When I try to run the planner, I get a blank page, or an error about Java. How can I fix this?
The Flexible Retirement Planner is written in Java and requires your computer to have Java installed. You can get the latest version of Java by following the directions at this link.
In some cases, it may be necessary to uninstall and reinstall Java to get the planner to work correctly. This is particularly true if you get the errors “Could not find the main class: com.frp.application.FRPMain” or “The registry refers to a nonexistant Java Runtime Environment installation or the runtime is corrupted.”
Below are steps to uninstall and reinstall Java on Windows systems:
- Close all web browser windows
- Go to the windows start menu, then go to Control Panel\Programs\Programs and Features\uninstall a program.
- In the list of installed programs, click on the name column to sort the list of programs by name.
- Scroll down to the J’s. and then uninstall any versions of Java present on your system.
- Once everything is removed, follow the instructions at java.com to install the latest version of java.
For problems running the planner on a Mac, check out these tips.
Can I configure the retirement planner to work like conventional calculators for comparison purposes?
Yes. Just set the Investing Style to Custom, set the Investment Return manually, then set the Return– Std Dev to 0. Finally, set the Retirement Spending Policy to Stable. This will cause the simulation to behave more like a traditional retirement calculator.
Are the dollar amounts that I enter in the retirement planner adjusted for inflation automatically?
The short answer is yes. In general, all dollar values are shown in “today’s value” dollars. For example, suppose you have estimated that annual retirement expenses will be $50,000 per year when you retire (in today’s dollars). Even though you enter $50,000 into the planner for retirement expenses and the detailed output table shows the amount fixed at $50,000 each year, the actual amount of expenses funded each year will be higher due to inflation. Also, the ending portfolio balance is displayed in today’s dollars rather than in inflated future dollars.
One case where amounts are not automatically adjusted for inflation is with No COLA cash flow amounts that you can enter on the Additional Inputs window. The No COLA cash flow option lets you enter cash flows that are not adjusted for inflation. In this case the cash flow will lose purchasing power over time. For example, if you create a “Pension Income” entry of $50,000 and specify that it has no COLA, the planner will reduce the purchasing power of that payment by the inflation rate each year. Since all output amounts are shown in today’s value dollars, the income will appear on the Detailed View tab starting as a payment of $50,000. In each year following the first payment, the output will show the payment’s value (in today’s value) slowly decreasing by the inflation rate. Please refer to the Additional Inputs documentation page for more information about planner cash flows and COLAs.
I’ve run other planners and I get more favorable results with the same inputs. Why is my probability of success so low?
The answer of course depends on many factors, however, the most often overlooked factor is that the Flexible Retirement Planner models the entire retirement plan through both the accumulation and draw-down phases. Since risk tends to compound over longer periods of time, It is often more difficult to get a high-probability result than with a traditional planner. Another area that can cause different tools to produce different results are the assumptions used for portfolio returns and standard deviation. You can manually set these values to match those used by another planner for comparison purposes by setting the Investing Style to Custom.
In other planners and I get less favorable results with the same inputs. Why is my probability of success so high?
In addition to the factors mentioned in the previous answer, higher than expected results can be the result of applying the Flexible or Conservative Spending Policies. If switching the spending policy to Stable causes the results to be more like you expected, you might want to read through the section on this web site about Spending Policies.
In other retirement calculators, I only enter my portfolio’s expected return. What does the input Return – Std Dev do?
The Return – Std Dev input (standard deviation of return) is telling the simulator how much variation is expected in the portfolio’s annual return. While the portfolio may return 8% on average, the amount of variation in that 8% from year to year (and in particular the sequencing of annual returns) is a key factor in determining how successful your plan will be.
