Abstract

Very little research has been done on strategic financial planning software programming. Today's approach is to perform a single simulation, calculation, or utility application and assume the results apply to all times and allocations for all future ages. But time periods change with age as do allocation characteristics over time. This paper steps back to look at financial planning software programming as a foundational strategy to model retirement income while aging that same retiree over time, meaning looking at all the possible future time periods as well as all prudent allocations over those possible future time periods. Additionally, research to date has focused on “early stage” retirement meaning the retirement event occurs sometime in the retiree’s age-60’s. In other words, the inception of retirement. Little research has been done looking at the transition into later stage ages or later allocations for portfolio income distributions through “late stage” retirement years. It is not enough to know how to initiate retirement. It is also necessary to know how to sustain retirement spending prudently, as well as how spending decisions ripple through age to future bequest balances. This paper reviews concepts on how to imagine that transition to and through late-stage retirement and develop better software programming using a data cloud concept to accomplish that early-to-late stage retirement income modeling based on research evidence. The author is a practitioner nearing nearly three decades specializing in research and application of drawdown of portfolios for supplemental retirement income, clinically with many different retirees of many different ages all at the same moment in time. The author also has numerous research papers published in the Journal of Financial Planning and numerous other published papers leading to the thoughts in these referenced papers and below. The author suggests integrating many different disciplines is important to advancing retirement income planning into more focused modeling, rather than today’s single simulation approach.

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