Retirement

Learn about Boldin's Monte Carlo simulation: What it is, why it matters, what is new

At Boldin, we are committed to helping you make informed, confident financial decisions. One of the key tools we use to support this goal is Monte Carlo Simulation– A powerful way to model financial uncertainty and stress test your retirement plan.

Boldin's Monte Carlo simulation has been recently updated to better reflect real-world uncertainty. This FAQ explains what changes, why we update them, and how they affect your plans.

What is a Monte Carlo simulation?

Monte Carlo simulation model Many possible future outcomes By doing thousands of trials and random monthly benefits. The goal is to understand Range and probability Over time, the results are different, which is an important goal of long-term financial planning.

After all, when planning, there is no way to predict what we know will happen. With Monte Carlo, you can evaluate a range of possible results.

How is Monte Carlo simulation different from linear simulation?

When projecting financial futures, you can use linear or Monte Carlo simulations.

  • Linear simulation According to the long-term average, there is a fixed return every year. They are simple, easy to follow, and are for setting expectations, but they do not reflect real-world variability.
  • Monte Carlo Simulation Bringing randomness into the return, modeling the actual uncertainty and displaying a series of results instead of a single path.

We recommend both: linear for clarity, while Monte Carlo is doing realism. Together, they provide a more complete picture of your financial plan.

What happened to Boldin's Monte Carlo simulation?

We did Three important updates For our Monte Carlo simulations, provide you with more accurate projections.

  1. Convert from using CAGR (CAGR) to AAGR (Arithmetic Average Growth Rate)
  2. Updated how the account moves together in simulation
  3. Completed our standard deviation assumption

Each change is described in more detail below.

How do these updates make your plan stronger?

Financial models evolve with better research, tools and data. These updates do not mean that the old methods are wrong, they represent improvements and more accurately reflect how the market behaves.

They also reflect our commitment to rooting your plan. As the financial landscape continues to evolve, we will continue to refine the model so you can make informed, wise decisions with more confidence.

What does Monte Carlo have to do with my chances of success in retirement scores?

your Opportunities for success in retirement The score is powered by Monte Carlo simulation. These simulations model thousands of possible futures based on factors such as spending, market earnings, and life expectancy to estimate the likelihood of success of your plan.

Instead of passing/failing ratings, treat your score as Possibility of adjustments required. For example, a score of 60% means that 6 of 6 of 10 simulation schemes are always on track, while in 4 of 10 you may need to make changes along the way.

This score can help you understand where your plans are today and how impactful it is on future uncertainty.

  • See this detailed article for further guidance on interpreting scores as part of an ongoing program.

Update 1: Prediction of AAGR instead of CAGR (intelligent basics)

Now, we are using AAGR (Arithmetic Mean), not CAGR (Geometric Mean) when running Monte Carlo predictions.

Why: To avoid fluctuations in double counts, ensure more realistic predictions.

Impact on plan results: Your retirement opportunity may increase your chances of success.

Why we make this change

Boldin's Monte Carlo simulation once relied on Compound Annual Growth Rate (CAGR) Model future returns. Although CAGR can be used to summarize long-term performance, it already includes Volatility resistance– Reduced growth caused by year-on-year fluctuations. When used in Monte Carlo simulations (volatility is also introduced), this means Volatility is counted twiceleading to overconservative predictions.

To improve accuracy, we used Arithmetic Average Growth Rate (AAGR)– Simple annual earnings average without compounding or built-in fluctuations. This allows the Monte Carlo engine to do the job: add realistic variability across thousands of simulated paths.

Why AAGR is better for Monte Carlo:

  • AAGR Give a clean starting point and then simulate the application volatility.
  • CAGR The volatility resistance has been baked, so adding more will distort the result.
  • This change avoids double counting and better reflects how the market behaves.

By using AAGR, Boldin's simulations provide a more transparent, realistic view of possible outcomes, thus helping you to be clearer and more confident.

Useful analogy

One of our team members recently underwent a backpacking trip. The first two days involved steep rocky terrain, with a slow speed of about 1.5 mph. On the third day, the trail leveled and the pace increased to about 4 mph.

If you look at the overall average speed (2 mph), you won't understand the reality of this trip. This average level is fluctuating.

