Li, Muyi

Associate Professor


Phone:0592-2185887

Email:limuyi1981@gmail.com

Office:D208

Biography Research Papers Research Projects

Research Interests:
 
Time series analysis(theory and application), Econometrics.
 
Education
 
Ph.D. in Statistics, The University of Hong Kong, 2007-2011.
M.S. in Probability and Statistics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, 2002-2005.
B.S. in Mathematics, AnHui University, 1998-2002.

Employment:

Sept. 2011-present: Assistant Professor, jointly appointed by Department of Statistics, School of Economics and Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
Lecturer for: Advanced Econometrics (I) (graduate level), Time Series Analysis (undergraduate  level )
 
Sept.2007-July 2011: Teaching Assistant, The University of Hong Kong
Tutor for: Time Series Analysis; Financial Data Analysis; Project Based on SAS;  Business Statistics
 
Sept. 2005 - Jul. 2007: Lecturer, School of Science, JiMei University, XiaMen, China.

 

 
Publication 

1. Muyi Li, Guodong Li and Wai Keung Li (2011). "Score Tests for Hyperbolic GARCH Models", Journal of Business and Economic Statistics, Vol 29(4):579-586.
2. Muyi Li, Wai Keung Li and Guodong Li (2013). "On Mixture Memory GARCH Models", Journal of Time Series Analysis,34:606-624.
3. Muyi Li and Yongxiang Huang (2014).  "
Hilbert-Huang Transform based multifractal analysis of China stock market", accepted by 
 Physica A: Statistical Mechanics and its Applications. 


Working Paper 

1. Muyi Li, Guodong Li and Wai Keung Li (2013). "On a New Hyperbolic GARCH Model", submitted.
2. Dong Li, Muyi Li* and Wuqing Wu (2013). "On Dynamics of Volatilities in Nonstationary Semi-Strong GARCH Model, submitted.
3. Muyi Li, Dong Li and Lianbin Zeng (2014). "Subsampling Inference in Threshold ARMA Models", submitted
Natural Science Foundation of China (NSFC), Title: Probability Proerties and Statistical Inference on Long Meory Volatility Models. 2014-2016.
Social Science Foundation of Fujian Province. Title:  Testing long memory and change point processes base on Whittle Likelihhood Information. 2013-2014.