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    Back to Simulations

    Monte Carlo Simulation

    Simulate thousands of possible portfolio outcomes using Geometric Brownian Motion to understand risk and return distributions.

    Parameters

    Configure your simulation

    8%
    15%
    10 years
    1,000

    Ready to Simulate

    Configure your parameters and click "Run Simulation" to generate thousands of possible portfolio outcomes.

    Understanding Monte Carlo Simulation

    What is Monte Carlo Simulation?

    Monte Carlo simulation is a computational technique that uses repeated random sampling to model the probability of different outcomes. In portfolio management, it helps estimate the range of possible returns and assess risk.

    Geometric Brownian Motion

    This simulation uses GBM, which models asset prices with continuous compounding, drift (expected return), and random shocks scaled by volatility. The formula is: dS = μSdt + σSdW

    Value at Risk (VaR)

    VaR 95% represents the maximum expected loss with 95% confidence. It's calculated as the difference between your initial investment and the 5th percentile outcome.

    CFA Relevance

    Monte Carlo methods are covered in CFA Level II (Quantitative Methods) and Level III (Portfolio Management). Understanding simulation is crucial for risk management and portfolio construction.