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Application of data clustering and machine learning in variable annuity valuation

机译:数据聚类和机器学习在可变年金评估中的应用

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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.
机译:在过去的四十年中,可变年金担保的评估得到了广泛的研究。但是,几乎所有研究都集中在单个可变年金合同中嵌入的担保的估值上。如何有效地为大型可变年金合同的投资组合的担保定价,尚未引起足够的重视。本文通过介绍一种基于数据聚类和机器学习的新方法来填补大量可变年金合同的担保价格,从而填补了空白。我们的测试结果表明,该方法在准确性和速度方面都表现出色。

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