• Title/Summary/Keyword: Bankruptcy Data

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Using Estimated Probability from Support Vector Machines for Credit Rating in IT Industry

  • Hong, Tae-Ho;Shin, Taek-Soo
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2005.11a
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    • pp.509-515
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    • 2005
  • Recently, support vector machines (SVMs) are being recognized as competitive tools as compared with other data mining techniques for solving pattern recognition or classification decision problems. Furthermore, many researches, in particular, have proved it more powerful than traditional artificial neural networks (ANNs)(Amendolia et al., 2003; Huang et al., 2004, Huang et al., 2005; Tay and Cao, 2001; Min and Lee, 2005; Shin et al, 2005; Kim, 2003). The classification decision, such as a binary or multi-class decision problem, used by any classifier, i.e. data mining techniques is cost-sensitive. Therefore, it is necessary to convert the output of the classifier into well-calibrated posterior probabilities. However, SVMs basically do not provide such probabilities. So it required to use any method to create probabilities (Platt, 1999; Drish, 2001). This study applies a method to estimate the probability of outputs of SVM to bankruptcy prediction and then suggests credit scoring methods using the estimated probability for bank's loan decision making.

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What Exacerbates the Probability of Business Closure in the Private Sector During the COVID-19 Pandemic? Evidence from World Bank Enterprise Survey Data

  • PHAM, Thi Bich Duyen;NGUYEN, Hoang Phong
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.6
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    • pp.69-79
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    • 2022
  • The purpose of the study is to look into the likelihood of private sector enterprises going bankrupt due to COVID-19 pandemic-related issues. The data for this study was taken from the World Bank's Enterprise Survey, which was intended to assess the impact of the COVID-19 pandemic on the business sector. This study uses the Ordinal Logit Method to analyze the model with dependent variables having ordinal values. The determinants reflect business performance, innovation, business relationships, and government support. According to the estimation results, a lower probability of business closures, illiquidity, and payment delays are found in businesses that maintain sales growth, operating hours, temporary workers, product portfolio, consumer demand, and input supply. Meanwhile, the increase in online business activities and receiving support from financial institutions and the government do not help businesses reduce the risk. Moreover, higher survival is found in manufacturing and developing countries. This implies the fragility of businesses in the retail and service sectors, especially for mega-enterprises in developed countries. In addition, the negative impact of the COVID-19 pandemic on businesses in Europe and West Asia is less severe than in other regions. The results imply policies to support the private sector during the pandemic, such as increasing labor market flexibility or rapidly implementing supportive policies.

Predicting Financial Distress Distribution of Companies

  • VU, Giang Huong;NGUYEN, Chi Thi Kim;PHAM, Dang Van;TRAN, Diu Thi Phuong;VU, Toan Duc
    • Journal of Distribution Science
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    • v.20 no.10
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    • pp.61-66
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    • 2022
  • Purpose: Predicting the financial distress distribution of an enterprise is important to warn enterprises about their future. Predicting the possibility of financial distress helps companies have action plans to avoid the possibility of bankruptcy. In this study, the author conducted a forecast of the financial distress distribution of enterprises. Research design, data and methodology: The forecasting method is based on Logit and Discriminant analysis models. The data was collected from companies listed on Vietnam Stock Exchange from 2012 to 2020. In which there are both companies suffer from financial distress and non-financial distress. Results: The forecast analysis results show that the Logistic model has better predictability than the Discriminant analysis model. At the same time, the results also indicate three main factors affecting the financial distress of enterprises at all three research stages: (1) Liquidity, (2) Interest payment, and (3) firm size. In addition, at each stage, the impact of factors on financial distress differs. Conclusions: From the results of this study, the author also made several recommendations to help companies better control company operations to avoid falling into financial distress. Adjustments to current assets, debt, and company expansion considerations are the most important factors for companies.

