Academic journal article
By Stout, R. Gene; Mitchell, John B.
Financial Services Review , Vol. 15, No. 2
This paper develops a dynamic model of retirement withdrawal planning that allows retirees and financial planners to improve the probability of retirement portfolio success while simultaneously increasing the average withdrawal rate. The key elements of the model are periodic adjustments of retirement withdrawal rates based on both portfolio performance and remaining life expectancy, and Monte Carlo simulation of both investment returns and mortality. The inclusion of mortality in fixed planning horizon models reduces the probability of retirement-portfolio ruin by almost 50%. When compared to fixed withdrawal rate models, dynamic withdrawal management incorporating mortality reduces the probability of ruin by another 35-40% while increasing average lifetime withdrawal rates by nearly 50%. © 2006 Academy of Financial Services. All rights reserved.
JEL classification: G1; G2
Keywords: Retirement portfolio; Adjustable withdrawal rates; Monte Carlo simulation
As the baby boomers enter retirement, the development of retirement withdrawal planning models has become, and will continue to become, increasingly more important. Although the search for simplicity will continue, the pursuit of accuracy will cause planning and control of retirement withdrawals to become increasingly complex. The withdrawal phase of retirement planning may well require more professional guidance and expertise than the accumulation phase.
To date, much of the emphasis of retirement planning models has been on sustainable fixed withdrawal rates from a retirement portfolio subject to uncertain security returns over a fixed planning horizon. These models are static inasmuch as the withdrawal rate and the planning horizon are fixed.
The volatility of market returns causes fixed withdrawal rate plans with reasonable probabilities of running out of money to generate significant increases in average portfolio values (Ameriks, Veres & Warshawsky, 2001; Pye, 2001). These increases in average portfolio values suggest that excess portfolio accumulations are a cost of reducing the probability of ruin.
Furthermore, financial ruin should be defined as the probability of running out of money in the retirement life span, whether that span is shorter or longer than a predetermined number of years. Thus, a first step in improving the accuracy of retirement withdrawal planning is the recognition of the uncertainty of the remaining life span.
This research develops a dynamic retirement withdrawal planning model for controlling retirement withdrawal rates in the context of uncertainty in portfolio performance and remaining life span, as well. The withdrawal management process reduces both the probability of running out of money in retirement and excess wealth accumulation.
2. Literature review
Previous research has explored maximum safe withdrawal rates from retirement portfolios. Bengen (1994) recommends a 4% real withdrawal rate from a portfolio made up of 50% stock and 50% intermediate-term treasuries for retirees age 60-65 and finds that rate sustainable for a minimum of 33 years. He advises that initial retirement portfolios should contain at least 75% equities. Bengen (1997), Tezel (2004), and Cooley, Hubbard and WaIz (1998) confirm the importance of aggressive portfolio allocations in promoting portfolio sustainability over long periods, although Ervin, Filer and Smolira (2005) find that internationally diversified portfolios would have been less successful than U.S. portfolios in providing real fixed monthly withdrawals over the same, 1930 to 2001, time period. While the conclusions of the previous researchers are based upon studying actual sequences of historic security returns, Milevsky (2001) and Ameriks et al. (2001) also find support for substantial equity allocations using simulated market returns.
Subsequently, Cooley, Hubbard and Walz (2003) compare the sustainability of withdrawals over fixed time periods under two methods for determining portfolio returns: simulation and overlapping historic periods. …