• The Korean Journal of Applied Statistics
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• v.36 no.4
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• pp.295-307
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• 2023

The heterogeneous autoregressive (HAR) model is a simple linear model that is commonly used to explain long memory in the realized volatility. However, as realized volatility has more complicated features such as conditional heteroscedasticity, leverage effect, and volatility clustering, it is necessary to extend the simple HAR model. Therefore, to better incorporate the stylized facts, we propose a threshold HAR model with GARCH errors, namely the THAR-GARCH model. That is, the THAR-GARCH model is a nonlinear model whose coefficients vary according to a threshold value, and the conditional heteroscedasticity is explained through the GARCH errors. Model parameters are estimated using an iterative weighted least squares estimation method. Our simulation study supports the consistency of the iterative estimation method. In addition, we show that the proposed THAR-GARCH model has better forecasting power by applying to the realized volatility of major 21 stock indices around the world.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.5
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• pp.659-666
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• 2023

Characterized by boom-and-bust cycles, low entry barriers, and an almost perfectly competitive structure, the construction industry presents a unique challenge for the survival and growth of its constituent companies. A crucial aspect of this challenge is the ongoing monitoring of their financial health and business performance. To understand the typical financial and operational status of construction companies, this study analyzes the financial statements of 6,252 such companies, all of which have undergone at least one external audit between 2000 and 2019. These statements were used to develop combined financial profiles and derive industry averages. The findings indicate that the construction industry experiences limited growth in sales and profitability. High leverage ratios can jeopardize financial stability, pushing companies to seek production efficiency, such as enhancing gross asset turnover. This tendency has been particularly noticeable in the aftermath of the global financial crisis in 2008.

• Korea Trade Review
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• v.46 no.2
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• pp.19-38
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• 2021

This study aims to analyze the foreign asset leverage effect on Korean oil & gas companies' foreign profits and to maintain the appropriate foreign asset volume for reducing exchange risk. For a long time, large Korean companies, including oil companies, overheld foreign currency liabilities. For this reason, most large companies have been burdened to hedge exchange risk and this excess limit holding deteriorated total profit and reduced foreign currency asset management efficiency. Our paper proceeds in presenting a three-stage analysis considering diversified exchange risk factors through estimation on transformation of foreign transactions a/c including annual trends of foreign asset and industry specifics. We also supplement incomplete the estimation method through a practical hedging case investigation. Our research parts are differentiated on the analyzing four periods considering period-specifics The FER value of the oil firms ranged from -0.3 to +2.3 over the entire period. The results of the FER Value are volatile and irregular; those results do not represent the industry standard comparative index. The Korean oil firms are over the credit limit without accurate prediction and finance high interest rate funds from foreign-owned banks on the basis on a biased relationship. Since the IMF crisis, liabilities of global firms have decreased. Above all, oil firms need to finance a minimum limit without opportunity losses on the demand forecast and prepare for uncertainty in the market. To reduce exchange risk from the over-the-limit position, we must consider factors that affect the corporate exchange risk on the entire business process, including the contract phase.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.3
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• pp.59-75
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• 2024

This study was conducted to examine the domestic and foreign street tree creation and management system. This study examined the planning, creation, and management of street trees in Seoul, Korea, Lebanon, U.S.A, Yokohama, Japan, and Paris, France. Although the work system and perception of street trees differ depending on the national administration and cultural differences, major differences and characteristics could be examined. According to the research results, each country surveyed street trees through various methods and standards, and it was confirmed that an efficient work performance system was established with quantitative standards and devices to efficiently utilize them compared to Korea. There is a limitation in representing an entire country as only one local government was considered. In addition, since laws are revised and established according to changes and needs in society, it is necessary to conduct continuous research.

• Design & Manufacturing
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• v.18 no.3
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• pp.1-8
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• 2024

Macular degeneration is a disease that damages the macula, the center of the retina, and is one of the three major eye diseases along with glaucoma and diabetic retinopathy. The optic nerve and most of the photoreceptor cells are located here, and since this is where images of objects are formed, it is the most important area for vision. The main symptom of macular degeneration is the inability to clearly distinguish the shape of objects or the inability to distinguish colors and light and dark. It is also a serious eye disease that causes black spots in the center of the field of vision. However, it is difficult to distinguish it from the form of vision loss due to presbyopia, so early diagnosis is often missed. The most common treatment for macular degeneration is antibody injection therapy. This treatment requires regular injections once every 1-2 months. When receiving antibody injection therapy, the fear of having to inject directly into the eye and the cost of long-term repeated procedures are a great burden to patients. To overcome these problems, special sustained-release formulations using drug delivery systems are being developed. Since the release speed and release time of the drug can be controlled, the number of times the drug is administered can be drastically reduced. However, the implant (Ø 0.46×6.0mm), which is a sustained-release agent, is manufactured by mixing biodegradable resin (PLGA) and therapeutic agent in a ratio of 4:6, so it is very brittle and there is a high risk of implant damage during handling. In order to safely insert the implant into the eye, a transport device that can be driven with controlled force is required. Therefore, in this study, the lever operating force was measured and analyzed to determine the influence of factors according to the cross-sectional thickness and shape of the linkage produced through injection molding as well as the post-process.

