Determining Sustainable/Optimal Withdrawal Rates Using Monte Carlo Simulations

Taylor Chase-Bynum and Henry Stone

Mentors: Nathan Henkel, James Whitehead III, Dr. Raymond Perkins, and Dr. Alex Hagen

T. Rowe Price

The topic of our research is Quantitative Finance and Lifecycle Research, along with the 4% rule. Quantitative finance is an area in finance that uses mathematical models to generate predictions on the stock market, generate profits for investors, and calculate and reduce the risk involved in investing. Lifecycle research is the study of target-date funds, which are retirement plans that allow the investor to set a specific date on which they want to retire. These funds allow for the diversification of the investor's portfolio in terms of their allocations of stocks, bonds, and cash. This fund also promotes a shift in allocations as the investor nears retirement, which in turn promotes security instead of growth (stocks to bonds). The 4% rule, instituted by William P. Bengen, is a very common rule for withdrawing in retirement. It encourages retirees to withdraw between 4% and 5% of their accumulated retirement funds annually when in retirement. Therefore, our goal is to use what we've learned about Lifecycle Research and Quantitative Finance to research optimal/sustainable retirement withdrawal rates. To do this, we will employ a Monte Carlo simulation coded in Python. Its function being to run many random samples to predict the trajectory of one’s retirement balance. In doing this, we took the “4% rule” into account since we are researching its sustainability. And we also recognized that many other factors must be considered when planning for retirement. So we took salary, asset allocation, and market behavior into account as well.