摘要：Many loss reserving models are over-parameterized yet ignore calendar-year (diagonal) effects. Venter [1] illustrates
techniques to deal with these problems in a regression environment. Venter [2] explores distributional approaches
for the residuals. Gluck [3] shows that systematic effects can increase the reserve runoff ranges by more
than would be suggested by models fitted to the triangle data alone. Quarg and Mack [4] show how to get more
information into the reserve estimates by jointly using paid and incurred data.
This paper uses the basic idea and data from [4] and the methods of [1] to build simultaneous regression models
of the paid and incurred data, including diagonal effects and eliminating non-significant parameters. Then alternative
distributions of the residuals are compared in order to find an appropriate residual distribution. To get a
runoff distribution, parameter and process uncertainty are simulated from the fitted model. The methods of
Gluck [3] are then applied to recognize further effects of systematic risk.
Once the final runoff distribution is available, a possible application is estimating the market value pricing of the
reserves. Here this is illustrated using probability transforms, as in Wang [5].
关键词：Reserving Methods; Reserve Variability; Uncertainty and Ranges, Fair Value, Probability Transforms,
Bootstrapping and Resampling Methods, Generalized Linear Modeling.
