Portfolio Simulator: Multi-Asset Monte Carlo
This is a sophisticated, browser-based financial modeling tool that lets you construct a multi-asset investment portfolio and run thousands of simulated future scenarios to understand potential outcomes, risks, and trade-offs.
What It Simulates
At its core, the tool runs a Monte Carlo simulation — generating up to 25,000 random future paths for your portfolio over a horizon of 1 to 30 years. Each path simulates monthly returns drawn from realistic statistical distributions: a standard normal, a fat-tailed Student-t, or a negatively skewed Student-t that better captures the asymmetric losses seen in real markets.
Building Your Portfolio
You can allocate capital across 15 asset classes, including US and international equities, emerging markets, government and corporate bonds, TIPS, high yield credit, gold, commodities, REITs, private equity, hedge funds, and cash. Weight sliders let you adjust allocations manually, or you can load preset portfolios like the classic 60/40, Ray Dalio’s All Weather, the Permanent Portfolio, a university endowment model, and several others.
Key Analytical Tabs
Assumptions lets you edit each asset’s expected return, volatility, inflation sensitivity, and factor betas directly in a table.
Correlations shows a full 15×15 editable correlation matrix. Critically, you can switch between four regime-dependent correlation sets — normal markets, crisis (where risky asset correlations surge toward 1), stagflation (where bonds and stocks fall together), and deflation — reflecting how diversification breaks down exactly when you need it most.
Scenarios stress-tests your portfolio against six historical events including the 2008 financial crisis, the 1970s stagflation, the Volcker rate shock, Covid’s 2020 crash, the dot-com bust, and the 2022 bond rout.
Simulation displays a fan chart of percentile bands, a terminal wealth histogram, and an annual return distribution with a normal overlay to visualize fat tails.
Risk Analytics produces a Q-Q plot comparing simulated returns to a theoretical normal distribution, VaR and CVaR across multiple confidence levels, rolling Sharpe ratios, and drawdown metrics including max drawdown and Calmar ratio.
Factor Decomposition breaks the portfolio’s risk into equity, duration, credit, and inflation exposures, showing marginal and component risk contributions per asset.
Leverage is a particularly deep module — it models the effect of borrowing to amplify returns, showing how Sharpe ratios, geometric growth rates, financing costs, and wipeout probabilities all shift as leverage increases, and where the Kelly-optimal leverage point sits.
Withdrawal simulates retirement drawdown scenarios, testing whether a given withdrawal rate survives over time and quantifying sequence-of-returns risk.