• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.123-139
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• 2019

The Korean NPL market was formed by the government and foreign capital shortly after the 1997 IMF crisis. However, this market is short-lived, as the bad debt has started to increase after the global financial crisis in 2009 due to the real economic recession. NPL has become a major investment in the market in recent years when the domestic capital market's investment capital began to enter the NPL market in earnest. Although the domestic NPL market has received considerable attention due to the overheating of the NPL market in recent years, research on the NPL market has been abrupt since the history of capital market investment in the domestic NPL market is short. In addition, decision-making through more scientific and systematic analysis is required due to the decline in profitability and the price fluctuation due to the fluctuation of the real estate business. In this study, we propose a prediction model that can determine the achievement of the benchmark yield by using the NPL market related data in accordance with the market demand. In order to build the model, we used Korean NPL data from December 2013 to December 2017 for about 4 years. The total number of things data was 2291. As independent variables, only the variables related to the dependent variable were selected for the 11 variables that indicate the characteristics of the real estate. In order to select the variables, one to one t-test and logistic regression stepwise and decision tree were performed. Seven independent variables (purchase year, SPC (Special Purpose Company), municipality, appraisal value, purchase cost, OPB (Outstanding Principle Balance), HP (Holding Period)). The dependent variable is a bivariate variable that indicates whether the benchmark rate is reached. This is because the accuracy of the model predicting the binomial variables is higher than the model predicting the continuous variables, and the accuracy of these models is directly related to the effectiveness of the model. In addition, in the case of a special purpose company, whether or not to purchase the property is the main concern. Therefore, whether or not to achieve a certain level of return is enough to make a decision. For the dependent variable, we constructed and compared the predictive model by calculating the dependent variable by adjusting the numerical value to ascertain whether 12%, which is the standard rate of return used in the industry, is a meaningful reference value. As a result, it was found that the hit ratio average of the predictive model constructed using the dependent variable calculated by the 12% standard rate of return was the best at 64.60%. In order to propose an optimal prediction model based on the determined dependent variables and 7 independent variables, we construct a prediction model by applying the five methodologies of discriminant analysis, logistic regression analysis, decision tree, artificial neural network, and genetic algorithm linear model we tried to compare them. To do this, 10 sets of training data and testing data were extracted using 10 fold validation method. After building the model using this data, the hit ratio of each set was averaged and the performance was compared. As a result, the hit ratio average of prediction models constructed by using discriminant analysis, logistic regression model, decision tree, artificial neural network, and genetic algorithm linear model were 64.40%, 65.12%, 63.54%, 67.40%, and 60.51%, respectively. It was confirmed that the model using the artificial neural network is the best. Through this study, it is proved that it is effective to utilize 7 independent variables and artificial neural network prediction model in the future NPL market. The proposed model predicts that the 12% return of new things will be achieved beforehand, which will help the special purpose companies make investment decisions. Furthermore, we anticipate that the NPL market will be liquidated as the transaction proceeds at an appropriate price.

• Environmental and Resource Economics Review
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• v.17 no.3
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• pp.135-166
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• 2008

This paper reports the empirical results of comparing the willingness to pay(WTP) for health risk reductions and the willingness to accept(WTA) for risk increases using experimental market methods in the first time in Korea. Health risks were defined as probabilities of premature death from exposure to one of As, Pb, and THM in tap water. A total of six experimental markets with 15 participants in each experiments were held using 20 repetitive Vickrey second-price sealed-bid auctions. To compare the effects of market experiences, trading a marketed good, candy bar, was introduced before the trading the non-marketed good, drinking water risks. Moreover, an objective risk information was provided after the first 10 trials to incorporate learning processes. Regardless of marketed or non-marketed goods, the mean of WTA exceeded the mean of WTP at the first auction trial. As experimental trials proceeded, the disparity between WTA and WTP for marketed goods disappeared. However results for non-marketed goods were rather mixed to the extent that WTA for health risks from As (relatively high risk leves) were significantly larger than WTP, while there were no significant difference between WTA and WTP for health risks fro Pb and THM (relatively low risk levels). On the other hand, participants seemed to respond in a 'rational' manner to the objective risk information provided, with positive learning effects of market-like experience(especially in the WTA experiments).

• Management & Information Systems Review
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• v.38 no.4
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• pp.61-78
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• 2019

When calculating gains from transfers of assets inherited or donated, the value recognized at the market price as of the date of inheritance or acquisition is recognized as the actual transaction value at the time of acquisition. However, Precedents for the appeal for review by the NTS, the request for adjudgment by the Tax Tribunal(TT) and the request of examination by the Board of Audit and Inspection of Korea(BAI) and the cases of the lawsuit have not shown a consistent results on how much such a the actual transaction value will be measured. This study investigates the operating state of the current tax appeal system using the statistical data of the TT, NTS, and BAI and cases of the lawsuit from 2008 to 2017, and suggests the Improvement of Capital Gains Tax Act on the transfer of inherited and donated property. As a result, total number of requested cases has diminished because cases of the pre-assessment review and the reconsideration appeal by the NTS have decreased steadily over the past decade, while the cases of the lawsuit and the administrative trials(the request for adjudgment by the TT, the appeal for review by the NTS, and the request of examination by the BAI) have been steadily increasing. Also This study found that more than 40% of the complainants proceeded with the cases of the lawsuit proceedings in disagreement with the disposition of tax dissatisfaction under the administrative trials. In addition, Even though the retrospective appraisal price is not recognized as the market price due to the strict interpretation of the tax regulations, it can be seen that it is interpreted as a more expanded concept in the application of the market price than the government office or the tax judge. Therefore, according to the precedents of the cases lawsuit, it is necessary to establish a regulation on the recognition of retroactive appraisal value.

• Knowledge Management Research
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• v.21 no.3
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• pp.45-65
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• 2020

It is desirable to invest in wine that increases its value, but wine investment itself is unfamiliar in Korea. Also, the process itself is unreasonable, and information is often forged, because pricing in the wine market is done by a small number of people. With the right solution, however, the wine market can be a desirable investment destination in that the longer one invests, the higher one can expect. Also, it is expected that the domestic wine consumption market will expand through the steady increase in domestic wine imports. This study presents the consortium block chain framework for revitalizing the wine market and enhancing transparency as the "right solution" of the nation's wine investment market. Blockchain governance can compensate for the shortcomings of the wine market because it guarantees desirable decision-making rights and accountability. Because the data stored in the block chain can be checked by consumers, it reduces the likelihood of counterfeit wine appearing and complements the process of unreasonably priced. In addition, digitization of assets resolves low cash liquidity and saves money and time throughout the supply chain through smart contracts, lowering entry barriers to wine investment. In particular, if the governance of the block chain is composed of 'chateau-distributor-investor' through consortium blockchains, it can create a desirable wine market. The production process is stored in the block chain to secure production costs, set a reasonable launch price, and efficiently operate the distribution system by storing the distribution process in the block chain, and forecast the amount of orders for futures trading. Finally, investors make rational decisions by viewing all of these data. The study presented a new perspective on alternative investment in that ownership can be treated like a share. We also look forward to the simplification of food import procedures and the formation of trust within the wine industry by presenting a framework for wine-owned sales. In future studies, we would like to expand the framework to study the areas to be applied.