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Simulation Mode

Monte Carlo Financial Simulator

Simulate Your Investment Journey

Our advanced Monte Carlo simulation tool helps you understand the potential outcomes of your investment strategy over time. By running thousands of simulations based on historical market performance, you can visualize the probability of achieving your financial goals.

Simulation Parameters

1 50 100

Investment Parameters

0% 25% 50%
-10% 10% 30%
0% 50% 100%
0% 5% 10%
Includes management fees, expense ratios, and advisory fees
0% 25% 50%
Returns will be adjusted to real (inflation-adjusted) returns. All results shown in today's purchasing power.

Trading Strategy Parameters

1% 50% 99%
0.1% 50% 100%
Average profit per winning trade as % of position size. Example: 10% means $100 profit on a $1,000 position
-100% -50% -0.1%
Average loss per losing trade as % of position size. Example: -5% means $50 loss on a $1,000 position
0.1% 50% 100%
Percentage of total account risked per trade. Professional recommendation: 1-2% per trade. Higher values dramatically increase risk of ruin.
0% 25% 50%
Balance will be adjusted for inflation erosion. All results shown in today's purchasing power.

Retirement Planning Parameters

18 59 100
0% 10% 20%
0% 25% 50%
-10% 10% 30%
0% 50% 100%
0% 5% 10%
Includes management fees, expense ratios, and advisory fees
0% 25% 50%
Returns will be adjusted to real (inflation-adjusted) returns. All results shown in today's purchasing power.

💰 Tax Configuration (Optional - Enhanced Accuracy)

Enable tax modeling for more accurate retirement projections. Works for all countries!

Model multiple accounts with different tax treatments and optimize withdrawal strategy

Market Return Distribution

The simulation uses a normal distribution to model market returns. Adjust the parameters to match your investment strategy.

What does this mean?

With your selected parameters, annual returns will be:

  • Between -18% and 30% about 68% of the time.
  • Between -30% and 42% about 95% of the time.

About Monte Carlo Simulations

A Monte Carlo simulation performs risk analysis by building models of possible results by substituting a range of values for any factor that has uncertainty. It then calculates results over and over, each time using a different set of random values from the probability functions.

Running simulation...

Simulation Results

Probability of Reaching Your Goal
73%

These show your portfolio value after years in different scenarios. In 10% of simulations, results were worse than Pessimistic. In 10% of simulations, results were better than Optimistic.

Pessimistic Outcome
$750,000
10th Percentile
Likely Outcome
$1,200,000
Median (50th Percentile)
Optimistic Outcome
$1,800,000
90th Percentile

Based on 10,000 simulations with the parameters you provided.

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Frequently Asked Questions

What is a Monte Carlo simulation?
A Monte Carlo simulation is a mathematical technique that generates random variables for modelling risk or uncertainty of a certain system. It runs multiple simulations with random quantities for uncertain variables and presents the results in a probability distribution, which helps in understanding the impact of risk and uncertainty.
How accurate is this simulation?
While Monte Carlo simulations are powerful tools for financial planning, they have limitations. The accuracy depends on the quality of inputs and assumptions. This simulation uses historical market patterns to predict future outcomes, but actual results may differ due to changes in market behavior, unexpected events, or structural economic shifts.
How should I interpret the results?
The simulation shows a range of possible outcomes with their probabilities. The percentiles represent the likelihood of achieving at least that amount. For example, a 90th percentile result means there's a 10% chance you'll achieve equal or better results. The probability score shows your chances of reaching your stated goal amount.
What does volatility mean?
Volatility (standard deviation) measures how much returns fluctuate around the average return. Higher volatility means more uncertainty - both more upside potential and more downside risk. Lower volatility means more consistent returns, but potentially lower overall growth.
How many simulations should I run?
For most purposes, 10,000 simulations provide a good balance between accuracy and performance. More simulations (20,000+) can provide slightly more precise results but take longer to calculate. For quick estimates, 1,000 simulations are usually sufficient.