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    중소기업의 종합평가모형 및 예측에 관한 연구 = An Empirical Research on Risk Evaluation Model and Forecasting of SMEs

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    https://www.riss.kr/link?id=A99903928

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    It is not easy to evaluate a risk of SMEs by the same criteria. Because this approach method can be applied to calculate the risk evaluation rating and accuracy of the prediction to the each company, this research is expected to provide useful information to the supervisory authority as well as financial institution. RisK Evaluation Model of this research consists of the elements such as composite rating system, principal component analysis etc, and risk evaluation rating is calculated by the company`s financial variables which include information about the level of risk. As a result of an empirical analysis on SME from 2000 to 2011, firm-specific risk evaluation rating seems to be generally increasing in 2002, but it shows decrease during a 2003 credit card crisis period. Firm-specific risk evaluation rating generally increases after 2003, but it starts to decrease due to the sub-prime mortgage crisis at the end of 2007 and the global financial crisis of 2008. Thus, observing similarities or differences on global economic trend, we need to monitor the change in risk evaluation level of companies. Also, from a point of view on the prediction accuracy, the bankruptcy prediction on model 2 measured as 0.6205 on average, is higher than that of model 1, 0.6043. The higher ratio of model 2 indicates that the model including macroeconomic effects has shown a better result, and it helps to verify whether certain companies exposure to macroeconomic risk shocks or not. This paper has a valuable meaning because the empirical research of SMEs default frequency, which is considering both financial and macroeconomic variables, is very rare. To set up the risk evaluation and forecasting level, the model recommended in this research is based on several simple assumptions, and it is able to improve the suitability of model if we apply an appropriate ratio of finance to each industry.
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    It is not easy to evaluate a risk of SMEs by the same criteria. Because this approach method can be applied to calculate the risk evaluation rating and accuracy of the prediction to the each company, this research is expected to provide useful informa...

    It is not easy to evaluate a risk of SMEs by the same criteria. Because this approach method can be applied to calculate the risk evaluation rating and accuracy of the prediction to the each company, this research is expected to provide useful information to the supervisory authority as well as financial institution. RisK Evaluation Model of this research consists of the elements such as composite rating system, principal component analysis etc, and risk evaluation rating is calculated by the company`s financial variables which include information about the level of risk. As a result of an empirical analysis on SME from 2000 to 2011, firm-specific risk evaluation rating seems to be generally increasing in 2002, but it shows decrease during a 2003 credit card crisis period. Firm-specific risk evaluation rating generally increases after 2003, but it starts to decrease due to the sub-prime mortgage crisis at the end of 2007 and the global financial crisis of 2008. Thus, observing similarities or differences on global economic trend, we need to monitor the change in risk evaluation level of companies. Also, from a point of view on the prediction accuracy, the bankruptcy prediction on model 2 measured as 0.6205 on average, is higher than that of model 1, 0.6043. The higher ratio of model 2 indicates that the model including macroeconomic effects has shown a better result, and it helps to verify whether certain companies exposure to macroeconomic risk shocks or not. This paper has a valuable meaning because the empirical research of SMEs default frequency, which is considering both financial and macroeconomic variables, is very rare. To set up the risk evaluation and forecasting level, the model recommended in this research is based on several simple assumptions, and it is able to improve the suitability of model if we apply an appropriate ratio of finance to each industry.

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