• The Journal of Asian Finance, Economics and Business
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• 제7권8호
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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.

• The Journal of Asian Finance, Economics and Business
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• 제10권2호
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• pp.175-181
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• 2023

Competition assures improved products and services to meet customers' needs. The soundness of a firm's financial health is crucial for the country's economic well-being. Distressed companies cause investor panic, which has a knock-on effect on the economy and leads to a deterioration in the image and value of the companies. This paper aims to empirically investigate the influence of competition on financial distress (FD) in the healthcare industry using the Altman Zscore values as the proxy for FD. This study uses secondary data from ten healthcare companies operating in India between 2016 and 2020. The study's findings indicate a significant negative relation with the exogenous variables of the study, implying that a higher level of competition enhances a firm's FD or adversely affects financial health. The main implication of the study is two-pronged. Firstly, the firms' managers and decision-makers need not worry about competition as a deterrent to stability. Secondly, the policymakers need not be concerned that high competition may lead to financial stress for the firms. Therefore, this paper concludes that competition is good for firms operating in India.

• Asian Pacific Journal of Cancer Prevention
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• 제17권5호
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• pp.2459-2464
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• 2016

Background: Cancer treatments can have long-term physical, psychological, financial, sexual and cognitive effects that may influence the quality of life. These can vary from urban to rural areas, survival period and according to the type of cancer. We here aimed to describe demographics and psychosocial analysis of cancer survivors three to five years post-treatment in rural Australia and also assess relationships with financial stress and quality of life domains. Materials and Methods: In this cross-sectional study, 65 participants visiting the outpatient oncology clinic were given a self-administered questionnaire. The inclusion criteria included three to five years post-treatment. Three domains were investigated using standardised and validated tools such as the Standard Quality of Life in Adult Cancer Survivors Scale (QLACS) and the Personal and Household Finances (HILDA) survey. Included were demographic parameters, quality of life, treatment information and well-being. Results: There was no evidence of associations between any demographic variable and either financial stress or cancer-specific quality of life domains. Financial stress was however significantly associated with the cancer-specific quality of life domains of appearance-related concerns, family related distress, and distress related to recurrence. Conclusions: This unique study effectively points to psychosocial aspects of cancer survivors in rural regions of Australia. Although the majority of demographic characteristics were not been found to be associated with financial stress, this latter itself is significantly associated with distress related to family and cancer recurrence. This finding may be of assistance in future studies and also considering plans to fulfil unmet needs.

• 기술혁신연구
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• 제19권2호
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• pp.25-51
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• 2011

R&D 지출은 지속적이어야 하며, 일시적으로 감소할 경우 이후 상당한 조정비용을 부담하게 된다. 본 연구에서는 기업이 재정적으로 어려움에 처한 경우 R&D 조정비용을 회피하기 위해서 기업이 보유한 현금성 자산을 이용하여 R&D 자금을 조달하는지를 분석하였다. 기업의 재정상태를 알아보기 위해 선행연구에서 이용한 기업 연수 뿐 아니라 기업 규모, Altman Z-score 및 K-Score에 따라 기업의 재정상태를 구분하였고, Brown and Petersen(2010)의 동적 R&D모형을 이용하여 실증 분석을 실시하였다. 분석 결과, 재정적으로 어려움에 처한 기업을 분석한 모든 결과에서 R&D지출과 기업이 보유한 현금성 자산과 유의한 음(-)의 관계가 도출되었다. 즉, 중소기업, 부도확률이 중간이상인 기업, 기업 연수가 짧은 기업일수록 그렇지 않은 기업에 비해 지속적인 R&D지출을 위해 기업이 보유한 현금성 자산을 이용하는 것으로 나타났다. Altman의 Z-Score와 K-Score를 사용하여 분류한 결과는 새로운 시사점을 제공하고 있었는데, 부도확률이 매우 높은 기업들은 R&D 지출을 유지하고 있지 못하지만, 다만 판단유보 상태에 있는 중간 기업들이 재정적인 어려움에 처했을 때에도 막대한 R&D 조정비용을 예방하기 위하여 현금성 자산으로 재원을 조달하고 있었다. 이러한 결과는 본 논문에서 설정한 가설과 일치되는 것으로 재정적으로 어려움에 처한 기업은 현금성 자산을 이용해 R&D 자금을 조달하고 있음을 확인할 수 있었다.

