How do I simulate a portfolio rebalance?

Open this page and use the live Retirement Planner tool below — set your inputs and the simulation runs instantly in your browser using real numerics. No install, no account needed.

Yes. The simulation runs free in your browser. A one-time unlock or a Pro plan adds advanced parameters, saved presets, data import, and clean exports.

Can I use my own numbers?

Absolutely — every input is adjustable, and with data import you can drive a portfolio rebalance from your own measurements.

Use case · powered by Retirement Planner

Retirement Planner for a portfolio rebalance

Simulate a portfolio rebalance live in your browser. This runs the real Retirement Planner solver — adjust the inputs, watch it respond instantly, and export the result. No install, no account.

For:Students Researchers Educators Engineers Hobbyists & Makers K-12 Students First Responders

Compound Interest

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Compound Interest & InvestingLive

the eighth wonder

Controls

Presets

Starting amount ($)

Monthly contribution ($)

Annual return

Years

Compounding means earning returns on your past returns, so growth accelerates over time. The gap between the balance line and your total contributions is pure compound interest — and it widens dramatically in the final years. Educational tool, not investment advice.

▶ Run in Python

Data Inspector

Final balance$691,150

Total contributed$190,000

Interest earned$501,150

Governing equation

A = 10, 000 (1 + \frac{0.070}{12})^{360} + 500 \cdot \frac{( 1 + \frac{0.070}{12} ) ^{360} - 1}{0.00583} = $691, 150

Reading this result: Rule of 72: at 7.0% a year, money roughly doubles every 10.3 years — about 2 doublings across your 30-year horizon. Each $500/mo contribution then earns returns on its own past returns, so the balance curve pulls away from your flat contribution line. Because compounding is exponential, most of the $501,150 in interest is created in the final years — time in the market matters far more than the amount. Educational tool, not investment advice.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

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Monte Carlo

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Monte Carlo Price SimulationLive

geometric Brownian motion

Controls

Presets

Initial price S₀

Expected return μ

Volatility σ

Horizon (years)

Geometric Brownian motion models a price with constant drift and random volatility — the assumption behind Black-Scholes. Running hundreds of simulated paths reveals the full distribution of outcomes, not just an average. Educational tool, not investment advice.

▶ Run in Python

Data Inspector

Median outcome$0

5th percentile$0

95th percentile$0

Governing equation

S_{t + Δ t} = S_{t} e^{(0.07 - \frac{0. 2 ^{2}}{2}) Δ t + 0.2 Δ t Z}, \tilde{S}_{1} \approx $0

Reading this result: Median outcome is about $0, just under the drift-only $107 — GBM compounds in log-space, so volatility always pulls the typical path below the average.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

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Amortization

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Loan / Mortgage AmortizationLive

where each payment goes

Controls

Presets

Loan amount ($)

Interest rate (APR)

Term (years)

A fixed-rate loan has a level monthly payment, but its split shifts over time: early payments are mostly interest, later ones mostly principal. That is why paying extra early, or choosing a shorter term, saves so much interest. Educational tool, not financial advice.

▶ Run in Python

Data Inspector

Monthly payment$2,212

Total interest$446,406

Total paid$796,406

Governing equation

M = P \frac{i ( 1 + i ) ^{n}}{( 1 + i ) ^{n} - 1}, P = $350, 000, i = 0.00542, n = 360, M = $2, 212

Reading this result: At 6.50% APR over 30 years, the monthly payment is $2,212 and you pay $446,406 in interest — about 128% of the amount borrowed. The payment is level, but its split shifts: your first payment is mostly interest (86% of it), while the last is almost all principal. A higher rate or a longer term sharply raises the total interest, and paying extra early attacks principal before interest can accrue on it.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

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About this simulation

The full Retirement Planner tool models a portfolio rebalance with the same numerics engineers and scientists use — running entirely client-side. Change any parameter and the result updates in real time, so you can build intuition, check a design, or teach the concept without spreadsheets or installs.

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Other ways to simulate a portfolio rebalance

Black-Scholes for a portfolio rebalance Option Payoff for a portfolio rebalance Monte Carlo (GBM) for a portfolio rebalance Efficient Frontier for a portfolio rebalance Value at Risk for a portfolio rebalance Bond Pricing for a portfolio rebalance

Frequently asked questions

How do I simulate a portfolio rebalance?: Open this page and use the live Retirement Planner tool below — set your inputs and the simulation runs instantly in your browser using real numerics. No install, no account needed.
Is it free?: Yes. The simulation runs free in your browser. A one-time unlock or a Pro plan adds advanced parameters, saved presets, data import, and clean exports.
Can I use my own numbers?: Absolutely — every input is adjustable, and with data import you can drive a portfolio rebalance from your own measurements.