• Journal of Navigation and Port Research
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• v.44 no.2
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• pp.119-127
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• 2020

In this study, the current state of management efficiency of ocean carriers in Korea and the factors affecting them were analyzed. The purpose of this research is to enhance global competitiveness of ocean carriers by presenting suggestions that can improve management efficiency based on the analysis results. The measurement of management efficiency was made using the DEA model. The results of testing the adequacy of the input and output variables used are as follows. Appropriate inputs are total assets, cost of goods sold, charter expenses, sales and general management expenses, and interest expenses. Appropriate variables are sales, operating income, and operating cash flow. According to the analysis results of the DEA model by these variables, inefficient carriers (78%) are nearly four times more than efficient carriers(22%). However, container carriers have the most improved management efficiency compared to 2016 and 2017. According to the panel regression analysis, the charter rate has the greatest negative impact on efficiency (CRS), and the debt rate has a significant negative impact. Thus, it appears that reducing the charter size and the debt-to-sale rate facilitate improvement of the management efficiency of ocean carriers. Additionally, the pre-sales tax return rate, value added rate, total asset turnover rate, and the scale variable and interest coverage rate have a positive (+) effect. Thus ocean carriers should restore their global competitiveness by improving management efficiency by securing stable cargoes increasing sales profitability from the cost management perspective, increasing productivity, and enhancing the efficiency of their total assets through efficient fleet management.

• Strategy21
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• s.36
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• pp.5-32
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• 2015

Geopolitics or Political Geography is an essential academic field that should be studied carefully for a more comprehensive analysis of international security relations. However, because of its tarnished image as an ideology that supported the NAZI German expansion and aggression, geopolitics has not been regarded as a pure academic field and was rejected and expelled from the academic communities starting from the Cold War years in 1945. During the Cold War, ideology, rather than geography, was considered more important in conducting and analyzing international relations. However, after the end of the Cold War and with the beginning of a new era in which territorial and religious confrontations are taking place among nations - including sub national tribal political organizations such as the Al Quaeda and other terrorist organizations - geopolitical analysis again is in vogue among the scholars and analysts on international security affairs. Most of the conflicts in international relations that is occurring now in the post-Cold War years can be explained more effectively with geopolitical concepts. The post - Cold War international relations among East Asian countries are especially better explained with geopolitical concepts. Unlike Europe, where peaceful development took place after the Cold War, China, Japan, Korea, the United States, Taiwan and Vietnam are feeling more insecure in the post-Cold War years. Most of the East Asian nations' economies have burgeoned during the Cold War years under the protection of the international security structure provided by the two superpowers. However, after the Cold War years, the international security structure has not been stable in East Asia and thus most of the East Asian nations began to build up stronger military forces of their own. Because most of the East Asian nations' national security and economy depend on the oceans, these nations desire to obtain more powerful navies and try to occupy islands, islets, or even rocks that may seem like a strategic asset for their economy and security. In this regard, the western Pacific Ocean is becoming a place of confrontation among the East Asian nations. As Robert Kaplan, an eminent international analyst, mentioned, East Asia is a Seascape while Europe is a Landscape. The possibility of international conflict on the waters of East Asia is higher than in any other period in East Asia's international history.

• International Area Studies Review
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• v.12 no.2
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• pp.79-97
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• 2008

After entering into the WTO in October, 2001, China started opening her bank industry on a full scale and her financial markets from the end of 2006. It is true that the Chinese commercial banks should make efforts to enhance their operational efficiency for adapting the rapid change of financial environments. In this paper, the efficiency of 4 Chinese state-owned commercial banks and 11 share holding commercial banks has been estimated. Our Tobit model to find out the determinants of these banks' efficiency. The results are as follows: The efficiency of these banks kept being improved from 1999 to 2003. With regard to the relationship between the determinants and the bank efficiency, their capital ratios, ownership structures and government subsidies are significant at the 5% level while the return on asset(ROA) is significant at the 10% level. The relationship between the determinants and the efficiency has showed that the size, capital ratios, ROA and ownership structure showed significantly before the entry to WTO, on the other hand, after WTO their capital ratios are the only factor to determine their efficiencies.

• The Korean Journal of Financial Management
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• v.20 no.2
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• pp.95-126
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• 2003

This paper introduces multifractal processes and presents the empirical investigation of the multifractal asset pricing. The multifractal stock price process contains long-tails which focus on Levy-Stable distributions. The process also contains long-dependence, which is the characteristic feature of fractional Brownian motion. Multifractality introduces a new source of heterogeneity through time-varying local reqularity in the price path. This paper investigates multifractality in stock prices. After finding evidence of multifractal scaling, the multifractal spectrum is estimated via the Legendre transform. The distinguishing feature of the multifractal process is multiscaling of the return distribution's moments under time-resealing. More intensive study is required of estimation techniques and inference procedures.

• The Korean Journal of Financial Management
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• v.24 no.4
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• pp.1-43
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• 2007

The traditional Black-Scholes model for option pricing is based on the assumption that the log-return of the underlying asset follows a Brownian motion. But this assumption has been criticized for being unrealistic. Thus, for the last 20 years, many attempts have been made to adopt different stochastic processes to derive new option pricing models. The option pricing models based on L$\acute{e}$vy processes are being actively studied originating from the Gerber-Shiu model driven by H. U. Gerber and E. S. W. Shiu in 1994. In 2004, G. H. L. Cheang derived an option pricing model under multiple L$\acute{e}$vy processes, enabling us to adopt drift and jumps to the Gerber-Shiu model, while Gerber and Shiu derived their model under one L$\acute{e}$vy process. We derive the Gerber-Shiu model which includes drift and jumps under L$\acute{e}$vy processes. By adopting a Gamma distribution, we expand the Heston model which was driven in 1993 to include jumps. Then, using KOSPI200 index option data, we analyze the price-fitting performance of our model compared to that of the Black-Scholes model. It shows that our model shows a better price-fitting performance.

