Deep neural network for optimal retirement consumption in defined contribution pension system
Réseau de neurones profond pour consommation à la retraite optimale en système de retraite à cotisations définies
Wen Chen and
Nicolas Langrené ()
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Wen Chen: CSIRO - Commonwealth Scientific and Industrial Research Organisation [Australia]
Nicolas Langrené: CSIRO - Commonwealth Scientific and Industrial Research Organisation [Australia]
Working Papers from HAL
Abstract:
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. Our results show that stronger risk aversion generates a flatter consumption pattern; however, there is not much difference in consumption with or without bequest until age 103. 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. Specifically, the optimal consumption level is slightly lower for females until age 84.
Keywords: decumulation; retirement income; deep learning; stochastic control; economic scenario generator; defined-contribution pension; optimal consumption (search for similar items in EconPapers)
Date: 2020-07-31
New Economics Papers: this item is included in nep-age, nep-cmp and nep-upt
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