scholarly journals OPTIMAL CONTROL OF THE DECUMULATION OF A RETIREMENT PORTFOLIO WITH VARIABLE SPENDING AND DYNAMIC ASSET ALLOCATION

2021 ◽  
pp. 1-34
Author(s):  
Peter A. Forsyth ◽  
Kenneth R. Vetzal ◽  
Graham Westmacott
Keyword(s):  
Asset Allocation ◽  
Asset Returns ◽  
Retirement Savings ◽  
Allocation Strategy ◽  
Investment Portfolio ◽  
Dynamic Asset Allocation ◽  
Dynamic Strategy ◽  
Prior Literature ◽  
Weighted Combination ◽  
Over Time

Abstract We extend the Annually Recalculated Virtual Annuity (ARVA) spending rule for retirement savings decumulation (Waring and Siegel (2015) Financial Analysts Journal, 71(1), 91–107) to include a cap and a floor on withdrawals. With a minimum withdrawal constraint, the ARVA strategy runs the risk of depleting the investment portfolio. We determine the dynamic asset allocation strategy which maximizes a weighted combination of expected total withdrawals (EW) and expected shortfall (ES), defined as the average of the worst 5% of the outcomes of real terminal wealth. We compare the performance of our dynamic strategy to simpler alternatives which maintain constant asset allocation weights over time accompanied by either our same modified ARVA spending rule or withdrawals that are constant over time in real terms. Tests are carried out using both a parametric model of historical asset returns as well as bootstrap resampling of historical data. Consistent with previous literature that has used different measures of reward and risk than EW and ES, we find that allowing some variability in withdrawals leads to large improvements in efficiency. However, unlike the prior literature, we also demonstrate that further significant enhancements are possible through incorporating a dynamic asset allocation strategy rather than simply keeping asset allocation weights constant throughout retirement.

scholarly journals Abnormal Portfolio Asset Allocation Model: Review

2020 ◽  
Vol 1 (1) ◽  
pp. 46-54
Author(s):  
Nurfadhlina Bt Abdul Halima ◽  
Dwi Susanti ◽  
Alit Kartiwa ◽  
Endang Soeryana Hasbullah
Keyword(s):  
Asset Allocation ◽  
Asset Returns ◽  
Higher Moments ◽  
Investment Portfolio ◽  
Allocation Model ◽  
Model Review ◽  
The Mean ◽  
Mean Variance ◽  
Skewness And Kurtosis ◽  
Normally Distributed

It has been widely studied how investors will allocate their assets to an investment when the return of assets is normally distributed. In this context usually, the problem of portfolio optimization is analyzed using mean-variance. When asset returns are not normally distributed, the mean-variance analysis may not be appropriate for selecting the optimum portfolio. This paper will examine the consequences of abnormalities in the process of allocating investment portfolio assets. Here will be shown how to adjust the mean-variance standard as a basic framework for asset allocation in cases where asset returns are not normally distributed. We will also discuss the application of the optimum strategies for this problem. Based on the results of literature studies, it can be concluded that the expected utility approximation involves averages, variances, skewness, and kurtosis, and can be extended to even higher moments.

Glide Paths Based on a Retirement Goal and Depleting Human Capital

2019 ◽  
Keyword(s):  
Human Capital ◽  
Life Cycle ◽  
Asset Allocation ◽  
Retirement Planning ◽  
Retirement Savings ◽  
Financial Assets ◽  
Dynamic Asset Allocation ◽  
Glide Path ◽  
Input Variables ◽  
Glide Paths

The retirement goals of many Americans are underfunded. The problem is compounded by the complexity of self-managing distribution portfolios, particularly as DC plans replace DB plans. We believe most retirement glide paths are satisfactory but suboptimal solutions. We introduce a glide path of financial assets over the life cycle based on a retirement goal and depleting human capital. The method is anchored to the foundational principles of intertemporal portfolio theory while borrowing heavily from goals-based asset allocation. The result is a dynamic asset allocation over the life cycle that is a function of critical input variables relevant to retirement planning such as retirement savings, retirement consumption and risk aversion. The glide path can be customized to individuals, or semi-customized to discrete subpopulations of DC plan participants.

scholarly journals Dynamic Asset Allocation under Mispricing, Predictability and Portable Alpha

2010 ◽  
Vol 11 (1) ◽  
pp. 73-101
Author(s):  
Hyoung-Goo Kang
Keyword(s):  
Portfolio Management ◽  
Asset Allocation ◽  
Information Matrix ◽  
Dynamic Asset Allocation ◽  
Simple Method ◽  
Potential Market ◽  
Dynamic Strategy ◽  
Out Of Sample ◽  
Time Basis ◽  
Risk Managers

The existing literature about portfolio management has investigated how to update a portfolio allocation, conditional on the information that possibly predicts asset returns and volatilities. We add several innovations to fill the lacuna of prior research in the contexts of global asset allocation. First, we suggest a simple method of how to rebalance portfolios automatically and dynamically in order to exploit potential market inefficiencies. The existing literature has not developed such a strategy. Out-of-sample tests demonstrate that our strategy dominates both static allocation and dynamic strategies that do not account for possible mispricing. Thus, our strategy can contribute not only to academia, but also to practical portfolio managers who endeavour to beat markets. Second, we elaborate portable alpha strategies using the new dynamic strategy. Once we add an alpha strategies using the new dynamic strategy. Once we add an alpha portfolio to existing portfolios, then they perform better in terms of mean and risk. Thus, it makes our alpha portfolio portable, i.e., we can apply the alpha portfolio to any fund and can enhance its performance. Third, our dynamic strategy implies a convenient method to estimate a conditional mean and covariance matrix as functions of predictive information matrix without consuming much computational risk managers and traders who need to control the risks of large target portfolios on a real time basis.

Dynamic Asset Allocation

1987 ◽  
Vol 1987 (1) ◽  
pp. 82-85, 93
Author(s):  
H. Gifford Fong
Keyword(s):  
Asset Allocation ◽  
Dynamic Asset Allocation
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