STATISTICS COLLOQUIUM
Himchan Jeong, PhD
Assistant Professor
Dept. of Statistics and Actuarial Science
Simon Fraser University
A non-convex regularization approach for stable estimation of loss development factors
Abstract
In this article, we apply non-convex regularization methods in order to obtain stable estimation of loss development factors in insurance claims reserving. Among the non-convex regularization methods, we focus on the use of the log-adjusted absolute deviation (LAAD) penalty and provide discussion on optimization of LAAD penalized regression model, which we prove to converge with a coordinate descent algorithm under mild conditions. This has the advantage of obtaining a consistent estimator for the regression coefficients while allowing for the variable selection, which is linked to the stable estimation of loss development factors. We calibrate our proposed model using a multi-line insurance dataset from a property and casualty insurer where we observed reported aggregate loss along accident years and development periods. When compared to other regression models, our LAAD penalized regression model provides very promising results.
Bio: Dr. Himchan Jeong is an Assistant Professor in the Department of Statistics and Actuarial Science at Simon Fraser University, Canada. He is a Fellow of the Society of Actuaries (SOA) and holds a Ph.D. from the University of Connecticut. He has been actively involved in teaching and conducting research in actuarial science for several years. In recognition for his academic achievements and excellence, he has been awarded the James C. Hickman Scholarship from SOA recently in 2018-2020.
His current research interest is predictive modeling for ratemaking and reserving of property and casualty insurance.
Event address for attendees: https://uconn-cmr.webex.com/uconn-cmr/onstage/g.php?MTID=e1ca1f81f7e6101bac1f064ea8fcba33f
There is also a call-in option: US Toll +1-415-655-0002
Access code: 120 464 6340
Date: Wednesday, February 24, 2021
Time: 4:00 p.m. EST, 1-hour duration
For more information, contact: Tracy Burke at tracy.burke@uconn.edu