  • CAGR Just like the overall average – it tells you the end result, but not the feeling of the journey.
  • AAGR Just like tracking your pace every day – it's best to capture variability.

If they plan their camping location at 2 mph, they will sleep in the wrong attractions every night.

This is the problem with using CAGR in simulations – it smooths out the risks you need to plan.


Update 2: Accounts return to move together now

Typically, the random rate of return for normal distribution is now 100% related, meaning that in each of the 1000 pathways, all accounts will rise or fall every month.

Why: To better reflect the real world situation, market movements often affect all accounts in the same direction each month.

Impact on plan results: Plans with many accounts may result in a decrease in chance of success, while plans with fewer accounts have little impact.

Why we make this change

To further improve projection accuracy, we have updated how to model an account declaration form in a simulation. This change ensures that your plan reflects how your portfolio generally performs in real markets, especially during periods of volatility, and helps avoid excessive smooth or optimistic results.

Previously, the simulations for each account were independent. This means your IRA can experience a bear market or boom in one year, while your Rose can experience another.

In the enhanced model, all accounts increase or decrease in the same month, and the rate of return and standard deviation determine the extent of increase and decrease in each account in the simulation.

This means that if your overturned IRA has a conservative asset allocation and your Roth IRA has an active allocation, it will increase and decrease at the same time, but the changes in the Roth IRA will be even greater.

This is how it works in Boldin Planner

Our model has not tracked individual asset classes (e.g. stocks and bonds) separately, but allows you to enter Single Mixed Return (e.g., 6%), resulting in Single standard deviation (for example, 11%) means your holdings in each account. In this setup, mixed risks and returns (i.e. mixed returns and related mixed standard deviations) have taken into account the lower volatility of the bond relative to the stock for projection or simulation.

How will this change the outcome of your plan?

The impact of this update depends on how many accounts you have in your plan:

  • If you have many accountsyou may see a slight decline in chances of retirement success. This is because previous models view each account as independent movement, which underestimates the overall portfolio risk.
  • If you have fewer accountsthis change may be small, as your plan is already capturing the more realistic situation of market behavior.

This update does not add new risks – it only reflects how your entire portfolio may move together in the real world.


Change 3: We perfected the standard deviation to provide more realistic assumptions of fluctuations

We have updated the standard deviation used in Monte Carlo simulations to better reflect current market research and improve the accuracy of forecasts.

Why this matters: This improvement is based on our recent Better price Update and ensure that each return assumption is paired with the most realistic volatility data available. Accurate standard deviation input is essential to generate simulations that closely reflect the actual performance of investment, especially in a long-term perspective.

Impact your plan results: Changes in standard deviation will change your Opportunities for success in retirement Fraction:

  • Higher standard deviation Meaning more potential fluctuations. As the downside risk increases, this can expand the range of simulation results and reduce your success score.
  • Lower standard deviation Reducing the scope of results may improve scores by reducing risk variability.

What is standard deviation?

The standard deviation is How much return on investment often differs From the average time over time. In the context of Monte Carlo simulations, it represents the potential ups and downs your portfolio may encounter in a given year.

In short, standard deviation is one of the key ways we model uncertainty. By refining these inputs, we help ensure that your plan reflects not only the expected growth, but also the range of realistic outcomes you may face when you retire.

How does the changes in our standard deviation affect the plan?

It depends on your assumed rate of return:

  • 0–3% return: The standard deviation has not changed
  • 4-7% return: Small standard deviation
  • 8–10%+return: The standard deviation is slightly reduced

therefore:

  • You may see a reduce If you use the medium return assumption, you have achieved success because of slightly higher volatility.
  • You may see a A slight increase If you choose a more aggressive return assumption, adjust the volatility downward.

These improvements are not meant to make your plan look better or worse, but are intended to make it more Honest and helpfulso you can develop a strategy for the ups and downs of the real world of financial markets.


Have your chances of success in retirement changed?

When you Opportunities for success in retirement Scores are just a tool in the planning toolbox, which is a powerful way to assess the flexibility of a plan. These changes help ensure that your scores reflect not only mathematics, but also the real uncertainty of life.

Log in to a Boldin Planner to assess your retirement success opportunities and other ways to measure future financial success.

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