The simulation creates a powerful tool that gives an array of results for any statistical problem, with numerous inputs sampled over and over again, according to Investopedia. Here are their four main points: 

• The Monte Carlo Simulation uses a random sampling of information to solve a statistical problem. 

• Combined, the Monte Carlo Simulation enables a user to come up with a bevy of results for a statistical problem with numerous data points sampled repeatedly. 

• The Monte Carlo Simulation can be used for personal finance planning and portfolio management, as well as in corporate finance.  

• On the downside, the simulation is limited in that it can’t account for a bear market, recessions, or any other kind of financial crisis that might impact potential results.  

For example, using a simulation tool like the one from Portfolio Visualizer, a person wants to retire at age 65 and they have saved $2 million, half of it in an IRA and half after tax invested 60% in stocks and 40% in bonds. Having a projected life to age 91, this person would need $80,000 per year after tax (that’s in addition to social security benefits) to live how they want to, considering basic living needs, travel, leisure activities and time with family. By running the particulars of this person’s investments and needs, the Monte Carlo Simulation shows that this person only has a 67% chance of fulling their retirement goals. If they have a major medical event, their chances of fulfilling their goals would come down to about 50%.  

Besides the gloomy forecast, the results would give recommendations for reversing the situation or extending their investment longer into retirement. First, they could withdraw less from their investments and reduce their standard of living, even just $670 a month could get them closer to their goal. Secondly, if they don’t want to change their lifestyle, they could work part-time. A third recommendation would be to change the stock/bond investment from 60/40 to something riskier like 90/10. (While that person’s investment goals may be far from yours, there are some standard risks and benefits that work more generally.) Here are some pros and cons from the experts at Above the Law. 

PROS 

• Probabilistic Results — Monte Carlo Simulations show not only what could happen, but also how likely each outcome is. This can be super beneficial for arguing hypothetical situations. 

• Graphical Results — Monte Carlo Simulations are easily represented in a graphic way that shows the range of possible outcomes in a scenario. 

• Sensitivity and Scenario Analysis — Monte Carlo Simulations make it easy to examine what would happen under circumstances that vary slightly from reality. Questions can be asked, like, “What would happen if this person changed their investments?” Or, “What would happen if this person had a major medical event?” 

CONS 

• Distribution Assumptions — Monte Carlo Simulations are created around statistical distribution. If the correct distribution is used, the results are valid, but if the wrong one is used, the results are meaningless. 

• Input Assumptions — Monte Carlo Simulations are as good as the inputs they start with. Making generalizations about someone’s future health or how their stocks may fare can be more assumption than statistical fact. 

• Formal Assumptions — Monte Carlo Simulations are built around mathematical formulas that drive the end values. Some of the simulation software has formulas built in that give quicker results, but those results can be incorrect if not the correct formula for the situation.  

In the end, using a Monte Carlo Simulation can be part of your retirement planning, but certainly not the entirety of it. It’s never too early to start thinking about retirement, and never too late to take steps to better your situation. Stay positive and you’ll get there, ideally with money to spare!