Retirement Planning Guidelines: An Alternative to the Trinity Study
Recently I wrote about the famous Trinity Study for developing guidelines about sustainable withdrawal rates to avoid outliving your wealth. I wrote about their portfolio success rates concept. Their approach results in tables like this:
Today, I’d like to suggest an alternative table for prospective retirees to use instead. The alternative is Table 3 from my article, “Capital Market Expectations, Asset Allocation, and Safe Withdrawal Rates,” from the January 2012 Journal of Financial Planning. This table is based on the same data as the Trinity study table, but uses Monte Carlo simulations instead of historical simulations. The table looks like this:
* It uses Monte Carlo simulations which count each year of the historical data equally. It is not subject to the bias against bonds in the historical simulations resulting from an overweighting of the middle historical years. (For more on this, see the section “Bias against Bonds in Historical Simulations” here.)
* I think the information is more directly useful: it connects withdrawal rates to acceptable failure rates and shows the optimal asset allocation.
* The results fit better with real world expectations. Stock allocation recommendations tend to be lower than the 50-75% outcome in the Trinity study. The table also shows how a wide range of asset allocations work nearly as well as the optimal. This gives relief for retirees worried about high stock allocations.
* Since it is based on Monte Carlo simulations, the table can be easily customized to a change in capital market expectations. That is, the historical portfolio success rates in the Trinity study may not matter now that bond yields and dividend yields are so much lower than their historical averages. By modifying these return assumptions, users can get results that may better fit their own expectations about the future. For example, here is the same table, but with the real return expectations for each asset class being two percentage points lower than their historical averages: