🎲What is Monte Carlo Simulation?
Monte Carlo simulation is a mathematical technique that predicts possible outcomes in uncertain situations. It's like rolling dice thousands of times to analyze all possible scenarios.
💡 Simple Example
For the question "How much will my portfolio be worth in 20 years?", the simulation runs thousands of different market scenarios (bull markets, bear markets, normal times) to show you the range of possible outcomes and their probabilities.
🎯Why is it Important for Investing?
📈 Set Realistic Expectations
Instead of just looking at average returns like "7% annually", it shows you that actual results can range from -20% to +30%.
⚠️ Risk Management
You can know in advance the probability of achieving your goals even in worst-case scenarios, allowing you to create safer investment strategies.
🔍 Real-World Applications
- • Retirement Planning: "What's the probability I can retire at 65? 80% or 90%?"
- • Goal Achievement: "What are the odds of saving enough for a house down payment in 10 years?"
- • Portfolio Comparison: "Which is safer: conservative vs aggressive portfolio?"
⚙️How Does it Work?
Step 1: Set Variables 📊
Average Return
e.g., 7% annually
Volatility
e.g., 15% standard deviation
Time Period
e.g., 20 years
Step 2: Run Simulation 🎲
The computer creates thousands of different scenarios (usually 10,000 runs):
- • Scenario 1: Year 1: +15%, Year 2: -8%, Year 3: +12%...
- • Scenario 2: Year 1: -5%, Year 2: +20%, Year 3: +3%...
- • Scenario 3: Year 1: +8%, Year 2: +7%, Year 3: -15%...
- ... 10,000 different scenarios
Step 3: Analyze Results 📈
Example Results:
- • 90% probability: Final assets above $500,000
- • 50% probability: Final assets above $1,000,000
- • 10% probability: Final assets above $2,000,000
- • Worst case: $300,000 (bottom 5%)
🛠️Practical Investment Applications
🎯 Goal-Based Investment Planning
Set Goals
- • $100,000 for house down payment in 10 years
- • $500,000 for children's education in 20 years
- • $1,000,000 for retirement in 30 years
Simulation Results
- • Current strategy success rate: 75%
- • With $200/month more: 90%
- • With aggressive portfolio: 85%
⚖️ Portfolio Comparison
| Portfolio | Goal Success Rate | Worst Case | Average Result |
|---|---|---|---|
| Conservative (30% stocks) | 85% | $800,000 | $1.2M |
| Balanced (60% stocks) | 78% | $600,000 | $1.5M |
| Aggressive (90% stocks) | 72% | $400,000 | $2.1M |
⚠️Limitations and Considerations
🚨 Important Limitations
- • Based on historical data: Assumes future resembles past
- • Normal distribution assumption: Real markets are more complex
- • Black swan events: Excludes unpredictable extreme events
- • Changing correlations: Asset relationships change over time
💡 Best Practices
- • Use as guidance: Not absolute predictions
- • Regular updates: Recalculate as market conditions change
- • Multiple scenarios: Test under different assumptions
- • Professional consultation: Discuss complex situations with experts
🛠️Try it with GrowthVisual
🎯 Goal-Based Planning
Calculate the probability of achieving specific goals using Monte Carlo simulation.
Investment Calculator →⚔️ Portfolio Battle
Compare two portfolios using simulation and see which one wins more often.
Portfolio Battle →🎯Key Takeaways
Monte Carlo simulation is a powerful tool that quantifies investment uncertainty. While perfect prediction is impossible, it lets you experience various scenarios in advance.
✅ Great for
- • Long-term investment planning
- • Retirement fund planning
- • Portfolio comparison
- • Risk tolerance assessment
⚠️ Be Aware
- • Historical data limitations
- • Doesn't predict extreme events
- • Needs regular updates
- • Use as reference only
🎯 Expected Benefits
- • Realistic expectations
- • Better risk management
- • Increased investment confidence
- • Rational decision making
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