Prediction of the financial risk of Special Treatment of a Listed Pharmaceutical Company in China: A Principal Component Analysis (Preprint)

2021 ◽  
Author(s):  
Yiming Cai ◽  
Xueyan Hu ◽  
Yiwei Guo ◽  
Ni Yan ◽  
Wai-Kit Ming
Keyword(s):  
Principal Component Analysis ◽  
Pharmaceutical Company ◽  
Financial Distress ◽  
Financial Risk ◽  
Principal Component ◽  
Component Analysis ◽  
Special Treatment ◽  
Pharmaceutical Companies ◽  
Risk Warning ◽  
Z Value

BACKGROUND The listed pharmaceutical industry of China is growing swiftly by about 10% interest per year. However, risk always keeps pace with improvements. In China, listed companies with significant financial distress or irregularities will be assigned a special treatment (ST) label indicating a risk warning. Recently, eight listed pharmaceutical companies with a ST sign are surviving with but present serious investment risks. OBJECTIVE This paper aimed to discover the most significant factors that cause conversion of a listed pharmaceutical company into an ST firm. Tailored approaches for protecting China’s listed pharmaceutical companies from financial risks are being developed in order to help this domain in profit. Besides, we also aimed to offer suggestions for investors for investigating Chinese listed pharmaceuticals with the goal of assisting the investors in making successful investments. METHODS After collecting data from online databases, a principal component analysis (PCA) model was applied for descending data dimensions. After selecting the components with highest contribution, a logistic regression (LR) model was conducted for simplifying the outcome and calculating the intercept, component coefficients, standard error (SE), and Z and p-values. RESULTS Nine principal components were crucial from the principal component analysis (PCA) model, and two components (components 1 and 5) remaining as the most important factors after the LR model. The estimated intercept was 4.866 (SE 1.096, Z-value 4.442, p < 0.001). The estimated coefficient for components 1 (SE 0.332, Z-value 3.067, p = 0.002) and 5 (SE 0.643, Z-value −2.6, p = 0.009) were 1.017 and −1.672, respectively. CONCLUSIONS Investors are supposed to supervise the accounting conditions in three sectors: (1) solvency, profitability, and research and development (R&D) investment; (2) running the firm properly; and/or (3) investing successfully. Firms are supposed to hire professional partitioners as leaders. The major shareholders should not plan any questionable investments for personal income, and they should ensure the firm works under conditions with low liability, high profitability, and R&D costs that match the perfect growth opportunity after the Coronavirus 2019 (COVID-19) pandemic and the strong growth of China’s economy in 2020.

scholarly journals Financial Risk Early-Warning Model Based on Kernel Principal Component Analysis in Public Hospitals

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Manxiang Qu ◽  
Yuexin Li
Keyword(s):  
Principal Component Analysis ◽  
Financial Risk ◽  
Principal Component ◽  
Component Analysis ◽  
Structural Features ◽  
Public Hospitals ◽  
Financial Data ◽  
Kernel Principal Component Analysis ◽  
Financial Risks ◽  
Warning Model

Public hospitals are facing the dual pressure of coping with external medical market competition and performing public health duties. Due to the influence of various risk factors, public hospitals are facing increasing financial risks. How to effectively prevent and control financial risks and maintain the normal operation and sustainable development of the hospital is a very important topic that needs to be studied in the development of public hospitals. Because the traditional principal component analysis method only pays attention to the global structural features and ignores the local structural features, a financial risk early-warning model based on improved kernel principal component analysis in public hospitals is proposed to improve the ability of risk assessment. The core ideas of the method in this paper for financial risk forecasting are as follows: the nonlinear features of the financial data are firstly extracted under different conditions, and then the feature matrix and the optimal feature vector are calculated to construct the distance statistics so as to determines the threshold by kernel density estimation; finally the Fisher discriminant analysis is used for similarity measurement to identify the risk types. Through experiments on the financial data of a number of public hospitals and listed companies, the experimental results verify the feasibility and effectiveness of the method used in this paper for financial risk analysis. This further shows that this research has a certain display significance.

A German version of the Intermittent Claudication Questionnaire (ICQ): cultural adaptation and validation

VASA ◽  
2012 ◽  
Vol 41 (5) ◽  
pp. 333-342 ◽  
Author(s):  
Kirchberger ◽  
Finger ◽  
Müller-Bühl
Keyword(s):  
Principal Component Analysis ◽  
Intermittent Claudication ◽  
Completion Time ◽  
Short Form ◽  
Principal Component ◽  
Component Analysis ◽  
German Version ◽  
Average Completion Time ◽  
Sf 36 ◽  
Related Quality

Background: The Intermittent Claudication Questionnaire (ICQ) is a short questionnaire for the assessment of health-related quality of life (HRQOL) in patients with intermittent claudication (IC). The objective of this study was to translate the ICQ into German and to investigate the psychometric properties of the German ICQ version in patients with IC. Patients and methods: The original English version was translated using a forward-backward method. The resulting German version was reviewed by the author of the original version and an experienced clinician. Finally, it was tested for clarity with 5 German patients with IC. A sample of 81 patients were administered the German ICQ. The sample consisted of 58.0 % male patients with a median age of 71 years and a median IC duration of 36 months. Test of feasibility included completeness of questionnaires, completion time, and ratings of clarity, length and relevance. Reliability was assessed through a retest in 13 patients at 14 days, and analysis of Cronbach’s alpha for internal consistency. Construct validity was investigated using principal component analysis. Concurrent validity was assessed by correlating the ICQ scores with the Short Form 36 Health Survey (SF-36) as well as clinical measures. Results: The ICQ was completely filled in by 73 subjects (90.1 %) with an average completion time of 6.3 minutes. Cronbach’s alpha coefficient reached 0.75. Intra-class correlation for test-retest reliability was r = 0.88. Principal component analysis resulted in a 3 factor solution. The first factor explained 51.5 of the total variation and all items had loadings of at least 0.65 on it. The ICQ was significantly associated with the SF-36 and treadmill-walking distances whereas no association was found for resting ABPI. Conclusions: The German version of the ICQ demonstrated good feasibility, satisfactory reliability and good validity. Responsiveness should be investigated in further validation studies.

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