National Liability and Fiscal Crisis (국가부채의 재정위기 현황과 감당수준)

  • Jung, Do-Jin
    • Asia-Pacific Journal of Business
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    • v.12 no.4
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    • pp.253-270
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    • 2021
  • Purpose - The main purpose of this study is to measure and evaluate the level of national liabilities that Korea's national finances can afford. Specifically, the concepts of national debt and national liability are clarified, and the appropriate level of national liabilities is measured in terms of short-term fiscal crisis, mid-to-long-term fiscal crisis, and GDP. Based on these measurements of fiscal crisis, this study would like to propose national fiscal management plans. Design/methodology/approach - In order to clearly recognize the difference between the national debt and the national liability, this study examines the data from 2013 to 2020. In addition, this study uses data from the national financial statements from 2013 to 2018 to measure the appropriate level of national liabilities in terms of fiscal crisis management. Findings - Short-term fiscal crises, measured by current ratios, will not occur. Nevertheless, in view of the cash flow compensation ratio, the short-term bankruptcy of the national finances of Korea depends on the re-borrowing of short-term borrowings and current and long-term borrowings. In addition, in order to manage the mid-to long-term financial crisis, it is necessary to pay attention to the liability growth rate rather than the liability size. Research implications or Originality - While previous studies focused on the appropriate level of national debt, this study was differentiated as a study focused on the level of national liability coverage. It is expected that the results of this study will be used to manage the national fiscal soundness.

The Pattern Analysis of Financial Distress for Non-audited Firms using Data Mining (데이터마이닝 기법을 활용한 비외감기업의 부실화 유형 분석)

  • Lee, Su Hyun;Park, Jung Min;Lee, Hyoung Yong
    • Journal of Intelligence and Information Systems
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    • v.21 no.4
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    • pp.111-131
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    • 2015
  • There are only a handful number of research conducted on pattern analysis of corporate distress as compared with research for bankruptcy prediction. The few that exists mainly focus on audited firms because financial data collection is easier for these firms. But in reality, corporate financial distress is a far more common and critical phenomenon for non-audited firms which are mainly comprised of small and medium sized firms. The purpose of this paper is to classify non-audited firms under distress according to their financial ratio using data mining; Self-Organizing Map (SOM). SOM is a type of artificial neural network that is trained using unsupervised learning to produce a lower dimensional discretized representation of the input space of the training samples, called a map. SOM is different from other artificial neural networks as it applies competitive learning as opposed to error-correction learning such as backpropagation with gradient descent, and in the sense that it uses a neighborhood function to preserve the topological properties of the input space. It is one of the popular and successful clustering algorithm. In this study, we classify types of financial distress firms, specially, non-audited firms. In the empirical test, we collect 10 financial ratios of 100 non-audited firms under distress in 2004 for the previous two years (2002 and 2003). Using these financial ratios and the SOM algorithm, five distinct patterns were distinguished. In pattern 1, financial distress was very serious in almost all financial ratios. 12% of the firms are included in these patterns. In pattern 2, financial distress was weak in almost financial ratios. 14% of the firms are included in pattern 2. In pattern 3, growth ratio was the worst among all patterns. It is speculated that the firms of this pattern may be under distress due to severe competition in their industries. Approximately 30% of the firms fell into this group. In pattern 4, the growth ratio was higher than any other pattern but the cash ratio and profitability ratio were not at the level of the growth ratio. It is concluded that the firms of this pattern were under distress in pursuit of expanding their business. About 25% of the firms were in this pattern. Last, pattern 5 encompassed very solvent firms. Perhaps firms of this pattern were distressed due to a bad short-term strategic decision or due to problems with the enterpriser of the firms. Approximately 18% of the firms were under this pattern. This study has the academic and empirical contribution. In the perspectives of the academic contribution, non-audited companies that tend to be easily bankrupt and have the unstructured or easily manipulated financial data are classified by the data mining technology (Self-Organizing Map) rather than big sized audited firms that have the well prepared and reliable financial data. In the perspectives of the empirical one, even though the financial data of the non-audited firms are conducted to analyze, it is useful for find out the first order symptom of financial distress, which makes us to forecast the prediction of bankruptcy of the firms and to manage the early warning and alert signal. These are the academic and empirical contribution of this study. The limitation of this research is to analyze only 100 corporates due to the difficulty of collecting the financial data of the non-audited firms, which make us to be hard to proceed to the analysis by the category or size difference. Also, non-financial qualitative data is crucial for the analysis of bankruptcy. Thus, the non-financial qualitative factor is taken into account for the next study. This study sheds some light on the non-audited small and medium sized firms' distress prediction in the future.

