and S&P500 as well as the relation between Bitcoin and the previously mentioned indexes, the question of whether gold and Bitcoin reacted in a similar fashion to the same indicators was examined. The results conclude that Bitcoin has similarities with gold, showing that it is risk averse and an investable commodity in lieu to profitability when it comes to inflation and currency value. When considered with price volatility, the main force behind the function of investment asset, categorizing Bitcoin as a high-risk financial investment asset rather than as a currency within the system would be more effective for management.

• Korean Journal of Construction Engineering and Management
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• v.12 no.3
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• pp.121-130
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• 2011

Real option values of early termination payment for selected BTO PPI projects are studied using binomial models. Two cases of early termination payments are considered; an option with the condition of private participants' default, and an option without the condition. Values vary depending upon parameter values such as revenues, costs, discount rates, debt ratio, and volatility of revenues. For selected projects, the option values without the default condition are estimated as 1%~7% of total project costs, whereas the option values with the default condition are estimated as 0%~1.89% of total project cost. When actual revenues differ from the forecasted revenues, apparently the option values deviate from the values based upon the forecasted revenues. When actual revenues fall short of the forecasted revenues, the option values increase by a large amount whereas the option values decrease by a small amount in the opposite case. This implies that the option values can be quite bigger than the values based upon the forecasted revenue especially when the revenue forecast uncertainty is large. This study is expected to play an important role in improving the early termination payment option policy of the government in PPI projects in Korea.

• The Korean Journal of Applied Statistics
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• v.35 no.2
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• pp.229-250
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• 2022

Since the publication of Markowitz's (1952) mean-variance portfolio model, research on portfolio optimization has been conducted in many fields. The existing mean-variance portfolio model forms a nonlinear convex problem. Applying Dantzig's linear programming method, it was converted to a linear form, which can effectively reduce the algorithm computation time. In this paper, we proposed a Dantzig perturbation portfolio model that can reduce management costs and transaction costs by constructing a portfolio with stable and small (sparse) assets. The average return and risk were adjusted according to the purpose by applying a perturbation method in which a certain part is invested in the existing benchmark and the rest is invested in the assets proposed as a portfolio optimization model. For a covariance estimation, we proposed a Gaussian kernel weight covariance that considers time-dependent weights by reflecting time-series data characteristics. The performance of the proposed model was evaluated by comparing it with the benchmark portfolio with 5 real data sets. Empirical results show that the proposed portfolios provide higher expected returns or lower risks than the benchmark. Further, sparse and stable asset selection was obtained in the proposed portfolios.

• Communications for Statistical Applications and Methods
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• v.16 no.5
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• pp.803-812
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• 2009

The application of extreme value theory to financial data is a fairly recent innovation. The classical annual maximum method is to fit the generalized extreme value distribution to the annual maxima of a data series. An alterative modern method, the so-called threshold method, is to fit the generalized Pareto distribution to the excesses over a high threshold from the data series. A more substantial variant is to take the point-process viewpoint of high-level exceedances. That is, the exceedance times and excess values of a high threshold are viewed as a two-dimensional point process whose limiting form is a non-homogeneous Poisson process. In this paper, we apply the two-dimensional non-homogeneous Poisson process model to daily losses, daily negative log-returns, in the data series of KBW/USD exchange rate, collected from January 4th, 1982 until December 31 st, 2008. The main question is how to estimate extreme quantiles of losses such as the 10-year or 50-year return level.

• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.771-783
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• 2018

The life insurance industry is interested in various factors that influence the long-term extensions of insurance contracts such as the necessity for the advisors' long-term management of consumers, product consulting, and improvement of the investment aspects. This paper investigates important factors leading to a long-term contract that forms an important part of the life insurance industry in Korea. For this purpose we used the data of contents (i.e., data from Jan 1, 2011 to Dec 31, 2016) of the contracts of xxx insurance company. In this paper, we present how to select important variables to influence the duration of the contract maintenance via a penalized Cox's proportional hazards (PH) modelling approach using insurance life data. As the result of analysis, we found that the selected important factors were the advisor's status, the reward type 2 (annuity insurance) and tendency 4 (safety-pursuing type).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.303-304
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• 2021

In the 21st century, as we enter the Fourth Industrial Revolution, research in various fields utilizing big data is being conducted, and innovative and useful technologies are constantly emerging in the world. Among several technologies recently in the big data era, among various fields utilizing some algorithms of artificial intelligence, it shines in the field of finance and is used for pin tech, financial fraud detection and risk management, etc., and recently Even in the booming stock market, it is used for investment prediction and investment factor analysis using artificial intelligence algorithm models. In this paper, we plan to investigate various research cases and investigate trends in how they are used in the stock market through artificial intelligence that utilizes big data.

