How do I simulate a subsidy?

Open this page and use the live Project Portfolio 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 subsidy from your own measurements.

Use case · powered by Project Portfolio

Project Portfolio for a subsidy

Simulate a subsidy live in your browser. This runs the real Project Portfolio 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

Critical Path

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Critical Path MethodLive

project scheduling

Controls

Presets

Task B duration (days)

Task D duration (days)

The Critical Path Method finds the longest chain of dependent tasks through a project — the sequence that sets the minimum completion time. Tasks on it have zero slack: delay any one and the whole project slips. Tasks off it can float. Stretch task B or D and watch the critical path re-route. The backbone of project management.

▶ Run in Python

Data Inspector

Project duration15 days

Critical tasksA, B, D, F

Tasks6

Reading this result: The critical path is A → B → D → F at 15 days. Tasks C, E carry slack — delaying them will not move the finish date, but any slip on a critical task pushes the whole project.

Governing equation

T = paths max i \sum d_{i} = 15 days, slack_{i} = L S_{i} - E S_{i}

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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About this simulation

The full Project Portfolio tool models a subsidy 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.

More you can do with Project Portfolio

Project Portfolio for a supply-demand market Project Portfolio for a monopoly Project Portfolio for an auction Project Portfolio for a tax policy Project Portfolio for a trade tariff Project Portfolio for an inflation model Project Portfolio for a labor market Project Portfolio for a game-theory standoff

Other ways to simulate a subsidy

Supply & Demand for a subsidy Price Elasticity for a subsidy Monopoly Pricing for a subsidy Cobb-Douglas for a subsidy Lorenz & Gini for a subsidy Laffer Curve for a subsidy

Frequently asked questions

How do I simulate a subsidy?: Open this page and use the live Project Portfolio 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 subsidy from your own measurements.