• The Journal of the Korea Contents Association
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• v.18 no.10
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• pp.490-497
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• 2018

In this study, we examined whether common idiosyncratic volatility(CIV), a risk factor for idiosyncratic volatility, can be evaluated as a pricing factor. The sample is listed on the Korea Exchange. The analysis period is 288 months from July 1992 to June 2016. The main results of this study are as follows. First, in the empirical verification of the market excess returns of the testing portfolios, the difference in the return on the CIV factor sensitivity difference was statistically significant. In other words, we confirmed that there is a risk premium for CIV factors. Second, CAPM, FF3 factor model, and FF5 factor model do not explain the risk premium for CIV factors, whereas factor models that add CIV factors explain the risk premium for CIV factors. In other words, the CIV factor can be evaluated in terms of pricing factors.

• The Journal of Information Systems
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• v.12 no.2
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• pp.57-72
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• 2003

The purpose of this paper is to propose the modeling of multiagent based SCM and implement the prototype in the Internet environment. SCM process follows the supply chain operations reference (SCOR) model which has been suggested by Supply Chain Counsil. SCOR model has been positioned to become the industry standard for describing and improving operational process in SCM. Five basic processes, plan, source, matte, deliver and return are defined in the SCOR model, through which a company establishes its supply chain competitive objectives. A supply chain is a world wide network of suppliers, factories, warehouses, distribution centers and retailers through which raw materials are acquired, transformed or manufactured and delivered to customers by autonomous or semiautonomous process. With the pressure from the higher standard of customer compliance, a frequent model change, product complexity and globalization, the combination of supply chain process with an advanced infrastructure in terms of multiagent systems have been highly required. Since SCM is fundamentally concerned with coherence among multiple decision makers, a multiagent framework based on explicit communication between constituent agents such as suppliers, manufacturers, and distributors is a natural choice. Multiagent framework is defined to perform different activities within a supply chain. Dynamic and changing functions of supply chain can be dealt with multi-agent by cooperating with other agents. In the areas of inventory management, remote diagnostics, communications with field workers, order fulfillment including tracking and monitoring, stock visibility, real-time shop floor data collection, asset tracking and warehousing, customer-centric supply chain can be applied and implemented utilizing multiagent. In this paper, for the order processing event between the buyer and seller relationship, multiagent were defined corresponding to the SCOR process. A prototype system was developed and implemented on the actual TCP/IP environment for the purchase order processing event. The implementation result assures that multiagent based SCM enhances the speed, visibility, proactiveness and responsiveness of activities in the supply chain.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1479-1494
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• 2015

Since the Markowitz's mean-variance framework for portfolio analysis, the topic of portfolio optimization has been an important topic in finance. Traditional approaches focus on maximizing the expected return of the portfolio while minimizing its variance, assuming that risky asset returns are normally distributed. The normality assumption however has widely been criticized as actual stock price distributions exhibit much heavier tails as well as asymmetry. To this extent, in this paper we employ the genetic algorithm to find the optimal portfolio under the Value-at-Risk (VaR) constraint, where the tail of risky assets are modeled with the generalized Pareto distribution (GPD), the standard distribution for exceedances in extreme value theory. An empirical study using Korean stock prices shows that the performance of the proposed method is efficient and better than alternative methods.

• Health Policy and Management
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• v.29 no.1
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• pp.27-39
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• 2019

Background: This study is designed to estimate the factors that affect the level of three different performance (publicity, efficiency, profitability) among regional public hospitals. Methods: The units of analysis are the regional 30 hospitals, which have the operating data during 22 years (from 1933 to 2014). The research method is used by fixed panel analysis. The publicity is measured by medicaid outpatient proportion and medicaid inpatient proportion. The efficiency is measured by two types of efficient score by DEA (data envelopment analysis). The profitability is measured by medical income to medical revenue and ROA (return on total asset). Results: At first, the increase of bed gives negative affect to the publicity but give positive effect to the efficiency and profitability. Because it means the increase of the region population, it gives more profitability compare to hospital with small number of beds. The more the operating period is the higher effect to the publicity and efficiency because of it's refutation. The debt ratio gives negative effect to publicity, but positive effect to profitability. It is the normal belief that there is inverse relationship between publicity and profitability. The turnover rate of bed gives the negative affect to the publicity, but positive affect to the efficiency and profitability. That give us the implication that type of the inpatient make different effect the hospital performance. The ratio of labor cost give negative effect to all kind of performance. That means that the higher labor cost don't mean the higher publicity and labor cost control is very important factors to hospital performance. So the region hospital have to focus the labor factors more to make higher performance. Conclusion: As the conclusion, the independent variables give similar effect to the efficiency and the profitability, but give inverse effect to the publicity. That means that if an region hospital want to make the more publicity, it loss the higher efficiency and profitability. Specially publicity is higher negative relation with the profitability.

• 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.