• The Journal of Engineering Geology
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• v.17 no.2 s.52
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• pp.163-176
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• 2007

Landslides which is one of the major natural hazard is defined as a mass movement of weathered material rock and debris due to gravity and can be triggered by complex mechanism. It causes enormous property damages and losses of human lift directly and indirectly. In order to mitigate landslide risk effectively, a new method is required to develope for better understanding of landslide risk based on the damaged cost produce, investment priority data, etc. In this study, we suggest a new evaluation method for slope stability using risk analysis. 30 slopes including 10 stable slopes, 10 slopes of possible failure and 10 failed slopes along the national and local roads are examined. Risk analysis comprises the hazard analysis and the consequence analysis. Risk scores evaluated by risk analysis show very clear boundaries for each category and are the highest for the failed slopes and the lowest for the stable slopes. The evaluation method for slope stability suggested by this research may define the condition and stability of slope more clearly than other methods suggested by others.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.1
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• pp.45-63
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• 2019

The number of domestic construction company is expanding every year while the construction workers' exposure to disaster risk is increasing due to technological advancements and popularity of high-rise buildings. In particular, the industry faces greater fatalities and severe large scale accidents because of construction industry characteristics including influx of foreign workers with different language and culture, large number of aged workers, outsourcing, high place work, heavy machine construction. The construction industry is labor-intensive, which is to be completed under given timeline and consists of unique working environment with a lot of night shifts. In addition, when a fixed construction budget is not secured, there is less investment in safety management resulting in poor risk management at the construction site. Taking account that the construction industry has higher accident risk rate and fatality rate, risky and unique working environment, and various labor pool from foreign to aged workers, preemptive safety management through risk factor identification is a mandatory requirement for the construction industry and site. The study analyzes about 8,500 cases of construction accidents that occurred over the past 10 years and identified risk factor by construction industry sector to secure a systematic insight for risk management. Based on interrelation analysis between accident types, work types, original cause materials and assailing materials, there is correlation between each analysis factor and work industry. Especially for work types, there is great correlation between work tasks and industry type. For reinforced concrete and earthwork are among the most frequent types of accidents, and they are not only high in frequency of accidents, but also have a high risk in categories of occurrence.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.17-25
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• 2017

Owing to recent climate change, the scale of rainfall tends to increase gradually and the risk of flooding has increased. Therefore, the importance of improving the levee management and disaster response is increasing. Levee management in Korea is carried out at the level of damage recovery after the occurrence of damage. Therefore, it is necessary to develop a technology for predicting and managing the levee safety with proactive river management. In this study, a method to estimate the safety against erosion and overflow was suggested. A map of levee safety that can be used as basic data is presented by displaying the levee safety on the map. The levee erosion safety was calculated as the ratio of the internal and external force for each shore type. The levee overflow safety was calculated as the ratio of the maximum conveyance and design flood. The maximum conveyance was a discharge when the level of the river was equal to the level of the levee crown. The levee safety was classified into 5 grades: very safe, safe, normal, dangerous, and very dangerous. As a research area from downstream of Nam River Dam to Nakdong River Junction, the levee safety against erosion and overflow was estimated for all levees and all cross-sections of the river. The levee safety was displayed on a map using GIS. Through the levee safety map as a result of this study, the levee safety can be observed intuitively. Using the levee safety map, a maintenance plan for a river can be easy to build. This levee safety map can be used to help determine the priority of investment for efficient budget used.

• Korean Journal of Construction Engineering and Management
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• v.11 no.3
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• pp.134-144
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• 2010

In China, the enhancement of water services has become the most crucial issue confronted with the rapid urbanization and industrialization process. A huge financial gap to meet the demand for water infrastructure and need for adopting advanced operation technology precipitated the rapid growth of PPP over the last 10 years. Diverse schemes of PPP such as TOT, Divestiture, and Management Contract and Lease have been practiced. Local governments and private investors/operator have adjusted their objectives and strategies to avoid potential pitfalls behind BOT projects in China. However, current academic research outcomes do not properly reflect important issues of BOT projects or related case studies in China. This limitation has brought in the lack of assessment of important risks and success factors required for the improvement of the body of risk management. In this regard, this study uses the market analysis method to identify major schemes of PPP water projects and conducts case studies on five PPP projects to identify key risk and success factors in association with each different scheme. It is expected that the risk and success factors identified from the cases will be used as reference to Korean companies which plan to enter the Chinese water market.