Run stochastic market simulations to test your retirement portfolio's survival. Model Sequence of Returns Risk and early retirement stock crashes.
Initial monthly withdrawal rate: ₹1,66,667 / month
Higher volatility represents higher equity allocation (higher returns dispersion).
Demonstrates "Sequence of Returns Risk" — a crash early in retirement is far more destructive than one later.
Probability of Success
Out of 500 randomized trials, your portfolio successfully survived the full withdrawal window in 338 trials!
Worst Trial Final Balance
₹0
Poor market sequences
Best Trial Final Balance
₹4,62,97,08,809
Prosperous bull markets
The Monte Carlo retirement simulator is a premium statistical modeling tool that runs 500 independent historical return trials to determine the exact probability of your portfolio surviving your retirement window.
Traditional calculators make a critical error: they assume a constant, steady rate of return (e.g., 10% every year). In the real world, stock markets are highly volatile. A portfolio can average 10% over three decades, but experience massive losses in years 1 and 2, which can drain your nest egg permanently. A Monte Carlo simulation models this random volatility to audit your statistical safety.
Sequence of Returns Risk is the risk that the order (sequence) of your investment returns is highly unfavorable early in your retirement phase.
If the stock market experiences a severe crash (e.g., -30%) in Year 1 or 2 of your retirement, you are forced to sell a large number of depreciated shares to fund your annual living expenses. This locks in permanent paper losses and severely shrinks your compounding engine.
Even if the market rebounds vigorously in Year 6, your remaining principal may be too small to recover, leading to early depletion. Our simulator features a Sequence Risk Crash Overlay that lets you force a -30% crash in Year 1 or Year 2 to demonstrate this phenomenon.
To run the simulation, the React engine executes 500 parallel trials. In each trial, the annual return for every year of the retirement horizon is generated randomly using the Box-Muller Transform to create a normal distribution of returns:
Yearly Return = Average Return + [ Z * Volatility ]
Where:
For each trial, the annual balance compounds as:
Balance (y) = [ Balance (y - 1) - Withdrawal (y) ] * (1 + Yearly Return / 100)
If the balance remains greater than ₹0 at the end of the retirement horizon, that trial is marked as a Success. The overall metric is returned:
Probability of Success (%) = [ Successful Trials / 500 ] * 100
In professional financial planning, a probability of success of 80% or higher is considered highly secure. If your success probability is between 50% and 80%, you should consider incorporating dynamic withdrawal guardrails. A success rate below 50% indicates a high risk of depletion, and you should consider increasing your starting corpus or reducing annual spending.
Higher volatility (e.g., a 100% equity portfolio with 20% standard deviation) increases the dispersion of your outcomes. While it gives you a chance of achieving massive wealth in lucky paths, it also increases the likelihood of early depletion in poor sequences, lowering your overall Monte Carlo success rate compared to a diversified, lower-volatility portfolio.