Feb 28, 2023

The Problems With Monte Carlo: Why Simulations May Not Predict Your Success in Retirement

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  • The Problems With Monte Carlo: Why Simulations May Not Predict Your Success in Retirement

Monte Carlo simulations are commonly used to predict retirement success by modeling many possible outcomes of a retirement plan. One drawback to this method is that the simulations are not always reliable, since they are based on certain assumptions that may not hold true in the real world. Here are a few reasons why Monte Carlo simulations may not provide an accurate prediction of your retirement success:

Modeling assumptions:

Monte Carlo simulations rely on several assumptions, such as the rate of return, inflation, and longevity, to generate the model's projections. If these assumptions are incorrect, the simulation's results will be flawed. For example, if you overestimate your rate of return, the simulation will show a higher retirement income than what is possible in reality.

Limited data:

Monte Carlo simulations are generally based on historical data, but this data is limited and may not be accurately reflect future market conditions.

Human behavior:

Retirement success is based not just on financial projections but also on human behavior. Factors such as unexpected health issues, job loss, or spending habits can greatly impact your retirement success. Monte Carlo simulations cannot account for these variables as they are based on mathematical models, not human behavior.


Monte Carlo simulations are often viewed as the final word on retirement success. People may make important financial decisions based solely on the simulation's results, without considering other factors that may impact their retirement. This can lead to a false sense of security, which can result in a less successful retirement.


Monte Carlo simulations are based on randomness and are intended to model a range of possible outcomes. However, the reality is that retirement success is not solely based on random events. The stock market, for example, has been known to have periods of significant growth followed by long periods of low or negative returns, and vice versa.

Unknown factors:

There are many variables that can impact retirement success, such as inflation, market conditions, and personal circumstances, that Monte Carlo simulations may not account for. This can result in a less accurate prediction of retirement success.

Incomplete information:

Monte Carlo simulations can only provide an estimate of retirement success based on the information provided. If important information is omitted or incorrect, the simulation's results will be flawed. For example, if you do not accurately estimate your expenses, the simulation's results will not reflect your true cashflow in retirement.

Hidden agenda:

Monte Carlo simulators are often designed for the financial services industry by the financial services industry. This can make a Monte Carlo simulator appear as a simple diagnostic tool, but in actuality, it is also designed to help sell a specific type of fee-based portfolio product.


Monte Carlo simulations are a valuable tool in predicting retirement success, but they are not always reliable. The limitations of the model, the assumptions used, and the impact of human behavior can greatly impact the accuracy of the simulation's results. Rather than rely solely on these results to make important financial decisions, seek the advice of a trusted financial professional to consider all the factors that may impact your retirement success when making your financial decisions.


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