In our journey for Financial Independence and the goal to Retire Early (FIRE), one area of concern we have is what happens if we retire at or near the market peak? We have had many years of continuous investment growth and are at an all-time high for the stock markets. Our timing for Retire Early could be as soon as next year but will be in the next 2-3 years.
A detailed analysis of this sequence risk was discussed in the first part of the series. How can we model and plan for the Sequence Risk of poor market performance in the first ten years of retirement? In that analysis, we only looked at ten-year stock price appreciation and did not include dividend yields. How will adding in the dividend yield data to the analysis effect the results?
In our first part of the series we used the Shiller stock performance data, dating back to before 1918, to analyze the ten-year future return based on the market valuation using the Schiller CAPE (Cyclically Adjusted Price to Earnings) (1). Based on research by Shiller and others, there is a reasonable correlation between current market valuations and future market performance which can be useful for our retirement planning. Today the CAPE is above 32 (33.54 as of the writing of this article) so it is in historic high territory for stock valuations which suggest a high risk for lower future returns in the next ten years.
We took this information and created High, Medium, and Low risk profiles for our Monte Carlo simulation tool. This allows us to account for Sequence Risk, using lower expected returns based on the CAPE data for the initial ten years of retirement.
We won’t go into all the background data in this post, but you can read more details on the original analysis in that first article here.
In the original analysis, the model only included the S&P 500 stock price appreciation. How will the performance change when we add in divided yields.
Just a note this article has a lot of technical information provided and is based on analysis of historic data. There is no guarantee historic data will accurately represent future performance. Please review our DISCLAIMER AND POLICIES section on the website.
What About Those Dividends?
Dividends are easy to forget since they are returning historic lows, about ~2% annualized return. They do make an impact on overall performance of our investments. The original Shiller data set did include the annual dividends for the S&P 500.
We took the dividend data and calculated the ten-year annualized future yield for each period. This yield was added to the stock price appreciation values used in the prior analysis.
One caveat is we did not adjust for “real” values which remove inflation based on the CPI. In our simulation models we account for inflation independently for each year and did not want to remove inflation from the performance data. A future approach we may separate out the real growth and add back the simulated inflation for that period.
Below, we overlay the original scatter chart data with the new divided yield data. As expected, We see the yield increases the overall performance for all values of CAEP (inverse of CAPE) and most importantly also during the very high valuation periods (low CAEP values).
Sequence Risk Bands
The next graph shows our “Sequence Risk Bands” overlaid on the data set. We use these bands to estimate the amount of risk for High, Medium, and Low sequence risk periods. We can take the market performance data and apply it to our Monte Carlo simulator.
As shown in the scatter graph above the bands are:
- High Risk is at a midpoint of CAEP = 3% (+/- 1%).
- Medium Risk is at a midpoint of CAEP = 4% (+/- 1%).
- Low Risk is at a midpoint of CAEP = 5% (+/- 1%).
Since the long-term average is 6.0% CAEP (~16.5 CAPE from 1918-2008) above 6% would be considered nominal returns. In this case, we don’t need to consider Sequence Risk and we use the long-term market averages. The market performance data we can use in our simulation for the Sequence Risk is summarized in the chart below.
We added this table to our retirement simulation tool to allow adding the option to simulate sequence risk. Users may want to use other values, so we also added a user selected option for sequence risk but in most cases these ranges should be sufficient.
Let’s Update Our Retirement Simulation Tool!
As we mentioned in past articles, one reason we prefer having our tool in Excel and keeping it unlocked is to allow for adding features and updates as we learn.
Confirming the Baseline Model
This new sequence risk data set with divided yields is included in Version 10 of our Retirement Simulator tool. A Beta test version will be available in the near future once we finish some Alpha testing. Subscribe to our website to get an update when we release the latest version of our tools.
Our baseline success rate is from our article on dual life expectancy. We had a success rate of 98.3% with modeling a 55-year retirement. This is close to our real-life situation if we retire early next year.
