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FuturePath calculates a personalized number that helps you monitor your progress toward meeting your retirement goals.


Estimating Approach

We use a Monte Carlo simulation that looks at 1,000 market scenarios to calculate how your retirement savings might grow. This information is used to calculate the estimated change in your assets and income over time. Below are the detailed assumptions behind this methodology.

Your withdrawal amount from investments is displayed in today's dollars for the current year and is assumed to increase by 3% each year throughout the retirement horizon. These amounts do not take any taxes into account that may be due upon withdrawal.


Social Security and Pension Benefits:


Any Social Security estimates are based on your current annual salary, current age, and stated age at retirement. The estimates are based on current law; the laws governing Social Security benefits and amounts are subject to change. The accuracy of the estimate depends on the pattern of your actual past and future earnings. The estimate may not be representative of your situation. Visit for more information.

FuturePath® estimates each person's Social Security benefits independently. When one spouse or planning partner predeceases another, FuturePath® assumes the surviving spouse/partner is eligible to receive the higher of the two estimated Social Security benefit amounts through the end of the couple's retirement horizon. If your planning partner is not your legal spouse, Federal law may preclude you from receiving Social Security benefits associated with the deceased partner's work history.

For pension benefits, FuturePath® allows you to assume that a portion of the pension benefit amount will be paid to a surviving spouse/partner. Federal/state laws may preclude a surviving spouse/partner from receiving pension benefits associated with the deceased spouse/partner's work history.


Monte Carlo Simulation:


Monte Carlo simulations model future uncertainty. In contrast to tools generating average outcomes, Monte Carlo analyses produce outcome ranges based on probability--thus incorporating future uncertainty.


Material Assumptions Include:


Underlying long-term rates of return for the asset classes are not directly based on historical returns. Rather, they represent assumptions that take into account, among other things, historical returns. They also include our estimates for reinvested dividends and capital gains.

These assumptions, as well as an assumed degree of fluctuation of returns around these long-term rates, are used to generate random monthly returns for each asset class over specified time periods.

The monthly returns are then used to generate 1,000 scenarios, representing a spectrum of possible return outcomes for the modeled asset classes. Analysis results are directly based on these scenarios.

Required minimum distributions (RMDs) are included. In the simulations, if the RMD is greater than the planned withdrawal, the excess amount is reinvested in a taxable account.


Material Limitations Include:


The analysis relies on return assumptions, combined with a return model that generates a wide range of possible return scenarios from these assumptions. Despite our best efforts, there is no certainty that the assumptions and the model will accurately predict asset class return ranges going forward. As a consequence, the results of the analysis should be viewed as approximations, and users should allow a margin for error and not place too much reliance on the apparent precision of the results. Users should also keep in mind that seemingly small changes in input parameters (the information the user provides to the tool, such as age or contribution amounts) may have a significant impact on results, and this (as well as mere passage of time) may lead to considerable variation in results for repeat users.

Extreme market movements may occur more often than in the model.

Some asset classes have relatively short histories. Actual long-term results for each asset class going forward may differ from our assumption--with those for classes with limited histories potentially diverging more.

Market crises can cause asset classes to perform similarly, lowering the accuracy of our projected return assumptions, and diminishing the benefits of diversification (that is, of using many different asset classes) in ways not captured by the analysis. As a result, returns actually experienced by the investor may be more volatile than projected in our analysis.

The model assumes no month-to-month correlations among asset class returns ("correlation" is a measure of the degree in which returns are related or dependent upon each other). It does not reflect the average duration of "bull" and "bear" markets, which can be longer than those in the modeled scenarios.

Inflation is assumed to be constant, so variations are not reflected in our calculations.



The analysis assumes a diversified portfolio which is rebalanced on a monthly basis. Not all asset classes are represented and other asset classes may be similar or superior to those used.

Taxes on withdrawals are not taken into account, nor are early withdrawal penalties.

The analysis models asset classes, not investment products. As a result, the actual experience of an investor in a given investment product (e.g., a mutual fund) may differ from the range of projections generated by the simulation, even if the broad asset allocation of the investment product is similar to the one being modeled. Possible reasons for divergence include, but are not limited to, active management by the manager of the investment product, or the costs, fees, and other expenses associated with the investment product. Active management for any particular investment product -- the selection of a portfolio of individual securities that differs from the broad asset classes modeled in this analysis -- can lead to the investment product having higher or lower returns than the range of projections in this analysis.


Modeling Assumptions


The primary asset classes used for this analysis are stocks, bonds, and short-term bonds. An effectively diversified portfolio theoretically involves all investable asset classes including stocks, bonds, real estate, foreign investments, commodities, precious metals, currencies, and others. Since it is unlikely that investors will own all of these assets, we selected the ones we believed to be the most appropriate for long-term investors.

Results of the analysis are driven primarily by the assumed long-term, compound rates of return of each asset class in the scenarios. Our corresponding assumptions, all presented in excess of inflation, are as follows: for stocks, 4.90%, for bonds, 2.23% and for short-term bonds, 1.38%.

Investment expenses in the form of an expense ratio are subtracted from the return assumption as follows: for stocks 0.70%, for bonds, 0.60% and for short-term bonds, 0.55%. These expenses represent what we believe to be a reasonable approximation of investing in these asset classes through a professionally managed mutual fund or other pooled investment product.


Asset Allocation and Withdrawals from Investments:


The asset allocation for the investments you've included in FuturePath® has either been selected by you, or for aggregated assets, is provided using the Morningstar classification of individual securities and holdings within mutual funds to categorize them as stocks, bonds, or short term investments. Any percentage of holdings classified by Morningstar as "other" has been assigned to stocks.

Your target asset allocation presents a suggested allocation based on your age, or the age of your spouse/partner if they are older. This target reflects a suggested allocation of investments that has the potential to help your portfolio keep pace with inflation while reducing market volatility. There is no assurance that the recommended asset allocation will either maximize returns or minimize risk or be the appropriate allocation in all circumstances for every investor with a particular time horizon.

Your withdrawal amount from investments is displayed in today's dollars for the current year and is assumed to increase by 3% each year throughout the retirement horizon. These amounts do not take any taxes into account that may be due upon withdrawal.

The modeled asset class scenarios described above and your projected withdrawals from investments may be calculated at, or result in, a Simulation Success Rate. Simulation Success Rate is a probability measure and represents the number of times our outcomes succeed (i.e. has at least $1 remaining in the portfolio at the end of retirement). This Simulation Success Rate is the primary component of the Confidence Number.


IMPORTANT: The projections or other information generated by FuturePath® regarding the likelihood of various investment outcomes are hypothetical in nature, do not reflect actual investment results, and are not guarantees of future results. The simulations are based on assumptions. There can be no assurance that the projected or simulated results will be achieved or sustained. The charts present only a range of possible outcomes. Actual results will vary with each use and over time, and such results may be better or worse than the simulated scenarios. Clients should be aware that the potential for loss (or gain) may be greater than demonstrated in the simulations.


The results are not predictions, but they should be viewed as reasonable estimates. Source: T. Rowe Price Associates, Inc.