Monte Carlo

Once you create a base scenario, and show your client whether they're on track for their future goals, the next question is often: "What happens if things don't go according to plan?".

What if inflation is higher than expected? What if returns are lower than expected? What if your client experiences a very bad sequence of returns just as they retire?

A Monte Carlo simulation is a risk analysis tool that helps answer these questions by illustrating the likelihood that the client will meet their goals across a range of simulated market outcomes.

This analysis can help identify proactive changes that may improve plan resiliency today (e.g., keeping a defined benefit pension plan instead of taking the commuted value, adjusting asset allocations), as well as potential adjustments clients could make in the future if circumstances change (e.g., reducing spending, downsizing their home).

Here is a 13-minute video overview to see the feature in action.

A base scenario using fixed annual returns provides a strong foundation for planning discussions, tax analysis, and cash flow projections. However, it does not capture the uncertainty and range of outcomes clients may experience in the future. Monte Carlo analysis helps illustrate this range, allowing advisors and clients to better understand the resilience of a plan under different market conditions.

The Monte Carlo feature runs 1,001 possible sequences of returns and inflation rates through your scenario to calculate how your client would fare in those different circumstances. These sequences can include higher inflation periods, poor returns at the beginning of the plan, poor returns right after retiring, and many more. Snap determines whether your client would run out of liquid resources (e.g., personal Financial Assets) during the projection length and provides a Success Probability. The Success Probability explains how often the client ends the projection with a positive Goal Balance (the remaining personal net liquid assets after tax).

In addition to showing the Success Probability, Snap provides the Goal Balance (the remaining personal net liquid assets after tax) at key percentiles to give a sense of how much the client's well-being would be impacted. These metrics create an excellent discussion tool to help clients better understand what may happen in the future.

In addition to the high level summary at the top of the modal, you have access to detailed charts that break out important metrics (e.g., Goal Balance, Financial Assets, Estate After Tax) by year and percentile.

The remainder of this article outlines how to use this tool to its full potential.

Once you've completed your base scenario, you can click Stress Testing just above the projection table in the centre of the Planning Page and then click Monte Carlo. Stress Testing is an optional paid add-on that provides access to three tools:

1. Monte Carlo - This tool creates 1,001 random sequences of inflation and return data and calculates the results of your projection for each individual sequence. It provides a Success Probability and distribution of key metrics. This is best used to help clients understand the range of potential future outcomes.
2. Randomized Scenario - This tool allows you to view any of the individual 1,001 random sequences that are also used in the Monte Carlo tool to better understand the sequences and how they impact the projection. You can apply any of the sequences to your projection to walk the client through the actual outcomes (e.g., showing annual returns, account balances, deposits and withdrawals).
3. Historical Scenario - This tool is separate from the Randomized Scenario and Monte Carlo tools. It allows you to apply actual historical sequences that begin anytime after 1965. This can help clients understand how their plan would have fared during previous market conditions (e.g., during high inflation in the 1970s and early 1980s, or during the tech market selloff in 2000).

If your Planning Page has a lower resolution, or your window is smaller, the buttons will be displayed as icons. Click the button with the Stress Testing symbol in the same location and then click Monte Carlo.

Once you access the Monte Carlo modal, you can click Calculate in the bottom left corner to begin the process of generating the randomized sequences and calculating your scenario results.

The modal will then begin to display the results as the tool works through all 1,001 sequences. You can see how many have been calculated in the bottom left corner.

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Once all sequences have been created and applied to your projection, you'll see a summary of the results. The top section of the modal includes the Success Probability for the final year of the projection. This value is the percentage of the 1,001 scenarios that have a Goal Balance that is greater than or equal to $0 in the final year.

It also includes the Median, Conservative, and Pessimistic Goal Balances in the final year of the projection.

• The Median (P50) Goal Balance is the surplus or shortfall balance in the 50th percentile scenario (i.e., 50% of scenarios are better than this Goal Balance and 50% are worse).
• The Conservative (P25) Goal Balance is the surplus or shortfall in the 25th percentile scenario (i.e., 75% of scenarios are better than this Goal Balance and 25% are worse).
• The Pessimistic (P5) Goal Balance is the surplus or shortfall in the 5th percentile scenario (i.e., 95% of scenarios are better than this Goal Balance and 5% are worse).

