An empirical comparison of some experimental designs for the valuation of large variable annuity portfolios

Guojun Gan, and Emiliano A. Valdez. "An empirical comparison of some experimental designs for the valuation of large variable annuity portfolios." Dependence Modeling 4.1 (2016): 382-400, electronic only. <http://eudml.org/doc/287121>.

@article{GuojunGan2016,
abstract = {Variable annuities contain complex guarantees, whose fair market value cannot be calculated in closed form. To value the guarantees, insurance companies rely heavily on Monte Carlo simulation, which is extremely computationally demanding for large portfolios of variable annuity policies. Metamodeling approaches have been proposed to address these computational issues. An important step of metamodeling approaches is the experimental design that selects a small number of representative variable annuity policies for building metamodels. In this paper, we compare empirically several multivariate experimental design methods for the GB2 regression model, which has been recently discovered to be an attractive model to estimate the fair market value of variable annuity guarantees. Among the experimental design methods examined, we found that the data clustering method and the conditional Latin hypercube sampling method produce the most accurate results.},
author = {Guojun Gan, Emiliano A. Valdez},
journal = {Dependence Modeling},
keywords = {Variable annuity; Portfolio valuation; Metamodeling; Generalized beta of the second kind (GB2); Multivariate experimental design; Data clustering; Latin hypercube; variable annuity; portfolio valuation; metamodeling; generalized beta of the second kind (GB2); multivariate experimental design; data clustering},
language = {eng},
number = {1},
pages = {382-400, electronic only},
title = {An empirical comparison of some experimental designs for the valuation of large variable annuity portfolios},
url = {http://eudml.org/doc/287121},
volume = {4},
year = {2016},
}

TY - JOUR
AU - Guojun Gan
AU - Emiliano A. Valdez
TI - An empirical comparison of some experimental designs for the valuation of large variable annuity portfolios
JO - Dependence Modeling
PY - 2016
VL - 4
IS - 1
SP - 382
EP - 400, electronic only
AB - Variable annuities contain complex guarantees, whose fair market value cannot be calculated in closed form. To value the guarantees, insurance companies rely heavily on Monte Carlo simulation, which is extremely computationally demanding for large portfolios of variable annuity policies. Metamodeling approaches have been proposed to address these computational issues. An important step of metamodeling approaches is the experimental design that selects a small number of representative variable annuity policies for building metamodels. In this paper, we compare empirically several multivariate experimental design methods for the GB2 regression model, which has been recently discovered to be an attractive model to estimate the fair market value of variable annuity guarantees. Among the experimental design methods examined, we found that the data clustering method and the conditional Latin hypercube sampling method produce the most accurate results.
LA - eng
KW - Variable annuity; Portfolio valuation; Metamodeling; Generalized beta of the second kind (GB2); Multivariate experimental design; Data clustering; Latin hypercube; variable annuity; portfolio valuation; metamodeling; generalized beta of the second kind (GB2); multivariate experimental design; data clustering
UR - http://eudml.org/doc/287121
ER -