This graph only shows 100 of the 20,000 scenarios considered.
5 Return % and ROI for each row vary with each run of the simulation.
IMPORTANT: The projections created by the Goal Simulator are hypothetical in nature. They do not reflect actual investment results and do not guarantee future results. An investor cannot invest directly in a Monte Carlo Simulation. The simulation is based on assumptions. There can be no assurance that the projections shown will be achieved. The chart only shows a range of possible scenarios. Actual results will vary and may be better or worse than demonstrated. The potential for gain (or loss) may be greater than that shown.
Monte Carlo Simulation
A Monte Carlo simulation models the probability of potential outcomes. It uses randomization to simulate uncertainty.
Material Assumptions Include:
The Assumed Inflation Rate, Average Annual Return and Maximum Drawdown (among other fields) are to be entered by the user, and Toews makes no representation as to the possibility or benefit of entering any particular value. However, individuals should consider whether the values they enter are reasonable considering all relevant factors.
The aforementioned assumptions and modeling assumptions below enable the Goal Simulator to randomly generate 20,000 scenarios showing the probability of success.
The Goal Simulator incorporates assumptions to generate potential outcomes. These potential outcomes are speculative in nature and should be considered approximations rather than as accurate predictions of future results.
The following variables which may be in this document can be manipulated and may not match those of the market at any given time: Assumed Inflation Rate, Average Annual Return and Maximum Drawdown. If these variables were modified, the performance could be completely different. Please note the variables selected and their values when reviewing the performance shown. In addition, the Goal Simulator assumes that the inflation rate and return rates are constant for the period indicated and may not be indicative of actual market behavior, in which market conditions may vary.
The Goal Simulator uses Maximum Drawdown as a proxy for standard deviation. We ran two studies, one of which found a correlation between maximum drawdown and standard deviation for Morningstar Categories US Fund Intermediate-Term Bond and US Fund Large Blend, where each unit of standard deviation corresponds to 3.01 units of max drawdown. The other study found a correlation where each unit of standard deviation corresponds to 2.92 units of max drawdown for the following 10 Morningstar categories--US Fund High Yield Bond, US Fund Intermediate-Term Bond, US Fund Large Blend, US Fund Large Growth, US Fund Large Value, US Fund Mid-Cap Blend, US Fund Mid-Cap Growth, US Fund Mid-Cap Value, US Fund Small Growth, and US Fund World Large Stock. Only the specified Morningstar categories were considered in determining the methods to use in the Monte Carlo simulation; therefore, actual results may have been different if a broader range of categories had been considered.
The Goal Simulator employs a multiplier of 3 since it is between the values found in each of our studies and corresponds with the Empirical Rule.
According to the Empirical Rule (a statistical rule), assuming that data follows a normal distribution, 99.7% of observations should fall within three standards deviations of the mean. Although standard deviation and maximum drawdown may be correlated when the mean returns are similar, the same may not be true otherwise. Equity and fixed income may have different mean returns. Therefore, the correlation of maximum drawdown and standard deviation may be more accurate by individual asset class rather than as a blend.
Correlation measures the relatedness between two or more variables and may not be indicative of a causal relationship.
The Goal Simulator does not consider asset class in the generation of possible successful scenarios. If it did, other outcomes may have resulted.
The simulation does not consider the following, which may cause results to differ: tax implications, early withdrawal penalties, or active management costs, fees and other expenses.
The Goal Simulator defines "success" as achieving the user's End Goal at the end of the Expected Retirement Duration. The Annual Retirement Income Needed is selected by the user and is withdrawn at the end of the year, starting at the Retirement Age. The amount withdrawn is adjusted to account for the Assumed Inflation Rate. If both Investor and Spouse are entered, Income Needed in Retirement starts at the earlier of the two retirement ages.
Social Security payments begin at the entered Retirement Age, but the inception may not begin before the age of 62 or after 70. A simplified Social Security analysis has been used, restricting Social Security revenue to the individual and does not allow it to transfer to a spouse or other individual.
The Goal Simulator utilizes an implementation of the Marsaglia polar method to generate random numbers in a normal distribution for the Monte Carlo Analysis. The Average Annual Return is used as the target mean of the distribution. The target standard deviation is derived from the Maximum Drawdown as previously described in Material Limitations.
The same Average Annual Return is applied to each Investment.
Other Goals are applied in the year entered even if the Investment would have been spent over a number of years.
The simulation always starts from the current year and runs until both Investor and Spouse (if applicable) have reached the end of their retirement (shown as Retirement Age + Retirement Duration) and doesn't exclude impossible scenarios such as having a negative age.
Social Security, Retirement and End Goal are valued in current dollars.
The Goal Simulator is used herein to educate and communicate about future uncertainty. Individuals should consult a financial professional for individualized advice tailored to their specific situations.