Research On The Prediction Of Corporate Bond Defaults Risk——Based On The Case of Xiang’e Debt

中国公司债券起始于2007年，经过8年的发展，已经取得显著的成绩。从总体上看，中国企业最主要的融资方式是银行贷款，直接融资与间接融资比例不平衡。然而随着中央对债券市场的重视程度不断加强，公司债券将会作为债券市场发展的重点之一着重发展。在国际债券市场，公司债券违约是正常现象，而随着中国公司债券市场如火如荼的快速发展，公司债券违约事件也开始出现。做为一个公司债券投资者，事前预警远比事后预警更有效果，该如何预测公司债券违约风险发生呢？本文选取中国公募债券第一起本金刚性兑付被打破的湘鄂债为例，收集了2010-2014年的财务数据，首先使用了财务指标进行违约风险预测，继而运用Altman多元判别Z-sc...Chinese corporate bonds began in 2007,after eight years of development,we have made great achievements. In general, the most important way for Chinese enterprises to finance is bank loan,direct financing and indirect financing imbalance.However,with the central government emphasis on the bond market continued to strengthen,corporate bonds will serve as one of the key focus on the development of bo...学位：工商管理硕士院系专业：管理学院_工商管理硕士(工商管理硕士)学号：1792014115093

External Validation of Risk Prediction Models for Postpartum Stress Urinary Incontinence

BackgroundOur research team developed two prediction models of postpartum stress urinary incontinence (PSUI) , one for primiparas, and the other for multiparae, aiming at early identifying women at high risk of PSUI, and providing effective interventions, but they have not yet been externally validated.ObjectiveTo externally validate the risk prediction models of PSUI previously developed by us to assess their clinical applicability.MethodsThis study was conducted between July and September 2020. Participants were 6-month postpartum women (validation group) who were selected from the electronic medical record system of Shenzhen Hospital of Southern Medical University, and the University of Hong Kong-Shenzhen Hospital. Information about age, height, pre-pregnancy weight, abortion history, and delivery history was collected from the electronic medical record system of the two hospitals. A telephone follow-up was conducted to investigate the incidence of stress urinary incontinence within 6-month postpartum. The area under the receiver operating characteristic curve (AUC) was computed to estimate the value of the predictive models in discriminating PSUI. Hosmer-Lemeshow goodness-of-fit test was used to examine the calibration of the prediction models.ResultsA total of 298 cases were included, and 203 of them (68.1%) were primiparas (158 with PSUI, and other 45 without) , other 95 (31.9%) were multiparae (72 with PSUI, and other 23 without) . The AUC of the risk prediction model for PSUI in primiparas was 0.719〔95%CI (0.643, 0.795) 〕, and that of the risk prediction model for PSUI in multiparae was 0.833〔95%CI (0.738, 0.928) 〕. Hosmer-Lemeshow goodness-of-fit test suggested that the PSUI risk prediction model for primiparas had poor calibration (χ2=34.11, P<0.001) , while that for multiparae had satisfactory calibration (χ2=9.62, P=0.293) .ConclusionThe PSUI risk prediction model for primiparas could effectively distinguish PSUI, but its applicability needs to be further improved. The PSUI risk prediction model for multiparae had acceptable performance, which may be used and promoted as an evaluation tool for early pelvic floor rehabilitation in multiparae

Risk-Neutral Skewness and Implied Volatility Skew: The Tail Risk Prediction or Investor Sentiment？

本文从S&P500指数期权数据中提取出风险中性偏度与波动率偏斜，对风险中性偏度和波动率偏斜时间序列的研究发现，它们存在自相关与条件异方差。我们采用多项Logistic模型来研究在短期、中期和长期中风险中性偏度、波动率偏斜与市场尾部风险之间的关系。结果表明，风险中性偏度与波动率偏斜含有未来市场尾部风险的信息，但这并不意味着期权市场能够准确预测现货市场的尾部风险。从预测期限来看，风险中性偏度与波动率偏斜对市场尾部风险的解释力度并未随着预测期限的增长而减弱。最后本文着手研究风险中性偏度和波动率偏斜与市场情绪之间的关系。结果显示，投资者情绪能够解释S&P500指数期权的波动率偏斜与风险中性偏度。当市场...We extract risk-neutral skewness and volatility skew from the S&P500 index option data. With a time series study of the risk-neutral skewness and volatility skew, we find that they exhibit autocorrelation and conditional heteroscedasticity. We use multinomial logistic model to study the short-term, medium-term and long-term relationship among risk-neutral skewness, volatility skew, and market tail...学位：经济学硕士院系专业：经济学院_金融工程学号：1562010115195

