Monte Carlo Key features include:
- Randomized Returns: The simulation generates random returns for each asset class using historical data and statistical methods, ensuring a realistic range of outcomes.
- Account-Level Precision: Each account’s unique asset allocation is preserved, and returns are calculated individually, allowing for precise modeling.
- Correlation Matrix: The simulation builds a correlation matrix and applies Cholesky decomposition to ensure returns across asset classes are realistically correlated, reflecting real-world diversification.
- Success Probability: The simulation determines plan success by checking if all expenses are covered in every year across all trials. The probability of success is calculated as the percentage of successful trials.
This method helps advisors and clients understand potential risks, stress-test strategies, and gain confidence in long-term financial outcomes.
Related resources: