Journal of the Korean Society for Aviation and Aeronautics
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v.31
no.4
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pp.28-44
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2023
This study investigates aircraft lessor business models by studying cases and interviewing experts to analyze investors and business strategies of aircraft lessor. The results confirm that there is a wide range of investors including institutional investors, financial institutions, insurance companies, corporations, and wealthy individuals for aircraft lessor. Aircraft lessors can be categorized based on its required rate of return (cost of capital) into bank-investing core, institutional investor-investing value-added, and hedge fund-investing opportunistic. Aircraft lessor decides leasing rate by aircraft purchasing price and lessee's credit rating. Core aircraft lessors invest in new aircrafts for new placement or sale-and-leaseback strategy requiring little technical risk in aircraft, value-added lessors invest in middle-aged aircrafts for re-leasing, opportunistic lessors invest in old aircrafts for freighter conversion or part-out strategy requiring high level of expertise. This study provides insights for future Korean aircraft lessor establishment and investment.
In this paper, I examine whether the listed companies in Korea tend to manage operating cash flows upward via classification shifting after the adoption of K-IFRS. As proxies for cash flow management, I derive a measure of abnormal operating cash flows borrowing from Lee(2012). Alternative proxies include a series of categorical variables designed to identify the types of classification shifting of interest and dividend payments among others, in the statement of cash flows. Higher level of estimated abnormal operating cash flows, and the classification of interest/dividend payments in non-operating activity sections are considered to indicate the managerial intention to maximize reported operating cash flows. I consider several potential incentives to manage operating cash flows, which include financial distress, the credit rating proximity to investment/non-investment cutoff threshold, avoidance of negative or decreasing operating cash flows relative to previous period and so forth. In a series of empirical analyses, I do not find evidence in support of the opportunistic classification shifting explanation, inconsistent with several previous literature in Korea. In contrast, I observe negative associations between the CFO management proxies and selected incentives, which suggest that the classification is likely to represent above average cash flow performance rather than opportunistic motives exercised to maximize reported operating cash flows. I reckon that this observation is, in part, driven by the K-IFRS requirement to maintain temporal consistency in classifying interest and dividend receipts/payments in cash flow statement.
Proceedings of the Safety Management and Science Conference
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2002.11a
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pp.321-339
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2002
The result of variance decomposition through yield of Treasury of 30 year maturity of USA, S&P 500 index, stock price of KEPCO has 76.12% of impulse of KEPCO stock price at short-term horizon, but they have 51.40% at long-term horizon. After one year, they occupy 13.65%, and 33.25%. So their effects are increased. By the way, S&P 500 index and yield of Treasury of 30 year maturity of USA have relatively more effect for forecast of stock price oi KEPCO at short-term & long-term. The yield of Treasury of 30 year maturity of USA more than S&P 500 index have more effect for stock price of KEPCO. It is why. That foreign investors through fall of stock price of USA invest for emerging market is less than movement for emerging market of hedge funds through effect of fall of yield of Treasury of 30 year maturity of USA, according to relative effects for stock price of Korea companies. The result of variance decomposition through won/dollar foreign exchange rate, yield of corporate bond of 3 year maturity, Korea Stock Price index(KOSPI), stock price of KEPCO has 81.33% of impulse of KEPCO stock price at short-term horizon, but they have 41.73% at long-term horizon. After one year, they occupy 23.57% and 34.70%. So their effects are increased. By the way, KOSPI and won/dollar foreign exchange rate have relatively more effect for forecast of stock price of KEPCO at short-term & long-term. The won/dollar foreign exchange rate more than KOSPI have more effect for stock price of KEPCO. It is why. The recovery of economic condition through improvement of company revenue causes of rising of KOSPI. But, if persistence of low interest rate continues, fall of won/dollar foreign exchange rate will be more aggravated. And it will give positive effect for stock price of KEPCO. This gives more positive effect at two main reason. Firstly, through fall of won/dollar foreign exchange rate and rising of credit rating of Korea will be followed. Therefore, foreign investors will invest more funds to Korea. Secondly, inflow of foreign investment funds through profit of won/dollar foreign exchange rate and stock investment will be occurred. If appreciation of won against dollar is forecasted, foreign investors will buy won. Through this won, investors will do investment. Won/dollar foreign exchange rate is affected through external factors of yen/dollar foreign exchange rate, etc. Therefore, the exclusion of instable factors for foreign investors through rising of credit rating of Korea is necessary things.
The propose of study is to examine the characteristics of companies with high possibility to form an internal control weakness using forecasting model. This study use the actual listed/unlisted companies' data from K_financial institution. The first conclusion is that discriminant model is more valid than logit model to predict internal control weak companies. A discriminant model for predicting the vulnerability of internal control has high classification accuracy and has low the Type II error that is incorrectly classifying vulnerable companies to normal companies. The second conclusion is that the characteristic of weak internal control companies have a low credit rating, low asset soundness assessment, high delinquency rates, lower operating cash flow, high debt ratios, and minus operating profit to the net sales ratio. As not only a case of listed companies but unlisted companies which did not occur in previous studies are extended in this study, research results including the forecasting model can be used as a predictive tool of financial institutions predicting companies with high potential internal control weakness to prevent asset losses.
Korean Journal of Construction Engineering and Management
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v.13
no.6
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pp.107-120
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2012
This study is conducted so as to understand actual condition of financial difficulties confronted by construction companies in the recession of real estate market which has been continued since the financial crisis started from USA in the second half of 2008, and provide fundamental data for the establishment of policy direction. Compared with this actual condition survey with a 2008 investigation, it seems that the practice of financial institutions or credit evaluation relating parts among sections, which were pointed as problems in such investigation, are resolved to some extent. It seems that there are many causes to aggravate financial conditions as pointed at this time and such causes are related to self-problems, which are inherent to the construction business, such as the smooth settlement of construction payment, the securement of new construction projects, the limitation according to the risk inherent to the construction business, and the industry vision, etc.
The Journal of the Institute of Internet, Broadcasting and Communication
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v.14
no.6
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pp.273-279
/
2014
Recently, it was occurred in the nation's largest Information spill about 140 million cases of credit card customers' personal and credit information. As such, it was rapidly to increase in consumer complaints about the privacy of personal information in accordance with outflow of financial companies increased accident. But it is still not clear precaution. Therefore, in financial customer position, it is possible to confirm and determine in advance whether or not superior to the security company. In addition, It is time to be required institutional device that can be a real effort to equip a good security company. This report is considered a model of "Disclosure of corporate security assessment " of these devices institutional study. And We study in realistic and objective stance about why do we need this policy.
The ISP 98 is developed by the American Institute of International Banking Law & Practice in 1998. The ISP98 are also published as ICC Publication No. 590. A detailed commentary on the rules("The Official Commentary on the International Standby Practice") has been written by Professor James E. Byrnes. Presently there is no compelling reason to revise the rules themselves even if ten years is passed since the issuance of ISP98. Insteadthe American Institute of International Banking Law & Practice will provide Model Forms in the early 2009. Special features of the ISP 98 are as the following. Firstly, the ISP 98 is copyrighted by the Institute of International Banking Law and Practice, Inc., and published by the International Chamber of Commerce. Secondly, the ISP 98 differs from UCP in style and approach because it must receive acceptance not only from bankers and merchants, but also from a broader range of those actively involved in standby law and practice corporate treasurees and credit manager, rating agencies, government agencies and regulators, and indenture trustees as well as their counsel. Because standbys are often intended to be available in the event of disputes or applicant insovency, their texts are subject to a degree of scrutiny not encountered in the commercial letter of credit context. Thirdly, the ISP 98 supplement the UCP if the UCP dose not have the relative rule. Lastly, the ISP 98 has the official commentary. In addition, several provision of the ISP 98 would surprise the commercial parties and/or are rather peculiar, while some of them display a certain bias in favor of the banks.