There are also charts showing different metrics throughout the length of the projection. Each metric and chart is discussed in more detail below. The charts include:

• Success Probability
• Goal Balance
• Financial Assets
• Estate After Tax
• Shortfall Probability

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The Success Probability chart displays the percentage of scenarios that finish each year with a Goal Balance greater than or equal to $0. The Goal Balance is the client's Financial Assets, less any negative Cash Balance, less taxes payable on their Financial Assets. This represents the client's liquid personal resources available to fund spending going forward.

You can hover over any year of the chart to view the Year, Age, and Goal Balance at the Median (P50), Conservative (P25) and Pessimistic (P5) level.

In rare cases, a client may have a Success Probability that is lower in early projection years than later years. This can occur if the client retires early, has a mortgage or other debt going into retirement, or is expecting to receive an inheritance or downsize their home in the future. This represents cash flow challenges early in the plan that may resolve later through changes to consumption needs or other lump sum cash inflows.

While the Success Probability is very helpful for understanding the client's future outcomes, it's also important to consider other metrics in the modal (e.g., Estate After Tax). For instance, the client may still have significant non-liquid, or non-personal resources in the plan (e.g., Real Assets, Corporations). To increase their Success Probability, you could distribute more from their Corporation, or sell Real Assets.

It's also important to review the Goal Balance chart as this explains the magnitude of the surpluses and shortfalls. For instance, a plan may have an 80% Success Probability, but the Goal Balance in the 20% of shortfall scenarios may only be -$20,000. This is much more manageable for a client to handle than a 90% Success Probability where the 10% of shortfall scenarios are -$1,000,000.

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The Goal Balance chart displays the client's Financial Assets, less any negative Cash Balance, less taxes payable on those Financial Assets. This represents the client's liquid personal resources available to fund spending going forward.

The Goal Balance chart displays lines for the Pessimistic (P5), Conservative (P25), Median (P50), Favourable (P75), and Optimistic (P95) levels. You can also see the values for the Worst (P0) and Best (P100) scenarios by hovering your mouse over the chart in any year. The Worst and Best scenarios are excluded from the chart itself to avoid skewing the y-axis and to prevent overemphasizing those unlikely outcomes.

The Goal Balance is an important addition to the Success Probability for understanding the variability in future outcomes. Two plans could have the same Success Probability (e.g., 85%), but one may have a range of Goal Balances between -$5,000,000 and $20,000,000, while the other could have a range between -$200,000 and $2,000,000. The second scenario is much more predictable, which many clients may prefer.

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The Financial Assets chart doesn't include any adjustments made in Goal Balance. It simply includes the gross Financial Assets held personally in the projection for each year. This can help with portfolio discussions to so that your clients understand expected balances over time and when the balances could reach $0.

The Financial Assets chart displays lines for the Pessimistic (P5), Conservative (P25), Median (P50), Favourable (P75), and Optimistic (P95) levels. You can also see the values for the Worst (P0) and Best (P100) scenarios by hovering your mouse over the chart in any year. The Worst and Best scenarios are excluded from the chart itself to avoid skewing the y-axis and to prevent overemphasizing those unlikely outcomes.

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The Estate After Tax chart factors in everything in the projection (e.g., Financial Assets, Real Assets, Corporations, Insurance, Debt, Tax on Estate). This is helpful if the client wants to know what would be left for their beneficiaries under the different outcomes. If the client has a specific estate goal (e.g., $500,000) you can see which percentiles are expected to fall above or below that value to estimate their likelihood of achieving their estate goal.

The Estate After Tax chart displays lines for the Pessimistic (P5), Conservative (P25), Median (P50), Favourable (P75), and Optimistic (P95) levels. You can also see the values for the Worst (P0) and Best (P100) scenarios by hovering your mouse over the chart in any year. The Worst and Best scenarios are excluded from the chart itself to avoid skewing the y-axis and to prevent overemphasizing those unlikely outcomes.