As an experiment, set Investing Style to Custom and choose a value for Return-Avg that you’ve used in other planners. Next, set the Return – Std Dev to zero and run the simulation. Note the results this produces, then increase Return – Std Dev by a percent or two and rerun the simulation. Do this a few times with slight increases to the standard deviation each time and notice how increased portfolio volatility (higher standard deviation) affects your plan. This exercise should demonstrate that risk matters. This is why a portfolio’s risk level or expected volatility, usually expressed as the standard deviation of returns, must be taken into account in financial planning.
Why does the stoplight show a yellow or red light when the Ending Balance of my plan is so high?
The stoplight will be green only when the performance of the plan is very strong. The ending portfolio balance that’s shown is the median ending balance taken over all the simulation runs. While on average (50% of the time) you may end with a high balance, successful retirement planning is usually based on much better odds for success, typically 90% or greater.
Why does the stoplight show a yellow or red light when the Probability of Success is greater than 90%?
Success is often difficult to define. The stoplight color is determined by two simulation outputs. The first is the Probability of Success, defined as the percent of simulation runs that didn’t run out of money. The second output that’s considered is the percentage of planned retirement spending that gets funded over the course of the plan. The logic behind this is that if you planned on having $75,000 per year, but only got $25,000 (so your nest-egg could be preserved), you won’t be happy with the result. The spending percentage threshold for a green light is 90% or greater. For more about how the spending percentage is determined, see the documentation page on Spending Policies.
Is it possible to adjust the spending levels to account for the fact that retirees often spend less later in retirement?
Sure. Just zero out Annual Retirement Spending on the main input section, and click the Additional Inputs button, and enter your retirement spending there. Instead of entering just one value for the whole retirement period, break it into 2 or three values, entering each one as a separate Other Expense cash flow with a given start and end year. Be sure that the start/end years don’t overlap and make sure you check the spending column in the Detailed Output tab after you run the simulation to be sure the planner did what you wanted it to.
If my portfolio doesn’t do well in the early years of retirement, I might go back to work, can the planner model that?
It can. Click on the Settings button next to the Additional Inputs button on the top right of the input panel. A window will pop up that has some settings for configuring “back to work” scenarios. You can learn more about this capability by reading about Spending Policies.
When I click the Settings button and increase Spending Policy – Minimum Percent of Expenses to Fund, the probability of success for my plan goes way down. Why did this happen?
This planner isn’t like most planners because it tries to be flexible and apply small spending cuts to save the portfolio when things aren’t looking so good. You can turn this off by setting Spending Policy to Stable and the planner will just withdraw the amount you asked for every year (adjusted for inflation).
With the Flexible Spending Policy selected, the planner tries to improve portfolio survivability by implementing small incremental spending reductions in years when the plan isn’t going so well. In the output, the “Percent Expenses Funded” value (tracked per year) gives you an idea of how much belt tightening the plan is imposing in order to get the probability of success that’s shown.
For example, if under a worst case scenario you’d be willing to cut back and spend only 50% of your target annual expenses (during the worst years), you could set the “Minimum Percent of Expenses to Fund” to 50% (in the settings window). Reducing the spending floor like this is likely to improve the odds of the plan being successful. Conversely, the default spending floor is 75%. If you think a 25% reduction in expenses would be too steep, you could bump that up to 80% or 85%, and see how much that lowers your probability of success. Usually the lower you set the floor, the higher your success rate will be.
One caveat on the use of a low floor is that the output shows the MEDIAN value (half of simulation runs had a higher value and half were lower). So just because the simulation doesn’t show any years where you hit the spending floor, you can be nearly certain that in some simulation trials the floor was hit, and that if that was real life you would have had to cut all the way back to the floor.
Finally, if you click the Show %of expenses funded check box, just below the graph, you can see the year-by-year effects of the spending policy overlaid on the graph.
What does the Spending Multiplier (in the Settings window) do?
In each simulation trial, the program decides year-to-year whether the amount the retiree gets to spend should stay the same, go down, or go up. The decision is based on whether the portfolio is bigger or smaller than it was at retirement start, and based on whether the portfolio went up or down in value since last year. The program implements this by adjusting the “percent of expenses to fund” variable. If things are going badly, the program doesn’t cut the percent of expenses all the way back to the floor right away. Instead, it starts withholding the yearly spending COLA (cost of living adjustment), which will require the retiree to cut spending in the next year by the inflation rate.
