• 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.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.6
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• pp.773-782
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• 2019

Basel III (Third Basel Accord or Basel Standards) is a global, voluntary regulatory framework on bank capital adequacy, stress testing, and market liquidity risk. Basel III regulatory ratios include capital adequacy, asset soundness, and liquidity. The capital adequacy variables include BIS capital adequacy ratio, BIS tier 1 capital ratio, and tangible common equity ratio. The asset soundness variables include non-performing loan ratio and non-performing loan coverage ratio. The liquidity regulation variables include KRW liquidity coverage ratio and foreign currency liquidity coverage ratio. This study aims to investigate how capital adequacy standard affects efficiency of internet primary banks. As a result of this study, BIS capital adequacy ratio of domestic internet primary banks is lower than that of commercial banks. In order to maintain sustainable operation considering capital adequacy regulations, it is necessary to expand additional capital. In addition, the delinquency rate and non-performing loan ratio of domestic internet primary banks is gradually increasing due to the maturity of high-yield loans in 2019.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.795-807
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• 2020

The more liquid the capital market, the more attractive it will be for investors to place their money in the capital market. Therefore, the purpose of this study is to investigate the factors that influence stock liquidity of manufacturing sector companies listed on the stock exchange in Indonesia. The independent variables used in this study are forward-looking information disclosure, institutional ownership, foreign ownership, and board activity with information asymmetry as an intervening variable and stock liquidity as the dependent variable. The population of this study is manufacturing sector companies listed on the Indonesian stock exchange (IDX). Samples are selected based on the random sampling method, and the number of samples is calculated based on the Slovin formula. The sample was 59 manufacturers, and data was annual reports (for 2 years) and stock transactions from 2016 to 2017. The results of the study showed that forward-looking information disclosure had a significant effect on information asymmetry. Information asymmetry and foreign ownership have a significant impact on stock liquidity, whereas information asymmetry mediates the relationship between forward-looking disclosures and stock liquidity. Furthermore, the accuracy of information about the certainty of business activity both now and in the future can instill confidence in stakeholders in interacting and cooperating.

• Journal of the Economic Geographical Society of Korea
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• v.2 no.1_2
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• pp.63-81
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• 1999

The aims of this study are to analyze the current states and problems of development finance in the regional development projects, and to examine new sources and techniques of development finance for activating regional development projects. Analyzing the current states of development finance in regional development project, the problems such as the poorness of development function, the low accessibility to formal financial market, especially capital market, and the dominant use of corporate financing can be seen. In these context, four alternatives are proposed in order to activate development finance. First alternative is to use the funds which invest the equity of real estate, such as REITs. The second is to activate project financing. The third is to use asset backed securities. The forth is using mezzanine capitals as the means of protecting investors.

• Journal of Technology Innovation
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• v.16 no.2
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• pp.125-145
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• 2008

The paper evaluates the Korean science, technology, and innovation policy(STIP) in terms of an individual firm. The firm is Viromed(Ltd), a new technology-based venture company in the field of biotechnology. The case is compared with the 'Hwang Project', which is known as a typical failure case in Korea. In order to evaluate the Korean STIP, we establish 6 areas, which are technological infrastructure, institutional infrastructure, human capital infrastructure, technology market, industrial base, and innovation networks. The study shows that the policy schemes relating with technological infrastructure, institutional infrastructure, human capital infrastructure, and industrial base play a positive role in the start-up, development and innovation of Viromed(Ltd). However, we can hardly find the role of Korean government in fostering the technology market, transferring the technological output to economic performance. Although the international networks with the British, American, and Japanese firms or investors were a key success factor of the growth of Viromed(Ltd), the role of the government in this policy area was not enough. As for the 'Hwang Project', we suggest that the government should consider the possibility of commercialization in choosing R&D projects and determining the size of financial aids. Since the evaluation of the Korean STIP is based on an individual firm, the results of the paper need to be confirmed by a systematic comparison with other cases or industries.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.70
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• pp.109-133
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• 2016

As for Korea, China is very important because of an advantageous geological accessibility and high economic dependency. Therefore, the Korean government announced its plan to establish 5billion dollars' investment from Greater China (including Hong Kong and Singapore) and the government has put much effort into accommodating more Chinese investment by diversifying investment channels from Greater China. Under this major Chinese investment boom, it is crucial to conduct in-depth research on accommodation of Chinese investment and create a plan to establish Chinese capital investment that will benefit both the investing country and the countries receiving the investment. Hence, the present study analyzed current trends in Chinese investment for the Korean market, focusing on the stimulation methodology for establishing greater investment from China. To this end, this paper examined various investment characteristics of Chinese investors for the Korean market by researching investment development levels on different time lines and analyzing Chinese investment in Korea for a variety of industries. Through the research, the following study derived a more effective strategy to accommodate greater Chinese capital investment. There has been a worldwide increase in the number of letter of credit cases involving fraud recently. It may happen that the documents which are tendered to the banks under a documentary credit are forged, altered or fraudulent. Banks assume no liability or responsibility for the form, sufficiency, accuracy, genuineness or falsification of any documents.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.1
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• pp.43-52
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• 2018

