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Portfolio Monte Carlo Lab

Run seeded scenario simulations using editable return, volatility, contribution and withdrawal assumptions.

Methodology visibleStress-tested inputsNo buy/sell recommendation

Simulation assumptions

How to use this Portfolio Monte Carlo Lab

Monte Carlo analysis answers a different question from a deterministic calculator. Instead of showing one compound return path, it generates many paths from a stated return-and-volatility model and summarizes the distribution of ending corpus values. The Finin2min implementation is seeded for reproducibility: the same assumptions and seed generate the same diagnostic output.

1. Enter factsReplace sample values with your portfolio, goal or market data.
2. Check assumptionsReturn, inflation, tax, cost and stress inputs remain visible.
3. Read the stress caseDo not rely on the base result alone when downside scenarios are available.

Calculation logic

The rigorous engine uses monthly lognormal return draws derived from the entered annual mean and volatility assumptions. A lognormal gross-return process cannot generate a monthly loss below -100%. Contributions and withdrawals are applied monthly, and withdrawals can grow with inflation. The output reports corpus-survival frequency plus the 10th percentile, median and 90th percentile ending corpus across simulations.

Worked interpretation

A 70% simulated success rate means 70% of the generated paths under the chosen model finish above zero. It does not mean the investor has a 70% real-world chance of success. Changing volatility while holding average return constant can materially change downside percentiles, which is exactly why a distribution view is useful.

What this result does not prove

Simulation probability is model probability, not real-world certainty. Market returns are not guaranteed to be lognormal, independent or stationary; correlations, valuation regimes, fees, taxes and asset-allocation changes can matter. The tool must therefore display assumptions next to the result and should not translate a simulated success rate into a suitability recommendation.

Integrity rule: a calculation can be mathematically correct and still be decision-inappropriate if the inputs, source date or model assumptions are wrong. Finin2min therefore keeps model assumptions visible and avoids converting the result into a security recommendation.

Methodology, data and limitations

This Finin2min tool separates calculation from recommendation. Inputs, return assumptions and stress parameters remain visible and editable. Results are educational scenarios, not forecasts or suitability advice.

Data integrity: do not silently ship stale market/fund data. When the page uses imported official data, retain source authority, effective date, retrieval timestamp, parser version and SHA-256 in the investment data manifest.

Primary / official references

Questions & answers

What does the Portfolio Monte Carlo Lab calculate?

Monte Carlo analysis answers a different question from a deterministic calculator. Instead of showing one compound return path, it generates many paths from a stated return-and-volatility model and summarizes the distribution of ending corpus values. The Finin2min implementation is seeded for reproducibility: the same assumptions and seed generate the same diagnostic output.

What assumptions drive the result?

The rigorous engine uses monthly lognormal return draws derived from the entered annual mean and volatility assumptions. A lognormal gross-return process cannot generate a monthly loss below -100%. Contributions and withdrawals are applied monthly, and withdrawals can grow with inflation. The output reports corpus-survival frequency plus the 10th percentile, median and 90th percentile ending corpus across simulations.

Can I treat the result as a forecast or recommendation?

No. The output is an educational scenario generated from the values entered. It does not predict market returns, recommend a security or establish suitability for an individual investor.

How should I handle market or mutual-fund data?

Use a current, complete dataset with a recorded effective date. Where the page requires imported scheme, NAV, TER, portfolio or industry data, Finin2min should publish or retain the source authority, retrieval date, parser version and file hash.

What are the main limitations?

Simulation probability is model probability, not real-world certainty. Market returns are not guaranteed to be lognormal, independent or stationary; correlations, valuation regimes, fees, taxes and asset-allocation changes can matter. The tool must therefore display assumptions next to the result and should not translate a simulated success rate into a suitability recommendation.

Financial information disclaimer: Investments involve risk. Calculations may omit taxes, costs, liquidity constraints, tracking difference, execution risk or individual circumstances unless explicitly entered. Verify current official documents before acting.

Guides that use this calculator

Background, worked examples and the rules behind these numbers.

Regulatory disclosure — SEBI

Finin2min is not registered with the Securities and Exchange Board of India (SEBI) as an Investment Adviser or as a Research Analyst. This tool performs an arithmetic calculation on the figures you enter and is published for general information and educational purposes only. It is not investment advice, it is not personalised to your financial circumstances, objectives or risk tolerance, and it is not a recommendation to buy, sell or hold any security, scheme or product. Projected values are illustrative and follow directly from the assumptions you supply; actual returns will differ, and past performance does not indicate future results. Consider consulting a SEBI-registered Investment Adviser before acting on any investment decision.