Variable annuities (VAs) are increasingly becoming popular insurance products in many developed countries which provide guaranteed forms of income depending on the performance of the equity market. Insurance companies often hold large VA portfolios and the associated valuation of such portfolios for hedging purposes is a very time-consuming task. There have been several studies focusing on inventing techniques aimed at reducing the computational time including the selection of representative VA contracts and the use of a metamodel to estimate the values of all contracts in the portfolio. In addition to the selection of representative contracts, this paper proposes using LASSO regression to select a set of representative scenarios, which in turn allows for the set of representative contracts to expand without significant increase in computational load. The proposed approach leads to a remarkable improvement in the computational efficiency and accuracy of the metamodel.

中文翻译：

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使用 LASSO 回归进行场景选择以评估可变年金投资组合

可变年金（VA）在许多发达国家日益成为流行的保险产品，根据股票市场的表现提供有保障的收入形式。保险公司通常持有大量的VA投资组合，而出于对冲目的对此类投资组合进行相关估值是一项非常耗时的任务。有几项研究侧重于发明旨在减少计算时间的技术，包括选择代表性的 VA 合约以及使用元模型来估计投资组合中所有合约的价值。除了选择代表性合约之外，本文还提出使用 LASSO 回归来选择一组代表性场景，从而允许代表性合约集在不显着增加计算负载的情况下进行扩展。所提出的方法显着提高了元模型的计算效率和准确性。