We entered the baseline data into Version 10 of the Retirement Simulation Tool. Due to some significant updates we made to the tools, we wanted to reconfirm our baseline data.
Retirement Simulator Improvements
1) Updated the investment mix. We now allow the entry of Stock, Bond, and Cash % and derive the Mean and Standard Deviation based on historic market data.
2) Allow selection of investment history length from 10-90 years of data
3) Allow options for investment fees.
4) Updated the sequence risk data to include dividend yields
To be comparable with the prior analysis we used 50-year historic data with a 50/50 mix of stock and bonds. This gave approximately the same mean and standard deviation for market performance as used in the prior baseline.
We then set our options for the second spouse reduced life expectancy and added the sequence risk lookup. For the baseline we did not include the option for Sequence Risk. The simulation was run for 10,000 life times to estimate our probability for success.
Baseline Updated Results
We ran the simulation and had a success rate of 94.2%. This is slightly reduced from the prior model (98%). In the new simulation, we have slightly different investment performance and we added in investment fees of 0.25% to the investment performance calculations. This provides more realistic assumptions for the model.
Modelling the Sequence Risk
In the Option Page, we now add in the High Sequence risk. This reduces the expected return to 5.1% average with a 4.9% standard deviation. This aligns with the historic ten year future returns (with dividends) for high market valuations.
The rest of the options and input data were left the same. The simulation was run for 10,000 life times to estimate our probability for success.
Our success rate dropped from 94.2% to 80.6%. This is a big improvement over the 69.2% from the prior analyses without dividends. We still need to do a little work to get our success rate closer to 95% goal.
Review of Sequence Risk Results
For our personal situation, initial models looked great at a 4% withdrawal rate. This new data suggests for a longer retirement period with high sequence risk, 4% may not be high enough.
One interesting thing to note is even with high sequence risk, our savings has a ~ 97 % chance to last 30 years (80 years old). A 4% SWR holds up well for a 30-year retirement even with high sequence risks!
Doing a quick check, if we reduce our WR to 3.5% the model shows a 93.4% chance of success. So even with the potential for a very poor market return for the ten-year initial retirement period, a 3.5% WR looks to be good for a 55-year retirement. This supports what others have reported on SWR for longer retirement periods.
Our next analysis we will add in Social Security to the model. Since our 4% WR lasts at least 30 years, will Social Security provide enough of a “safety” net to get us to our full 55-year retirement plan?
Remember Don’t Panic! It’s Just A Model and Stay Flexible
As we discussed earlier, if you are in a similar situation, for now don’t panic. This is one more piece of data to use for our planning. We really don’t know for sure what the future has in store but can use this correlation to help manage our planning and reduce our risks.
If you are planning to retire soon with high market valuations, it would be wise to adjust the initial withdrawal rate to be below 4% or model the sequence risk historic returns as we did for our case.
As with all the models the real world may not cooperate, so stay flexible in your plans. We really can’t predict the future, but we can model scenarios and plan accordingly. Retirement planning is a marathon and not a sprint, and over time priorities and personal situations change so stay flexible. Don’t get stuck on specific number or date.
One thing the models don’t account for is we can be flexible, so don’t get too caught up in 100% probabilities especially if your retirement date is far in the future. Extending your retirement by one or two-years during a down market can make significant improvements in your future success.
If you are already retired, postpone the big vacation, take a few smaller road trips. Or consider Barista FIRE for a few years with a part time job or side hustle. The trade off is waiting for the “perfect” time vs. getting enjoy your retirement sooner. We think the trade off of a little more risk is worth the benefit of retiring earlier and will stay flexible. Mrs. FoF is already talking about Barista FIRE.
Get a Free Copy of the Retirement Simulator!
Our basic version (8.0) of the simulation tool can be found on our website. Version 10 update will be released very soon with the revised sequence risk calculations and many other new features. It is a major update to the tool. If you would like a copy of this just subscribe to our website and we will let you know when it is available.