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arXiv 2007.09911q-fin.GNcs.LG
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固定缴款养老金制度中最优退休消费的深度神经网络

Deep neural network for optimal retirement consumption in defined contribution pension system

Commonwealth Scientific and Industrial Research Organisation(澳大利亚联邦科学与工业研究组织)

Wen Chen, Nicolas Langrené

摘要:

在本文中,我们开发了一种深度神经网络方法来解决一个基于寿命预期死亡率加权效用的模型,用于在固定缴款养老金制度的累积阶段实现最优消费。我们将此问题表述为多周期有限时域随机控制问题,并训练代表消费决策的深度神经网络策略。最优消费政策是由退休人员的个人信息,如年龄,财富,风险规避和遗赠动机,以及一系列的经济和金融变量,包括通货膨胀率和资产回报率共同模拟从一个建议的七因素经济情景发生器校准从市场数据确定。我们以澳大利亚的养老金制度为例,考虑到政府资助的经济状况调查老年养老金和其他实际方面,如基金管理费。我们数值测试的主要结果如下。首先,我们的深度神经网络最优消费政策适应市场条件的变化,优于文献中提出的确定性缩减规则。此外,随着训练迭代次数的增加,样本外性能优于率也会增加,最终在不到10分钟的训练后,在所有测试场景中都达到了优于率。其次,进行了敏感性分析,以揭示风险规避和遗赠动机如何改变退休人员的一生在这个效用框架下的消费。第三,我们提供了不同的起始财富余额的最优消费率。我们观察到,最优消费率是不成比例的初始财富,由于养老金支付。第四,在初始财富平衡和效用参数设置相同的情况下,由于死亡率的性别差异,男性和女性的最优消费水平不同。

英文摘要:

In this paper, we develop a deep neural network approach to solve a lifetime expected mortality-weighted utility-based model for optimal consumption in the decumulation phase of a defined contribution pension system. We formulate this problem as a multi-period finite-horizon stochastic control problem and train a deep neural network policy representing consumption decisions. The optimal consumption policy is determined by personal information about the retiree such as age, wealth, risk aversion and bequest motive, as well as a series of economic and financial variables including inflation rates and asset returns jointly simulated from a proposed seven-factor economic scenario generator calibrated from market data. We use the Australian pension system as an example, with consideration of the government-funded means-tested Age Pension and other practical aspects such as fund management fees. The key findings from our numerical tests are as follows. First, our deep neural network optimal consumption policy, which adapts to changes in market conditions, outperforms deterministic drawdown rules proposed in the literature. Moreover, the out-of-sample outperformance ratios increase as the number of training iterations increases, eventually reaching outperformance on all testing scenarios after less than 10 minutes of training. Second, a sensitivity analysis is performed to reveal how risk aversion and bequest motives change the consumption over a retiree's lifetime under this utility framework. Third, we provide the optimal consumption rate with different starting wealth balances. We observe that optimal consumption rates are not proportional to initial wealth due to the Age Pension payment. Forth, with the same initial wealth balance and utility parameter settings, the optimal consumption level is different between males and females due to gender differences in mortality.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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