Solving for optimal retirement financial plans by maximizing a discounted habit formation utility function

Abstract

With the increasing popularity of defined-benefit retirement plans, retiring individuals are looking for professional financial advice to help manage their nest eggs. Commonly prescribed generic "one size fits all" rules of thumb such as the 4% Rule can carry someone successfully through retirement, but they do not effectively take into account individual expectations or preferences of the retiree or the volatility and risk of the capital markets. An alternative approach is an investment strategy focused on maximizing an individual's utility or "happiness" during retirement. We consider the maximization of a utility function that exhibits habit formation. The programming language C++ is used to implement a solution algorithm for this maximization problem, and Microsoft Excel is utilized as an interface to present and analyze data. The resulting implementation is a planning tool that provides optimized retirement financial plans according to an individual's preferences. We demonstrate the effects of habit formation on optimal retirement consumption and investment plans and show how a dynamic investment and spending strategy that maximizes an individual's utility can provide a major improvement over the rules of thumb currently practiced.