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The Shortfall Probability chart shows the percentage of scenarios that have a negative Cash Balance in that year. Negative Cash Balances are indicated with pink shading on the Planning Page.

Since the projections are calculated behind the scenes, we wanted to maintain the transparency that the pink shading brings to understanding a projection.

A negative Cash Balance means that the client has had to borrow within the projection for some reason. This could be due to an override on a Financial Asset that is preventing Snap from withdrawing or an annual withdrawal limit on a locked-in account. Alternatively, it could be due to the plan running out of Financial Assets and represent one of the scenarios where the client isn't expected to succeed.

If you see years with Shortfall Probability where the Success Probability is still high, it means that the client is still on track, but that the plan would require temporary borrowing. You may want to review the original scenario or Apply & Run the Worst performing scenario from the Randomized Scenario model to see what's causing the shortfalls. This process is outlined in more detail in the next section.

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The Monte Carlo feature shares the same 1,001 scenarios as the Randomized Scenario feature. This means that once you've finished the Monte Carlo analysis, you can click Randomized Scenario and explore any of the individual scenarios in more detail.

If your client has a question about why the 5th percentile Goal Balance is so low, you can go to Randomized Scenario, click the P5 button, click Update, and view the sequence for that scenario.

Then, if you'd like to view the scenario with the rates applied you can click Apply & Run to update the projection.

Applying a Randomized Scenario allows you to move from a high level summary of potential future outcomes in the Monte Carlo modal, to diving into the granular year to year return and withdrawal assumptions that would cause each scenario to occur.

Controlling the assumptions

You also have the ability to control the assumptions used in the Monte Carlo analysis from the Randomized Scenario modal. Click Show fine print in the top-right corner of Randomized Scenario.

A new section will appear under the chart that allows you to see the Actual return assumptions in the selected sequence. You can also click show Expected to review and edit the assumptions for Randomized Scenario and Monte Carlo. You can update the Expected Average Rate and Expected Standard Deviation for Inflation, Cash, Fixed Income, and Equity.

Once you change the Expected values and click Randomize Again at the bottom of the modal, your Randomized Scenarios will be recalculated and any existing Monte Carlo analysis will be cleared. You'll need to click Monte Carlo and then Calculate to use the new assumptions.

If you'd like to generate a new set of 1,001 scenarios, you can click Randomize Again at the bottom of Randomized Scenario modal. This will temporarily clear any existing Monte Carlo analysis, allowing you to recalculate Monte Carlo using the new sequences. If you Apply & Run any of the new sequences to your projection, any Monte Carlo from your previous rate sequence will be permanently cleared and you'll need to recalculate.

When you access the Randomized Scenario modal without first running a Monte Carlo analysis, the sequences are ordered from Worst to Best based on the Average Annual Real Rate of Return for the sequence. Since we don't yet know how the sequences impact the actual projection (this is done by Monte Carlo), we need to use the Average Annual Real Rate of Return for each sequence as a proxy for how good or bad they are.

Once you calculate Monte Carlo, when you access the Randomized Scenario modal, the sequences are ordered from Worst to Best based on the Goal Balance in the projection. This is the actual result of each plan from Worst to Best for the client's actual goals and outcome.

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You can toggle between Real Dollars and Nominal Dollars to adjust the values displayed in the Monte Carlo charts and tables. Nominal Dollars is the default, which displays actual future dollar values and aligns with most values elsewhere in Snap. Toggling to Real Dollars uses the randomly generated Inflation Rate for each scenario to discount the future values back to the current year for a more comparable metric.

It will also determine how the scenarios are ordered in the Randomized Scenario tool. For instance, if you select Nominal Dollars in Monte Carlo, then the scenarios will be ranked from Worst to Best based on the Nominal Goal Balance within the Randomized Scenario modal. This allows you to locate specific scenarios to review the sequence and apply to the projection if desired .

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1. How can Monte Carlo help my clients?

One desired outcome of financial planning is to help maximize the likelihood that your clients achieve their goals. Monte Carlo analysis can help understand how a client's projection may fall off track and the degree of risk that's present.

