首页> 外文期刊>Journal of computational science >GPU parallel implementation for asset-liability management in insurance companies
【24h】

GPU parallel implementation for asset-liability management in insurance companies

机译:GPU并行实现,可用于保险公司的资产负债管理

获取原文
获取原文并翻译 | 示例

摘要

In this work we present a stochastic asset liability management (ALM) model for a life insurance company together with its numerical simulation, based in a Monte Carlo balance sheet projection, and we carry out its efficient parallel computation using graphics processing units (GPUs) hardware. The liabilities of the company consist of a portfolio comprising with-profit life insurance policies, that evolve according to the policyholder saving account, surrender and biometric models. On the asset side, we mainly consider bonds, equity and cash, so that appropriate stochastic models are considered for their evolution. We consider some innovations with respect to literature in the modeling of the surrenders of the policyholders. Another important innovative aspect comes from the implementation of ALM in the new high performance computing architectures provided by GPUs technology. Numerical results illustrate the high speed up of the calculus by using GPUs and the coherence of the computations (asset evolution, default probabilities and so on). (C) 2017 Elsevier B.V. All rights reserved.
机译:在这项工作中,我们基于蒙特卡洛资产负债表投影,为人寿保险公司提供了一种随机资产负债管理(ALM)模型及其数值模拟,并使用图形处理单元(GPU)硬件对其进行了有效的并行计算。该公司的负债包括一个包含有利润的人寿保险单的投资组合,该保险单根据保单持有人的储蓄帐户,退保和生物特征识别模型而变化。在资产方面,我们主要考虑债券,股票和现金,因此要考虑其发展的适当随机模型。我们在保单持有人投降模型中考虑了一些有关文学的创新。另一个重要的创新方面是在GPU技术提供的新型高性能计算体系结构中实施ALM。数值结果说明了通过使用GPU以及计算的一致性(资产演化,默认概率等),微积分的速度加快了。 (C)2017 Elsevier B.V.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号