Journal of the Korean Data and Information Science Society
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v.27
no.1
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pp.33-44
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2016
There are many situations that the outcome for clinical decision and credit assessment should be predicted more than two categories. Five kinds of statistics which are used the concordance are proposed and used for these polytomous problems. However, these statistics are defined without exact distinction of categories, so that we have difficulty to use both the pair and set approaches and it is hard to understand the meanings of these statistics. Hence, it is not possible to compare and analyze them. In this paper, the polytomous confusion matrix is standardized and the concordance statistic can be represented based on the confusion matrix. The five kinds of statistics by using the concordance are defined. With the methods proposed in this paper, we could not only explain their meanings but also compare and analyze these statistics. Based on various data sets, properties of these five statistics are explored and explained.
This study examines the possibility of implementing the technology financing for export-import based small and medium sized enterprises. Our sample consists of 2,753 small and medium sized enterprises, receiving financial support from the Export-Import Bank of Korea for the period of 2011-2013. We find that only 400(200) firms reserve IPs(patents) annually. Given that IPs are likely to concentrate on manufacturer industries such as electronic components, computers, video, sound and communication equipment manufacturing(KSIC 26), other machinery and equipment manufacturing(KSIC 29), manufacture of motor vehicles and trailers(KSIC 31). We also find that the total assets, sales and R&D expenses of IP holding companies greatly exceeds those of companies without IPs. In addition, IP holding companies' liquidity seems slight edge and the leverage ratio is somewhat lower. However, profitability ratios of IP holding companies are rather than harsh or similar level. 20~30% of IP holding firms show very week credit scores, implying that banks' default risk is expected to be significant.
Data mining has empowered the managers who are charge of the tasks in their company to present personalized and differentiated marketing programs to their customers with the rapid growth of information technology. Most studies on customer' response have focused on predicting whether they would respond or not for their marketing promotion as marketing managers have been eager to identify who would respond to their marketing promotion. So many studies utilizing data mining have tried to resolve the binary decision problems such as bankruptcy prediction, network intrusion detection, and fraud detection in credit card usages. The prediction of customer's response has been studied with similar methods mentioned above because the prediction of customer's response is a kind of dichotomous decision problem. In addition, a number of competitive data mining techniques such as neural networks, SVM(support vector machine), decision trees, logit, and genetic algorithms have been applied to the prediction of customer's response for marketing promotion. The marketing managers also have tried to classify their customers with quantitative measures such as recency, frequency, and monetary acquired from their transaction database. The measures mean that their customers came to purchase in recent or old days, how frequent in a period, and how much they spent once. Using segmented customers we proposed an approach that could enable to differentiate customers in the same rating among the segmented customers. Our approach employed support vector regression to forecast the purchase amount of customers for each customer rating. Our study used the sample that included 41,924 customers extracted from DMEF04 Data Set, who purchased at least once in the last two years. We classified customers from first rating to fifth rating based on the purchase amount after giving a marketing promotion. Here, we divided customers into first rating who has a large amount of purchase and fifth rating who are non-respondents for the promotion. Our proposed model forecasted the purchase amount of the customers in the same rating and the marketing managers could make a differentiated and personalized marketing program for each customer even though they were belong to the same rating. In addition, we proposed more efficient learning method by separating the learning samples. We employed two learning methods to compare the performance of proposed learning method with general learning method for SVRs. LMW (Learning Method using Whole data for purchasing customers) is a general learning method for forecasting the purchase amount of customers. And we proposed a method, LMS (Learning Method using Separated data for classification purchasing customers), that makes four different SVR models for each class of customers. To evaluate the performance of models, we calculated MAE (Mean Absolute Error) and MAPE (Mean Absolute Percent Error) for each model to predict the purchase amount of customers. In LMW, the overall performance was 0.670 MAPE and the best performance showed 0.327 MAPE. Generally, the performances of the proposed LMS model were analyzed as more superior compared to the performance of the LMW model. In LMS, we found that the best performance was 0.275 MAPE. The performance of LMS was higher than LMW in each class of customers. After comparing the performance of our proposed method LMS to LMW, our proposed model had more significant performance for forecasting the purchase amount of customers in each class. In addition, our approach will be useful for marketing managers when they need to customers for their promotion. Even if customers were belonging to same class, marketing managers could offer customers a differentiated and personalized marketing promotion.
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