A Study on the Usefulness of Accounting Information for the Predication of Medium and Small Enterprises' Bankruptcy (중소기업 도산예측에 회계정보 유용성에 관한 연구)

  • Lee, Sung-Hwan
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.9 no.5
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    • pp.1460-1466
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    • 2008
  • The purpose of this study is to verify how the accounting information of a bankrupt firm which is defined as a dishonor, an impaired total capital, a poor financial performance of a business, a rejection of auditor's opinion and an incongruity of auditor's opinion differs from that of a healthy firm on the basis of the index of financial affairs if the accounting information released by KOSDAQ is valuable. The sampling firms consists of 45 KOSDAQ firms that went bankrupt from 2000 to 2007 and 45 healthy firms which are selected in accordance with the sizes of assets. It has also selected the 30 sampling firms for the confirmation of the model in the same way. According to the result of the in-depth analysis, the variables related to security among the 17 indexes of financial affairs that have been used in this study for 5 years show a noticeable difference between a bankrupt firm and a healthy one. The accuracy of failed firms using this model for confirmation demonstrates 76.7% in 5 years before the bankruptcy, 76.7% in 4 years before that, 65.0% in 3 years before it, 76.7% in 2 years, 88.3% in 1 year. This data shows that the process from a healthy firm to a bankrupt one has progressed gradually and confirms the value of the index of financial affairs, exhibiting the accuracy with 83.8% of a presuming sample and 76.7% of a confirming sample for 5 years.

Lessons from Haitai Distribution Inc's experience in Korea

  • Cho, Young-Sang
    • Journal of Distribution Science
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    • v.9 no.3
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    • pp.25-36
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    • 2011
  • Owing to the rapid growth of hypermarket/discount store formats since 1996, Korean retailing has suddenly attracted the significant attention from researchers. Before the emergence of large scale retailers such as E-Mart, Lotte Mart and Tesco Korea, there were the two retail formats who led the Korean retailing in the modern retailing history: department store and supermarket formats. Nevertheless, there has been little literature concerned about the two retail formats as a case study, while some authors have paid their attention to hypermarket/discount store formats. In addition, when mentioning the development process of retailing history, it is less likely that authors have made an effort to illustrate supermarket retailing history. In order to regard supermarket retailing as part of the Korean retailing, it is interesting to look at a representative supermarket retailer, Haitai, who was one of the subsidiaries of Haitai chaebol. Based on supermarket retailing, the company which was established as a joint venture in 1974 led a supermarket retailing in the Korean modernised retailing history. Before analysing whether Haitai failed or not, the definition of failure should be illustrated. With regard to the term, failure, in the academic world, authors have interchangeably used the following terms: failure, divestment, closure, organisational restructuring, and exit. To collect research data as a case study, the author adopted an in-depth interview method. The research is based on research interviews with 13 ex-staff who left after Haitai went bankruptcy, from store management department to merchandise department. By investigating Haitai's experiences through field interviews, the research found that Haitai restructured organisational decision-making process at the early stage when companies started to modernise organisational charts, benchmarking sophisticated retailing knowledge through the strategic alliance with a Japanese retailer. In respect of buying system, the company established firmly buying functions by adopting central buying system, and further, outstandingly allocated considerable marketing resources to the development of retailer brands with the dedicated team of retailer brand development. In the grocery retailing, abandoning a 'no-frill' packaging concept, the introduction of retailer brand packaging equal to, or better than national brand packaging design, encouraged other retailers to change their retailer brand development strategies. In product sourcing ways, Haitai organised for the first time the overseas sourcing team with the aim of improving the profit margins of foreign products and providing exotic products for customers, followed by other retailers. Regarding distribution system, the company introduced the innovative idea which delivered products ordered by stores directly to each store withboth its own vehicles and its own warehouse in which could deal with dry foods, chilly foods, frozen food, and non-foods, and even, process produce. In addition, Haitai developed many promotional methods to attract more customers like 'the guarantee of the lowest price', and expanded its own business to US in 1996, although withdrew, because of bankruptcy in 1997. Together with POS introduction in 1994, Haitai made a significant contribution to the development of the Korean retailing, influencing other retailers in many aspects. As a case study, the study has provided a number of lessons from Haitai's experiences for academicians and practitioners, suggesting that its history should be involved in the Korean modernised retailing.

