What is a Monte Carlo simulation?

A Monte Carlo simulation helps investors by modelling potential investment outcomes.

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What is a Monte Carlo simulation?

A Monte Carlo simulation in investing is like rolling the dice on potential outcomes for your investments. 

Instead of relying on past performance or gut feelings, Monte Carlo simulations use computer algorithms to model and predict multiple potential outcomes based on a range of possible variables and scenarios.

Think of it as a "what if" game for your investments. What if the economy takes a dip? What if interest rates go up? Or what if there's a major market disruption? 

By modelling these possibilities, Monte Carlo simulations can help investors see the potential risks and rewards of different investment strategies and make more informed decisions.

In short, Monte Carlo simulation is a tool that uses math and computer modelling to help you understand the possible risks and returns of your investments.

How Monte Carlo simulations can help your analysis

Monte Carlo simulations are important for retail investors because they provide a more complete picture of potential outcomes for an investment. 

As a retail investor, you want to make wise choices about where to put your money. You want to know not just the average return on investment but also the possible risks and ranges of potential outcomes.

That's exactly what Monte Carlo simulations can provide. By modelling a wide range of possible scenarios, Monte Carlo simulations can help you understand the risks and rewards of different investment strategies. They can also help you see how changes in market conditions or other factors might affect your investments.

So instead of relying on past performance or gut feelings, Monte Carlo simulations give you a more comprehensive look at potential outcomes. They're a valuable tool for anyone looking to take control of their financial future and make the most of their hard-earned money.

How you can run your own simulations

Financial advisors and money managers often use this tool, but you can do it, too. You don't need any professional systems or expensive resources to run Monte Carlo simulations at home. There are actually a few simple and accessible tools that anyone can use. Here are a few options:

  • Online calculators: You can use many online calculators to run Monte Carlo simulations for your investments. These tools allow you to input information about your portfolio, including your investments and their current values, and model potential outcomes based on different scenarios.
  • Spreadsheets: If you're comfortable with spreadsheets, use a tool such as Microsoft Excel or Google Sheets to run your Monte Carlo simulations. There are templates and formulas available online that you can use to get started.
  • Personal finance software: If you use personal finance software to manage your investments, some programs may already have built-in Monte Carlo simulation tools you can use. Check to see if your software has this feature and, if so, how you can use it.

Keep in mind that while Monte Carlo simulations can be a valuable tool, they're not a guarantee of future results. It's always important to do your own research before making investment decisions. 

Your analysis tool belt should always hold several useful analytic approaches. Just one method will rarely be good enough, and that's the whole point of running a range of randomized simulations anyway.

Scenarios where this simulation can help

These simulations can help investors in many ways. For example, Monte Carlo simulations can be a valuable tool for retirement planning

By modelling possible outcomes for a retirement portfolio, investors can better understand the risks and rewards of different investment strategies and make better decisions about allocating their assets. A Monte Carlo simulation might help an investor see that investing more heavily in stocks could lead to higher returns over the long term but also higher volatility.

They can also be used to help investors diversify their portfolios. An investor can see how their portfolio might perform under various market conditions by modelling different scenarios. 

For example, a Monte Carlo simulation might show that investing in a mix of stocks, bonds, and real estate could lead to more stable long-term returns across a wide variety of market conditions, reducing the portfolio's overall risk.

You can also analyse any single stock with this versatile tool. Monte Carlo simulations let you consider the risks and opportunities for your chosen company in light of factors such as different interest and inflation rates, wider or tighter profit margins, and intense or lukewarm end-market demand. 

You'll gain a deeper understanding of the business model's sensitivity to these issues, and you should also gain an understanding of how likely the risks are to materialize. This knowledge will provide a sound basis for any decision you make, whether it's to buy, hold, or sell.

These are just a couple of examples, but the possibilities are endless. Whether you're planning for retirement, diversifying your portfolio, or just considering whether you should invest in a particular stock, Monte Carlo simulations can help you reach a more informed decision.

Frequently Asked Questions

The pros:

  • A Monte Carlo simulation is basically a turbo-charged form of scenario analysis. It can help you make better investment decisions by modelling the probability of different outcomes. For example, by performing a Monte Carlo analysis, you might discover that your portfolio is particularly exposed to rising interest rates. Knowing this might prompt you to diversify into investments with offsetting risk exposures.
  • Using a Monte Carlo simulation means you don't have to simply rely on gut instinct when choosing between potential investments. Instead, you can use a probabilistic model to gain an understanding of the most likely outcomes for different investments using a wide range of scenarios.
  • Monte Carlo simulations are also surprisingly accessible for everyday investors, meaning anyone can use them in their analysis. Online financial calculators, spreadsheet tools and personal finance software all offer the ability to run Monte Carlo simulations.

And the cons?

  • Unfortunately, even the best financial models can't predict the future with absolute certainty. Monte Carlo analysis is a great addition to your investment toolkit, but it should be combined with other analysis methods to form a holistic view of a potential investment.
  • The outputs of any financial model are only as good as its inputs. If you feed faulty assumptions into a Monte Carlo simulation, its predicted outcomes will be inaccurate.

The Monte Carlo method was first developed in the late 1940s by two nuclear scientists who had worked together on the Manhattan Project, America's top-secret effort to build an atomic bomb. 

Polish-American mathematician Stanislaw Ulam wanted to develop a predictive model to estimate how likely he was to win a game of Solitaire. He figured if he could build a big enough dataset – by playing many games of Solitaire -- he could develop a probability distribution to estimate his likelihood of winning any game.

His colleague, Hungarian-American mathematician and physicist John von Neumann, believed Stanislaw's new modelling technique could have applications in nuclear science. Using early computers to run simulations, the two scientists used the method to predict how neutrons would behave in a nuclear explosion. Their project, in light of its attempts to incorporate chance and randomness into statistical modelling, was given the code name 'Monte Carlo' -- after the popular gambling destination in Monaco.

Predicting the future is hard – even Nostradamus got it wrong most of the time, and he's meant to be the best at it! Monte Carlo simulation might be a more scientific approach to predicting the future than whatever Nostradamus was doing, but it still runs into many of the same issues.

A well-calibrated Monte Carlo simulation might give you accurate results based on the inputs provided, but the simple fact is that there are just too many variables to ever possibly include in a single model. Also, if you're wrong about some of your baseline assumptions, the model outputs may be unreliable.

All this is to say that while Monte Carlo simulation can be a fantastic method to help in your investment decision-making, it's not a perfect crystal ball. Therefore, it's best to use Monte Carlo simulation and other forms of analysis and research when making investment decisions.

This article contains general educational content only and does not take into account your personal financial situation. Before investing, your individual circumstances should be considered, and you may need to seek independent financial advice.

To the best of our knowledge, all information in this article is accurate as of time of posting. In our educational articles, a 'top share' is always defined by the largest market cap at the time of last update. On this page, neither the author nor The Motley Fool have chosen a 'top share' by personal opinion.

As always, remember that when investing, the value of your investment may rise or fall, and your capital is at risk.

The Motley Fool has a disclosure policy. This article contains general investment advice only (under AFSL 400691). Authorised by Scott Phillips.