• 디지털융복합연구
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• 제2권1호
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• pp.145-160
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• 2004

P Leasing Company was a steady growing company with positive net income in most years since 1985 when it was established. However, it suddenly experienced a minus net income of 6.8 billion won in 1996. The reason of its deficit was known to be the financial distress of its two major leasing contracts. The total amount of two contracts was 58 billion won witch is about 8% of total amount of its leasing contracts. In this paper, we analyse how the disability of lease payments from the two leasing contracts influence P Leasing Company's financial stability, growth opportunity, and profitability. In addition, by performing ROI analyse, we point out the financial reasons of P Leasing Company's deficit in 1996. We hope our case analysis to help students understand the cash flow of leasing companies. The P Leasing Company case also illustrates the fact that bad leasing contracts would seriously affect the profitability of leasing companies as bad loans would seriously do the profitability of commercial banks.

• The Journal of Asian Finance, Economics and Business
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• 제8권1호
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• pp.573-585
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• 2021

The banking sector is one of the most important sectors in Pakistan's struggling economy. Recent studies have recommended that suitable methods can be applied to predict bankruptcy. In this context, this work analyzes Pakistan's banking sector's financial status through the five-factor Altman Z-score model, which determines the probability of bankruptcy for an organization. Banking data has been collected through the Pakistan Stock Exchange (PSX) in the period 2013-2017. The Z-score assessment criteria is defined as: Z> 2.99 - "safe" zone; Z> 1.8 Z>2.98- "grey" zone; and Z <1.8 - "distress" zone. Results show good predictions for the local banking industry, while most foreign Pakistani banks were found bankrupt with the Z-score below 1.1. One of the financial risks investors face when investing in any company is the risk of bankruptcy. One of the most used models for predicting financial distress for any company is Altman's Z-score model. On the other hand, the Z-score analysis suggests that all banking establishments are not bankrupt because they have sufficient ability to control bankruptcy. At the same time, foreign banks failed financially and would not be able to be sustained in the future because they do not have the ability to pay the short-term and long-term debt.

• 경영정보학연구
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• 제18권2호
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• pp.173-198
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• 2016

본 연구의 목적은 비즈니스 인텔리전스 연구 관점에서 기업부실화 예측 성능을 향상키시는 것이다. 이를 위해 본 연구는 기존 연구들에서 미흡하게 다루어졌던 1) 데이터셋을 구성하는 과정에서 발생하는 바이어스 문제, 2) 거시경제위험 요소의 미반영 문제, 3) 데이터 불균형 문제, 4) 서술적 바이어스 문제를 다루어 경기순환국면을 반영한 기업부실화 예측 프레임워크를 제안하고, 이를 바탕으로 기업부실화 예측 모델을 개발하였다. 본 연구에서는 경기순환국면별로 각각의 데이터셋을 구성하고, 각 데이터셋에서 의사결정나무, 인공신경망 등 단일 분류기부터 앙상블 기법까지 다양한 데이터마이닝 알고리즘을 적용하여 실험하였다. 또한 본 연구는 데이터불균형 문제를 해결하기 위해, 오버샘플링 기법인 SMOTE(synthetic minority over-sampling technique) 기법을 통해 초기 데이터 불균형 상태에서부터 표본비율을 1:1까지 변화시켜 가며, 기업부실화 예측 모델을 개발하는 실험을 하였고, 예측 모델의 변수 선정 시에 선행연구를 바탕으로 재무비율을 추출하고, 여기서 파생된 IT 산출물인 재무상태변동성과 산업수준상태변동성을 예측 모델에 삽입하였다. 마지막으로, 본 연구는 각 순환국면에서 만들어진 기업부실화 예측 모델의 예측 성능 비교와 경기 확장기와 수축기에서의 기업부실화 예측 모델의 유용성에 대해 논의하였다. 본 연구는 비즈니스 인텔리전스 연구 측면에서 기존 연구에서 미흡하게 다루어졌던 4가지 문제점을 검토하고, 이를 해결할 프레임워크를 제안함으로써 기존 연구 대비 기업부실화 예측률을 10% 이상 향상시켰다는 점에서 연구의 의의를 찾을 수 있다.