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A Study on the Evaluation of an Expert System에s Performance : Lens Model Analysis (전문가시스템의 성능평가에 관한 연구 : 렌즈모델분석)

  • 김충영
    • Journal of Information Technology Applications and Management
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    • v.11 no.1
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    • pp.117-135
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    • 2004
  • Since human decision making behavior is likely to follow nonlinear strategy, it is conjectured that the human decision making behavior can be modeled better by nonlinear models than by linear models. All that linear models can do is to approximate rather than model the decision behavior. This study attempts to test this conjecture by analyzing human decision making behavior and combining the results of the analysis with predictive performance of both linear models and nonlinear models. In this way, this study can examine the relationship between the predictive performance of models and the existence of valid nonlinear strategy in decision making behavior. This study finds that the existence of nonlinear strategy in decision making behavior is highly correlated with the validity of the decision (or the human experts). The second finding concerns the significant correlations between the model performance and the existence of valid nonlinear strategy which is detected by Lens Model. The third finding is that as stronger the valid nonlinear strategy becomes, the better nonlinear models predict significantly than linear models. The results of this study bring an important concept, validity of nonlinear strategy, to modeling human experts. The inclusion of the concept indicates that the prior analysis of human judgement may lead to the selection of proper modeling algorithm. In addition, lens Model Analysis is proved to be useful in examining the valid nonlinearity in human decision behavior.

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Return Premium of Financial Distress and Negative Book Value: Emerging Market Case

  • KAKINUMA, Yosuke
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.8
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    • pp.25-31
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    • 2020
  • The purpose of this paper is to examine a financial distress premium in the emerging market. A risk-return trade-off of negative book equity (NBE) and distress firms is empirically analyzed using data from the Stock Exchange of Thailand. This research employs Ohlson's (1980) bankruptcy model as a measurement of distress risk. The results indicate that distress firms outperform solvent firms in the Thai market and deny distress anomaly often found in the developed market. Fama-Frech (1993) three-factor model and Carhart (1997) four-factor model verify the existence of a distress premium in the Thai capital market. Risk-seeking investors demand greater compensation for bearing risks of distress firms' going concern. This paper provides fresh evidence that default risk is a significant explanatory factor in pricing stocks in the emerging market. Also, this study sheds light on the role of NBE firms in asset pricing. Most studies eliminate NBE firms from their sample. However, NBE firms yield superior average cross-sectional returns, albeit with higher volatility. Investors are rewarded with distress risks associated with NBE firms. The outperformance of NBE firms is statistically significant when compared to the overall market. The NBE premium disappears when factoring size, value, and momentum in time-series analysis.

Growth Opportunities, Capital Structure and Dividend Policy in Emerging Market: Indonesia Case Study

  • DANILA, Nevi;NOREEN, Umara;AZIZAN, Noor Azlinna;FARID, Muhammad;AHMED, Zaheer
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.10
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    • pp.1-8
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    • 2020
  • The objective of the study is to investigate the effect of growth opportunities on capital structure and dividend policy in Indonesia. The study employs panel data of companies listed on Indonesia Stock Exchange that distribute dividends from 2007 to 2017. Fixed and random effect regression models are used. Findings based on growth opportunities on capital structure and dividend policy in Indonesia are in line with the existing theory (i.e., contracting theory). Growth opportunities have a significant negative correlation with debt ratio and dividend yield, which suggests that firms with high growth opportunities are discouraged to generate debt to resolve underinvestment and asset-substitution problem. Firms with more investment opportunities tend to adopt a low dividend payout policy because the cash flows will be used up for investment. The positive impact of firm size on leverage is due to the low bankruptcy risk and cost of a large company. Profitability has a positive impact on the dividend policy because profitable companies can reserve larger free cash flows and, thus, pay higher dividends. The positive influence of ownership on leverage is interpreted by the unwillingness of majority stockholders to commit to equity financing in order to avoid reducing the ownership and preserve control of the company.