Application of data clustering and machine learning in variable annuity valuation

被引:72
|
作者
Gan, Guojun [1 ]
机构
[1] Manulife Financial, Global Variable Annu Hedging Dept, Toronto, ON M4W 1E5, Canada
来源
INSURANCE MATHEMATICS & ECONOMICS | 2013年 / 53卷 / 03期
关键词
Variable annuity; Data clustering; Machine learning; Monte Carlo simulation; Portfolio valuation; Portfolio pricing; LINKED LIFE-INSURANCE; MINIMUM WITHDRAWAL BENEFITS; STOCHASTIC INTEREST-RATES; EQUITY-INDEXED ANNUITIES; MATURITY GUARANTEES; DEATH BENEFITS; CONTRACTS; OPTIONS; MODEL; ALLOCATION;
D O I
10.1016/j.insmatheco.2013.09.021
中图分类号
F [经济];
学科分类号
02 ;
摘要
The valuation of variable annuity guarantees has been studied extensively in the past four decades. However, almost all the studies focus on the valuation of guarantees embedded in a single variable annuity contract. How to efficiently price the guarantees for a large portfolio of variable annuity contracts has not received enough attention. This paper fills the gap by introducing a novel method based on data clustering and machine learning to price the guarantees for a large portfolio of variable annuity contracts. Our test results show that this method performs very well in terms of accuracy and speed. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:795 / 801
页数:7
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