The multiplier magnifies this effect so that the spending gets cut (or increased) by multiples of inflation rate instead of just by the inflation rate. The result is that a multiplier greater than 1 speeds up the adjustment process and usually causes the floor of simulation to be hit more quickly. (Note that the multiplier is only relevant for the flexible and conservative spending policies).
The output from the planner shows that my median percent expenses funded stayed between 90% and 130%, yet I set the minimum for percent to spend to 75%. Why doesn’t the minimum go down to 75%?
The output report and graph shows the median value of the percent of expenses funded. This means you can’t see the handful of really bad trials where the simulation cut spending by 75% and still ran out of money. The likelihood that the median value will show 75% is related to the plan’s probability of success. Plans with a very low probability of success are more likely to show the median spending percent actually hitting the floor. Also, for more detailed data than just a range, make sure you click the Detailed Output tab and look at the year-by-year data (that’s the same data that gets graphed).
There’s no Y-axis label for % Expenses Funded on the graph. How can I tell what this means?
If you select that Show yearly inputs check box then click on the graph, the dashed red line will move to where you click, and the details to the right of the graph will update to show the data for the selected year. Doing this will allow you to see the value for % expenses funded. If you click-drag the red bar across the graph, the right hand data will update as you drag.
There’s no Y-axis label for the Show Failures line that appears on the graph. How can I tell what this means?
Over the course of the 10,000 simulation runs, when a trial runs out of money before the end of the plan (a failure), the year that the money ran out is recorded. At the end of the simulation, this data is tabulated to determine which years were most likely to be the ones where the money ran out. The graph shows the number of failures that happened in each year. The numbers used for this graph are shown in the last column of the table on the “Detailed View” tab (in parenthesis).
The “y scale” for the graph is arbitrary. The scale of the failures line runs from zero to the maximum number of failures in any one year, while typically represents a very small percentage of the 10,000 simulation paths. As an example, say the highest value for “failure count” occurred at age 88. Let’s say it had a value of 66. That means that out of the 10,000 simulation paths, there were 66 times that the plan ran out of money at age 88. In this example, the “failures line” in the graph will show its highest value of 66 at age 88.
Some retirement plans have high “infant mortality”, but if they get through the early years, things generally go well. Other times, the withdrawal rate is right on the edge and the more time that goes by, the more likely the plan will fail. This graph can be useful for evaluating these aspects of a plan. This graph can be particularly interesting when income or expenses change dramatically during retirement, like retiring early then starting social security a while later, or downsizing and selling real estate late in retirement.
To put this all in context, consider that a plan with a 95% probability of success, would have had a total of 10,000*.05 = 500 simulation paths that ran out of money.
The Flexible Retirement Planner says my plan is in pretty good shape. If I try to implement the plan in real life, how do I decide how much I should spend from year-to-year?
This planner is intended to roughly model the behavior that retirees are likely to exhibit in real life in order to produce a more accurate retirement plan. The general idea of the decision rule is that retirees should slowly adjust their spending in response to major swings in the value of their portfolio.
As an aside, a serious criticism and concern about tools like The Flexible Retirement Planner is that they instill an unwarranted confidence. Like any planning tool, Monte Carlo based retirement simulations are only as good as the inputs supplied, and unfortunately, it’s impossible for the inputs to be very reliable. There are many unknowns that conspire to reduce the accuracy of even the most well thought out plan. Some examples include unusually bad stock market performance, higher than expected inflation, unexpected healthcare or nursing care expenses.
So rather than viewing the output of the tool as a prediction of what will happen, it’s best to view it as support for making short term decisions about what to do over the next few years. Use the tool to guide these decisions, but revisit them often and reevaluate them in light of any new information you have.