Understanding the Types of Retirement Projections
Financial Planning has a number of different tools available to provide analysis at different levels. In addition to the assumptions that are used within a plan, the method used to project your retirement income and expenses will heavily influence how outcomes are evaluated.
There are three main types of retirement projections out there:
Flat Average Projections
Flat average projections use fixed assumptions for life expectancy, return rates, and inflation, applying them consistently throughout the retirement period. While this approach is straightforward, it does not account for variability in market returns or life events.
For instance, if you assume a flat 5% return each year, your projections will show a smooth, predictable line of growth. However, in reality, markets can experience years of both gains and losses. Flat averages are useful for a basic understanding of your retirement plan but may miss the risks and variability inherent in real-life financial markets.
Historic Simulation
Historic simulation models use historical data to estimate how different portfolios would have performed under various market conditions. This approach attempts to offer more realistic projections by accounting for actual past market behavior. For example, a simulation may apply returns from the 2008 financial crisis, allowing you to see how your portfolio might fare under a severe downturn.
While historic simulations can be more realistic than flat average projections, they also rely on the assumption that past performance is indicative of future results. While useful, this method does not account for unprecedented future events or shifts in market dynamics.
Monte Carlo Simulations
Monte Carlo simulations are often considered the gold standard of retirement projections. This method runs thousands of hypothetical scenarios, each varying the rates of return, life expectancy, and inflation, to assess the probability of success for a given strategy. Rather than assuming a steady return, Monte Carlo simulates a range of outcomes based on possible market conditions and life events.
This allows you to see not only the average outcome but also the best- and worst-case scenarios. For example, it may show that your portfolio has an 85% chance of lasting throughout your lifetime with your current withdrawal rate. Monte Carlo simulations provide a comprehensive view of risk and can help you adjust your strategy for a higher probability of success.
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