• Journal of Information Processing Systems
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• 제15권3호
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• pp.682-693
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• 2019

The traditional classification methods mostly assume that the data for class distribution is balanced, while imbalanced data is widely found in the real world. So it is important to solve the problem of classification with imbalanced data. In Mahalanobis-Taguchi system (MTS) algorithm, data classification model is constructed with the reference space and measurement reference scale which is come from a single normal group, and thus it is suitable to handle the imbalanced data problem. In this paper, an improved method of MTS-CBPSO is constructed by introducing the chaotic mapping and binary particle swarm optimization algorithm instead of orthogonal array and signal-to-noise ratio (SNR) to select the valid variables, in which G-means, F-measure, dimensionality reduction are regarded as the classification optimization target. This proposed method is also applied to the financial distress prediction of Chinese listed companies. Compared with the traditional MTS and the common classification methods such as SVM, C4.5, k-NN, it is showed that the MTS-CBPSO method has better result of prediction accuracy and dimensionality reduction.

• The Journal of Asian Finance, Economics and Business
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• 제8권1호
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• pp.665-673
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• 2021

Default has become an extreme concern in the current world due to the financial crisis. The previous prediction of companies' bankruptcy exhibits evidence of decision assistance for financial and regulatory bodies. Notwithstanding numerous advanced approaches, this area of study is not outmoded and requires additional research. The purpose of this research is to find the best classifier to detect a company's default risk and bankruptcy. This study used secondary data from the Pakistan Stock Exchange (PSX) and it is time-series data to examine the impact on the determinants. This research examined several different classifiers as per their competence to properly categorize default and non-default Pakistani companies listed on the PSX. Additionally, PSX has remained consistent for some years in terms of growth and has provided benefits to its stockholders. This paper utilizes machine learning techniques to predict financial distress in companies listed on the PSX. Our results indicate that most multi-stage mixture of classifiers provided noteworthy developments over the individual classifiers. This means that firms will have to work on the financial variables such as liquidity and profitability to not fall into the category of liquidation. Moreover, Adaptive Boosting (Adaboost) provides a significant boost in the performance of each classifier.

• 성인간호학회지
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• 제24권1호
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• pp.52-63
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• 2012

Purpose: The purpose of this study was to measure the quality of life (QOL) and to identify the factors influencing QOL in gynecological cancer patients. Methods: The subjects of this study were 242 people who were receiving medical therapy or follow-up after surgery from one general hospital in Daegu. Data were collected from August 1, 2010 to January 31, 2011. A questionnaire including questions on QOL, distress score, distress problem, depression, anxiety, insomnia, perceived health status and body image were completed by the subjects. Results: The mean score of QOL was $70.68{\pm}13.40$. Religion, job, presence of spouse, level of education, household income, financial compensation, disease stage and recurrence were the significant factors related to QOL. Distress score, distress problem, depression, anxiety, insomnia, perceived health status and body image were also significant factors influencing QOL. Sixty eight percent of the variance in subjective overall QOL can be explained by body image, distress problem, distress score, anxiety, level of education and perceived health status (Cum $R^2$=0.689, F=76.316, $p$ <.001). Body image was the most important factor related to QOL. Conclusion: An integrative care program which includes general, disease-related and psychosocial characteristics of patients is essential to improve QOL in gynecological cancer patients.