Research on Theory and Application of Stock Index Futures Volatility Model ——Empirical Analysis of ARMA(p,q)-EGARCH(1,1) Volatility Model Based on Basis Risk and Application on Stock Index Futures’ Risk Prediction

股指期货的市场风险又称为价格风险，是指由于股指期货合约价格的变化而引起的未来损失的可能性，主要表现为股指期货价格的波动性。波动率不仅是基本证券和金融衍生产品合理定价的核心变量，同时也是VaR、RiskMetrix等已被广泛运用的风险度量模型预测未来风险的基础。为此，在我国股指期货即将推出之际，构建模型来研究股指期货市场的波动性特征并精确预测股指期货波动率，对于有效地测量、控制和管理股指期货市场的交易风险，发展一个健康、健全的股指期货市场对经济的繁荣和稳定有着重大意义。鉴于此，本文尝试在这个领域根据我国的自身特征作一些创新性的研究。 首先本文对国内外有关股指期货的研究成果和ARCH簇波动率模型...Market risk of stock index futures is also known as price risk, refers to the stock index futures contracts due to price changes caused by the possibility of future losses, mainly show as a stock index futures price volatility. Volatility is not only the core variables for reasonable pricing of the basic securities and financial derivative products, but also has been widely used in risk measuremen...学位：经济学硕士院系专业：经济学院财政系_资产评估学号：1552007115005

Comparison of Three Risk Prediction Models for Carotid Atherosclerosis in Steelworkers

BackgroundAs a leading cause of ischemic cerebrovascular disease, carotid atherosclerosis (CAS) lowers the productivity of steelworkers. An increasing number of scholars have used machine learning to identify readily available factors to predict the risk of diseases. But there is still a lack of research on risk prediction models for CAS.ObjectiveTo compare the performance of support vector machine (SVM) -, BP neural network (BPNN) - and random forest (RF) -based models in predicting the risk of CAS in steelworkers.Methods4 568 steelworkers who underwent physical examination and health monitoring in Tangshan Hongci Hospital from March to June 2017 were selected for a survey using the Health Assessment Checklist developed by us for understanding their information about demographic characteristics (sex, age, BMI, education level, marital status) , personal behavior and lifestyle (smoking and drinking) , medical history (hypertension, diabetes, family history of CAS) , occupation history (current work in shifts, working under high temperature or in noisy environments) . Levels of serum cholesterol, triglyceride, homocysteine and uric acid were also collected. Variables for building SVM-, BPNN- and RF-based models for predicting the risk of CAS were determined using unconditioned multivariate Logistic regression analysis and literature review.ResultsIn predicting the risk of CAS in participants in the training set, the accuracy, sensitivity and specificity were 83.81%, 80.10%, 87.32%, respectively, for the SVM-based model, 79.27%, 66.19%, 91.62%, respectively, for the BPNN-based model, and 86.60%, 73.62%, and 98.90%, respectively, for the RF-based model. And the AUC for SVM-, BPNN- and RF-based models was 0.84, 0.79 and 0.86, respectively. The SVM-based model had the highest sensitivity, while the RF-based model had the highest accuracy and specificity (P<0.05) . In predicting the risk of CAS in participants in the test set, the accuracy, sensitivity and specificity were 85.70%, 81.63%, 90.29%, respectively, for the SVM-based model, 75.46%, 64.65%, 87.66%, respectively, for the BPNN-based model, and 73.37%, 60.00%, and 88.45%, respectively, for the RF-based model. And the AUC for SVM-, BPNN- and RF-based models was 0.86, 0.76, and 0.74, respectively. The SVM-based model had the greatest accuracy, sensitivity and AUC. The sensitivity, accuracy and AUC of the SVM-based model were significantly different from those of the BPNN- or RF-based model in predicting the CAS risk (P<0.05) .ConclusionThe SVM-based model may be better than other two models in predicting the risk of CAS in steelworkers

