JSM 2012 Home

JSM 2012 Online Program

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

Online Program Home

Abstract Details

Activity Number: 472
Type: Contributed
Date/Time: Wednesday, August 1, 2012 : 8:30 AM to 10:20 AM
Sponsor: Business and Economic Statistics Section
Abstract - #305114
Title: An Innovative Estimation Approach
Author(s): Yang Yu*+ and John Chen
Companies: Bowling Green State University and Bowling Green State University
Address: Dept. of Mathematics and Statistics, Bowling Green, OH, 43403, United States
Keywords: Skew-Normal ; MLE ; Algorithm

When analyzing volatility forecasting bi-variate time series with applications in investment, option pricing and risk management, S. Poon and Clive Granger (2006) advocated the use of a skew-t model, which has a corresponding skew normal family proposed in Chen (2010). The new skew-normal distribution has two pieces defined, respectively, for x < µ and x>= µ, where µ is the location parameter. In addition there are two parameters, the variance t and the skewness parameter ?. In the conventional method of MLE to estimate the three parameters, the explicit forms of algebraic solutions for this new family do not exist. In this talk, a new MLE method of estimation is derived. We established an algorithm to seek the overall MLE from the local MLE when the location parameter is restricted in a partition of the sample space. Following that, the MLEs of t and ? can be consequently computed. Compared with the conventional skew-normal model (which has singular information matrix in the MLE process), the advantage of this new skew-normal family is that the maximum likelihood estimators can be found by the new algorithm.

The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2012 program

2012 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.