电子邮箱: yaoxiao18@cufe.edu.cn

个人主页：https://sites.google.com/view/yaoxiao18/%E9%A6%96%E9%A1%B5


教育背景

2011.9—2015.1 管理科学博士, 信用风险方向
爱丁堡大学商学院信用研究中心
博士论文: “公司债券与银行贷款的违约损失率模型”

2008.9—2011.7 运筹学硕士
中国科学院数学与系统科学研究院
硕士论文: “改进的支持向量机模型及其在信用风险评估中的应用”

2004.9—2008.7 应用数学学士
北京林业大学理学院


研究兴趣

银行与金融市场的信用风险，系统风险和金融稳定性，个人与企业征信管理


工作经历

2018.9 至今 助理教授，中央财经大学商学院

2015.1-2018.7 高级分析师, 风险模型与分析组, 苏格兰皇家银行


论文发表

[1] Zhiyong. Li, K. Li, X. Yao & Q, Wen (2019). Predicting Prepayment and Default Risks of Unsecured Consumer Loans in Online Learning. Emerging Markets of Finance and Trade, 55(1), 118-132.

[2] X. Yao, J. Crook and G. Andreeva (2017). “Is It Obligor or Instrument That Explains Recovery Rate: Evidence from US Corporate Bond”, Journal of Financial Stability, 28, 1-15.

[3] X. Yao, J. Crook and G. Andreeva (2017). Enhancing Two-Stage Modelling Methodology for Loss Given Default with Support Vector Machines, European Journal of Operational Research, 263(2), 679-689.

[4] X. Yao, J. Crook and G. Andreeva (2015). “Support vector regression for loss given default modelling”, European Journal of Operational Research, 240(2), 528-538.

[5] Lean. Yu, X. Yao (2013). A total least squares proximal support vector classifier for credit risk evaluation. Soft Computing, 17(4), 643-650.

[6] Lean. Yu, X. Yao, Shouyang Wang, K.K. Lai (2011). Credit risk evaluation using a weighted least squares SVM classifier with design of experiment for parameter selection, Expert Systems with Applications, 38(12), 15392-15399.

[7] 姚潇, 余乐安 (2012). 模糊近似支持向量机模型及其在信用风险评估中的应用. 系统工程理论与实践, 3, 549-554.

工作论文

X. Yao & Lean. Yu. A Novel Dual-Weighted Fuzzy Proximal Support Vector Machine with Application to Credit Risk Analysis

X. Yao & Lean. Yu, Least Squares Support Vector Regression Based on Fixed Margin Strategy, working paper.

X. Yao, Default and recovery risk correlation: A case study of US corporate bonds.


教学经历

2018.9 中央财经大学商学院
管理研究方法 (36学时)

2013.9—2014.6 爱丁堡大学商学院硕士生课程助教
? SAS编程入门 (独立授课，20学时)
? 信用风险管理 (助教，20学时)


学术会议报告

2014.10 Analyzing Corporate Bond Recovery Rates: An Empirical Study on the Impacts of Unobservable Firm Heterogeneity (分组报告)
2014 FMA Annual Meeting, Nashville, Tennessee, USA.

2014.7 Two-Stage Modeling for Recovery Rates: A Case Study of UK Retail Credit Cards (分组报告)
20th Conference of the International Federation of Operational Research Societies, Barcelona.

2014.6 Use of SAS in PhD Research (邀请报告)
SAS Professionals Convention 2014, Marlow, UK.

2014.3 Modeling Loss Given Default in SAS/STAT (2014 SAS学生大使奖学金，分组报告)
SAS Global Forum 2014, Washington, D. C., USA.

2013.8 Predicting Loss Given Default: An Extension of Single Factor Model (分组报告)
Credit Scoring and Credit Control XIII, Edinburgh, UK

2013.7 Does Random Effect Make the LGD Predictions Better (分组报告)
26th European Conference on Operational Research, Rome, Italy

2010.10 A Fuzzy Proximal Support Vector Machine in Credit Risk Evaluation (分组报告)
9th Financial System Engineering and Risk Management Conference, Beijing, China


荣誉及获奖经历

2014 2014 SAS公司全球学生大使

2009 中科院优秀学生干部

2007 教育部国家奖学金

2006 北京林业大学校一等奖学金