Asset Allocation & Rebalancing

How This Tool Works

Operation: The Asset Allocation Simulator models portfolio growth based on a user-defined mix of asset classes. Users specify the percentage allocation to equities, bonds, gold, real estate, cash, and other assets, along with expected annual returns and volatility for each. The simulation uses a simplified compound growth model:

Portfolio Return = Σ(Allocation% × Expected Return%) / 100

Portfolio Risk (Std Dev) = √(Σ(Allocation² × Volatility² + 2 × ΣΣ(Allocation_i × Allocation_j × Volatility_i × Volatility_j × Correlation_ij)))

The tool runs a Monte Carlo-style projection with ~1000 iterations, varying annual returns within the expected volatility range using a normal distribution (Box-Muller transform). The output shows:

• Median portfolio value at the end of the investment horizon
• 5th and 95th percentile outcomes (best/worst case scenarios)
• Probability of reaching a target corpus
• Year-by-year growth chart showing the median, best, and worst trajectories

All computations are purely client-side JavaScript with no external data or network calls.

Key Benefits of Using the Asset Allocation Simulator

• Total financial privacy: Your portfolio allocations, investment amounts, and return assumptions are processed entirely in your browser. No financial strategy data is transmitted or stored — protecting your investment approach from being tracked or monetised.
• Monte Carlo simulation: Unlike simple linear projection calculators, the simulator runs 1000 randomised iterations that account for volatility. You see not just a single projected number, but a probability distribution of outcomes — a far more realistic picture of investment uncertainty.
• Correlation-aware modelling: The simulator accounts for correlations between asset classes (e.g., bonds often rise when equities fall). This captures the diversification benefit, which simplistic 'add the numbers' calculators miss entirely.

Practical Real-World Use Cases

• Retirement planners modelling portfolio risk: A 45-year-old planning for retirement in 15 years can model a 60% equity / 30% bond / 10% gold portfolio, run the simulation, and see the range of possible outcomes — from optimistic to pessimistic — informing whether the asset mix is too aggressive or too conservative.
• Financial advisors designing client portfolios: An advisor can build model portfolios (aggressive: 80/20 equity/bond, moderate: 60/40, conservative: 30/70) and run the Monte Carlo simulation for each, presenting clients with probabilistic outcome ranges rather than single-point projections.
• DIY investors testing allocation strategies: A self-directed investor debating between 70:30 and 50:50 equity:debt allocations can simulate both scenarios and compare the 10th, 50th, and 90th percentile outcomes to decide which risk level aligns with their goals.

Frequently Asked Questions (FAQ)

Are the projections guaranteed?

No — all projections are based on historical return and volatility assumptions that you provide. Real markets deviate from historical patterns. The simulation shows the mathematical consequences of your assumptions, not a guarantee of future results.

How do I choose realistic expected return values?

As a broad guide: large-cap equity 10–12%, mid-cap equity 12–15%, bonds 6–8%, gold 6–9%, cash 3–5% (pre-tax, pre-inflation). For more precise figures, refer to long-term historical averages for your specific market (India, US, etc.).

Does this account for inflation?

Not directly — the inputs are nominal (pre-inflation) returns. To model real (inflation-adjusted) returns, reduce your expected return inputs by your assumed inflation rate (e.g., if expecting 12% equity returns and 5% inflation, input 7% as the real return).