This research aims to evaluate the current state of technology of enterprises in Vietnam in comparison with several countries in the AEC economic community, thereby to propose several recommendations to Vietnamese enterprises in order able to promote technology innovation activities, create competitiveness with enterprises in the region. Qualitative research methods are used through statistics and comparative descriptions from data collected from various sources: WEF, World Bank, CIEM, General Statistic Office. The study results show that Vietnamese enterprises still have many limitations in technology, originated from their small business scale (capital and labor), the current research capacity is still low, the funding for this activity is not high and the accessibility of the capital is still difficult. According to the Global Competitiveness Index, Vietnam's science and technology indexes are low compared to other AEC-developed countries including the availability of the latest technology; the acquisition of technology at the enterprise level; the capacity of improvement; quality of scientific research organizations..., which shall be a major barrier for Vietnamese enterprises to have to overcome to be able to create the competitiveness when entering the global market. From then on, the authors proposed solutions for two subjects, enterprises and government, to help Vietnamese enterprises to overcome this barrier.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.33-40
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• 2020

The main aim of the study is to test a house pricing model by combining hedonic and asset-based pricing models. An understanding of the relationship between house pricing and its return (the rental income) helps to establish houses as a significant asset class. The model tested the relationship between house pricing (dependent variable) and the house attributes (independent variables) derived from Freeman's framework of housing attributes. This study uses a large data-set of 1,899 sample of new, high-end houses purchased between 2016 and 2019 collected from the national capital region of India (Delhi-NCR). The algorithm was built in R-Script, and stepwise multiple linear regression was used to analyze the model. The analysis of the model proves that the three significant variables, namely, carpet area, pay-off, and annual maintenance charges explain the price function. Further, the model is statistically fit. The major contribution of the study is to understand the key factors and their influence on the house pricing. The model will be helpful in risk assessment in the housing investment and enhance the chances of investment. Policy-makers can use information about the underlying valuation drivers of the house prices to stabilize the market and also in framing the tax policies.

• International journal of advanced smart convergence
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• v.7 no.3
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• pp.73-78
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• 2018

This study focuses on presenting the IT program module provided by BKLS measure in order to solve the problem of capital cost due to information asymmetry of external investors and corporate executives. Barron at al(1998) set up a BKLS measure to guide the market by intermediate analysts. The BKLS measure was measured by using the changes in the analyst forecast dispersion and analyst mean forecast error squared. This study suggests a model of the algorithm that the BKLS measure can be provided to all investors immediately by IT program in order to deliver the meaningful value in the domestic capital market as measured. This is a method of generating and analyzing real-time or non-real-time prediction models by transferring the predicted estimates delivered to the Big Data Log Analysis System through the statistical DB to the statistical forecasting engine. Because BKLS measure is not carried out in a concrete method, it is practically very difficult to estimate the BKLS measure. It is expected that the BKLS measure of Barron at al(1998) introduced in this study and the model of IT module provided in real time will be the starting point for the follow-up study for the introduction and realization of IT technology in the future.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.61-67
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• 2021

The covid-19 pandemic scenario caused the most extensive economic shocks the world has experienced in decades. Maintaining financial performance and economic stability is essential during the pandemic period. In these conditions, where movement is severely restricted, media consumption is considered to be increasing. The social media platform is one of the media online used by the public as a source of information and also expressing their sentiment, including individual investors in the capital market as social media users. Twitter is one of the social media microblogging platforms used by individual investors to share their opinion and get information. This study aims to determine whether microblogging sentiment investors can predict the capital market during pandemics. To analyze microblogging sentiment investors, we classified sentiment using the phyton text mining algorithm and Naïve Bayesian text classification into level positive, negative, and neutral from November 2019 to November 2020. This study was on 68 listed companies on the Indonesia stock exchange. A Vector Autoregression and Impulse Response is applied to capture short and long-term impacts along with a causal relationship. We found that microblogging sentiment investor has a significant impact on stock returns and volatility and vice-versa. Also, the response due to shocks is convergent, and microblogging investors in Indonesia are categorized as a "news-watcher" investor.