• Journal of Dental Rehabilitation and Applied Science
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• v.24 no.2
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• pp.213-230
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• 2008

The aim of this study was to analyze the initial movement and the stress distribution of each tooth and periodontal ligament during the lingual lever-arm retraction of 6 maxillary incisors using FEA. Two kinds of finite element models were produced: 2-properties model (simple model) and 24-properties model (multi model) according to the material property assignment. The subject was an adult male of 23 years old. The DICOM images through the CT of the patient were converted into the 3D image model of a skull using the Mimics (version 10.11, Materialise's interactive Medical Image Control System, Materialise, Belgium). After series of calculating, remeshing, exporting, importing process and volume mesh process was performed, FEA models were produced. FEA models are consisted of maxilla, maxillary central incisor, lateral incisor, canine, periodontal ligaments and lingual traction arm. The boundary conditions fixed the movements of posterior, sagittal and upper part of the model to the directions of X, Y, Z axis respectively. The model was set to be symmetrical to X axis. Through the center of resistance of maxilla complex, a retraction force of 200g was applied horizontally to the occlusal plane. Under this conditions, the initial movements and stress distributions were evaluated by 3D FEA. In the result, the amount of posterior movement was larger in the multi model than in the simple model as well as the amount of vertically rotation. The pattern of the posterior movement in the central incisors and lateral incisors was controlled tipping movement, and the amount was larger than in the canine. But the amount of root movement of the canine was larger than others. The incisor rotated downwardly and the canines upwardly around contact points of lateral incisor and canine in the both models. The values of stress are similar in the both simple and multi model.

• Management & Information Systems Review
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• v.34 no.3
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• pp.17-39
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• 2015

This study examined the structural changes and volatility in the global stock markets using a Markov Regime Switching ARCH model developed by the Hamilton and Susmel (1994). Firstly, the US, Italy and Ireland showed that variance in the high volatility regime was more than five times that in the low volatility, while Korea, Russia, India, and Greece exhibited that variance in the high volatility regime was increased more than eight times that in the low. On average, a jump from regime 1 to regime 2 implied roughly three times increased in risk, while the risk during regime 3 was up to almost thirteen times than during regime 1 over the study period. And Korea, the US, India, Italy showed ARCH(1) and ARCH(2) effects, leverage and asymmetric effects. Secondly, 278 days were estimated in the persistence of low volatility regime, indicating that the mean transition probability between volatilities exhibited the highest long-term persistence in Korea. Thirdly, the coefficients appeared to be unstable structural changes and volatility for the stock markets in Chow tests during the Asian, Global and European financial crisis. In addition, 1-Step prediction error tests showed that stock markets were unstable during the Asian crisis of 1997-1998 except for Russia, and the Global crisis of 2007-2008 except for Korea and the European crisis of 2010-2011 except for Korea, the US, Russia and India. N-Step tests exhibited that most of stock markets were unstable during the Asian and Global crisis. There was little change in the Asian crisis in CUSUM tests, while stock markets were stable until the late 2000s except for some countries. Also there were stable and unstable stock markets mixed across countries in CUSUMSQ test during the crises. Fourthly, I confirmed a close relevance of the volatility between Korea and other countries in the stock markets through the likelihood ratio tests. Accordingly, I have identified the episode or events that generated the high volatility in the stock markets for the financial crisis, and for all seven stock markets the significant switch between the volatility regimes implied a considerable change in the market risk. It appeared that the high stock market volatility was related with business recession at the beginning in 1990s. By closely examining the history of political and economical events in the global countries, I found that the results of Lamoureux and Lastrapes (1990) were consistent with those of this paper, indicating there were the structural changes and volatility during the crises and specificly every high volatility regime in SWARCH-L(3,2) student t-model was accompanied by some important policy changes or financial crises in countries or other critical events in the international economy. The sophisticated nonlinear models are needed to further analysis.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.38-50
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• 2020

The purpose of this study is to identify the risks to financial institutions in terms of expanding potential risks due to the deferral of exposure, by identifying the structures in which real estate finance and financial institutions affect real estate prices at low interest rates. To this end, real estate financing is categorized according to the method of financing and the type of value measurement from a risk management perspective and analyzed for each case. As a result of analysis, in the case of profitable real estate, the rate of real estate is increased by directly decreasing the cap rate and directly affecting the fair value calculation method. In the case of non-profitable real estate, the real estate price is increased by expanding the leverage width of investors or financial institutions. Through the analysis of this case, the continuous increase in real estate prices over the past 10 years has the potential to prevent financial institutions from losing under the circumstances such as the growth of real estate finance due to the advancement of the financial market and the continued low interest rate trend that has continued for 10 years. It is judged that the deferred delay is part of the cause, which leads to an increase in the risk to financial institutions.

• Journal of Service Research and Studies
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• v.7 no.1
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• pp.83-96
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• 2017

The importance of service science is emphasized in the modern economy, and the value and necessity of service research still increasing. Since the service research framework was proposed, it has been studied from various perspectives and incorporated into one framework--service research. The direction of service research has been established and a new baseline of research has been established. However, the modern economic and social environment could be described as a new era, the Fourth Industrial Revolution has changed drastically. More and more systematic research on services has become necessary. Therefore, this study analyzed the field of service research in the existing framework. The study suggested how service research could broaden the horizon of service research by studying the 'what'. To do this, we analyzed recent service research trends by themes. We also identified the shortcomings of previous studies about service, and suggested directions and research themes for future research. Based on this study we developed a general approach to the creation of new models from the viewpoint of service science. The authors were also able to develop a general approach to areas such as service innovation, service inference, service solution, and service design leverage. In addition, it is necessary to extend service research and business model to the utilization of service technology. This approach could contribute to forming the basis of future service development, and to utilize social media to create new value of innovative company. The results of this study could contribute to deepening and expanding service research.