This can help determine if a client should make changes to their plan today. For instance, they may want to change their asset allocation, adjust their government benefit start age, or make decisions about whether to commute a pension. Monte Carlo analysis can help compare decisions across a broader range of potential future outcomes.

It also helps the client understand what options are available to implement in the future if required. For instance, reducing spending by 10% starting in 10 years may be enough to address most of the downside risk in the projection. This change would only be required if things go worse than expected over the next decade.

Having this understanding ahead of time provides clients with more peace of mind. They're also less likely to have time sensitive questions and needs during market sell offs, since they already expect declines and are aware of the options available when they occur.

2. What is an acceptable Success Probability?

The optimal Success Probability will depend on your client's risk tolerance, the magnitude of the downside risk, and the flexibility of their goals and circumstances.

1. Risk tolerance - A client who is very risk averse may want a 90% Success Probability to sleep well at night knowing there's a limited chance of downside outcomes. A client who's more tolerant of risk may be comfortable with a 75% Success Probability.
2. Downside risk - A Success Probability of 50% or even lower could be acceptable to a client if the shortfalls (negative Goal Balances) are manageable. For instance, if a client has Real Assets or Corporations that can cover the shortfalls if required, they may be comfortable knowing that they can sell other assets as needed.
3. Flexibility - A client with $80K of target spending may be comfortable with a Success Probability of 50% (or even lower) if $40K of their spending is discretionary (e.g., travel, hobbies, donations). If they're willing and able to cut back on their spending as required in the future, then reviewing the plan on an ongoing basis and adjusting as needed can be a great way to minimize the chance of underspending throughout retirement. However, another client with $80K spending may be looking for an 85% Success Probability if they have more mandatory expenses (e.g., mortgage, car payments). This also applies to a client's flexibility for their Estate After Tax. A client with a high priority estate goal (e.g., leaving $500,000 to each of their three children) may want a higher Success Probability than a client with more flexibility in their estate goal. If there's flexibility to dip into the estate by borrowing against Real Assets or an Insurance policy, this leaves an additional buffer.

In general, a target between 70% and 90% tends to make sense for most client conversations. You can then adjust this based on the above three factors.

The most important thing to remember with the Success Probability is that the intention isn't to calculate the number once and walk away. Monte Carlo is designed to demonstrate the importance of ongoing reviews and planning, since we don't know what the future will bring. As a result, moving forward with a 50% Success Probability plan today doesn't automatically mean the client has a 50% chance of running out of money in the future. If you work with them on an ongoing basis they can continue to adjust their spending and other decisions as new information is learned.

3. How can I include the Monte Carlo Analysis in the Client Report?

For the first release of Monte Carlo we haven't yet added a page to the Client Report. We'll be working on this shortly and are looking for feedback on any details that users feel are critical to include for their discussions. If you'd like to see Monte Carlo analysis available as a page in the Client Report, please reach out to our support team by email at [email protected] or by phone at 1-888-758-7977 ext 1.

For the time being, the best options to share the Monte Carlo analysis with your clients area:

a. Present the modal live with your client.

b. Export individual Charts from the modal.

c. Take screenshots of the modal

c. Right click on the modal and then select Print. You can save this as a PDF and share it with your client. You may need to use More settings to customize the Scale to fit your desired sections.

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a. Ensure you don't have a Historical Scenario sequence applied

If you've already applied a Historical Scenario sequence to your projection, you won't be able to access the Monte Carlo or Randomized Scenario features.

To gain access to Monte Carlo and Randomized Scenario, you'll need to click Clear & Run to remove the Historical Scenario sequence from your projection. You can do this from the bottom-right corner of the Historical Scenario modal or from the Scenario Setup -> Financial Assets page.

b. Distribute corporate investments that are considered available for spending

If you have a Corporation in your projection, you may want to copy your base scenario and distribute the full investment balance through Dividends before calculating Monte Carlo. This is because the Goal Balance definition in Snap doesn't include balances remaining in Corporations or Real Assets. As a result, the Success Probability could be artificially low in your base scenario if there is cash available in the Corporation that Snap can't access for spending.

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