企业经营风险预警指标体系设计与预警系统模型设计

随着我国企业经营环境的显著改变,市场化程度的持续提高,对风险管理的需求和意义越来越高。本文立足于对中国石油天然气股份有限公司华北分公司的分析,归纳出营销类企业经营风险的指标体系,并在此基础上对该企业的经营风险预警体系和模型作了比较深刻的探讨

Research Progress and Application Prospect of Facial Micro-Expression Analysis in Forensic Psychiatry

Research on facial micro-expression analysis has been going on for decades. Micro-expression can reflect the true emotions of individuals, and it has important application value in assisting auxiliary diagnosis and disease monitoring of mental disorders. In recent years, the development of artificial intelligence and big data technology has made the automatic recognition of micro-expressions possible, which will make micro-expression analysis more convenient and more widely used. This paper reviews the development of facial micro-expression analysis and its application in forensic psychiatry, to look into further application prospects and development direction

风险预测与忧患深思:人工智能对教育发展的冲击与变革——哲学与伦理的思考

近年来,人工智能的重大价值已然受到各国政府的战略性重视。人工智能在贡献世界、发挥影响、促成改变的同时,也易于诱发系列风险危机,例如劳动的脱嵌与消匿、人与人的疏远与隔离、人类的被超越与被控制等。对于教育而言,人工智能将带来冲击与颠覆,譬如人工智能的超级泛在是否会导致人与教育的分离脱节?人工智能的科技依赖是否会导致人文教育的缺失让位?人工智能的全能覆盖是否会导致教师职业的沦陷取代?总体而言,我们对人工智能应持理性态度,既不能放任自流,也不能因噎废食,在开拓教育前线的同时,守住教育的底线。教育部哲学社会科学研究重大课题“‘互联网+’教育体系研究”(16JZD043)研究成

Construction and Verification of A Nomogram Model for Predicting Invasive Risk of Ground Glass Nodules

Objective To investigate the importance of a nomogram model based on biomarkers and CT signs in the prediction of the invasive risk of ground glass nodules. Methods A total of 322 patients with ground glass nodule, including 240 and 82 patients in the model and verification groups, respectively, were retrospectively analyzed. Independent risk factors for the invasive risk of ground glass nodules were screened out after using single and multiple Logistic analysis. R software was used to construct the nomogram model, and clinical decision curve analysis (DCA), receiver operating curve (ROC), and calibration curve were used for internal and external verification of the model. Results In this study, the independent risk factors for the invasive risk of ground glass nodules included systemic immune-inflammation index (SII), CYFRA21-1, edge, vascular cluster sign, and nodular consolidation tumor ratio (CTR). The area under the ROC curve of the constructed nomogram model had a value of 0.946, and that of the external validation group reached 0.932, which suggests the good capability of the model in predicting the invasive risk of ground glass nodules. The model was internally verified through drawing of calibration curves of Bootstrap 1000 automatic sampling. The results showed that the consistency index between the model and actual curves reached 0.955, with a small absolute error and good fit. The DCA curve revealed a good clinical practicability. In addition, nodule margin, vascular cluster sign, and CTR were correlated with the grade of pathological subtype of invasive adenocarcinoma. Conclusion A nomogram model based on biomarkers and CT signs has good value and clinical practicability in the prediction of the invasive risk of ground glass nodules

The Application of Data Mining in Personal Credit Risk Controlling and Forecasting

近年来，随着中国经济发展使城乡居民收入和消费水平明显提高，个人信贷消费市场已经成为国内金融机构的重点发展业务，但是目前多数金融机构对信用风险的评价基本建立在专家系统之上，带有很大的人为主观因素。因此，特别是研究如何将数据挖掘技术应用到银行的个人信用风险分析，如何防范个人信用风险，选择合理的科学风险评价和预测模型，具有重要的理论意义和现实价值。本文首先根据出现信用违约情况的概率大小来划分信用风险等级进而对其进行信用额度授权，以达到风险控制的目的；然后运用决策树、神经元网络、聚类分析进行挖掘分析，建立风险评估模型，根据模型得到准确的违约概率。同时也分析各个数据挖掘方法在个人信用分析中的应用范围，对...In recent years, with the constant development of the market economy in our country, incomes and the level of consumption of both rural and urban residents have increased steadily. Many bank institutions have made consume loan market a strategic priority. Consume loan market grows very quickly. They need personal credit analysis methods and analysis systems urgently. But many banks use expert syst...学位：经济学硕士院系专业：经济学院计划统计系_经济信息管理学学号：20041004