What is the Rebalancing Strategy multi-solver?

Rebalancing Strategy is a guided workflow that chains 2 individual PolySim solvers into one end-to-end analysis, piping each result into the next step.

Yes. Every step runs entirely in your browser using real numerics — no install, no account, no cloud cost. Custom or private solver packs are available as a paid service.

Finance & Quant Pack · Multi-Solver

Rebalancing Strategy

Drift & cost. This multi-solver chains 2 solvers into a single guided workflow — run each step in order and carry the result forward.

Workflow steps

or unlock everything with Pro →

Efficient Frontier

open full solver →

Efficient FrontierLive

Markowitz portfolio theory

Controls

Presets

Asset A return

Asset A volatility

Asset B return

Asset B volatility

Correlation

Combining two assets traces a curved frontier of risk versus return. Because they are not perfectly correlated, some mixes have lower risk than either asset alone — the power of diversification. The pink point is the minimum-variance portfolio. Educational tool, not investment advice.

▶ Run in Python

Data Inspector

Min-var weight A0%

Min-var return0.0%

Min-var volatility0.0%

Governing equation

σ_{p}^{2} = w^{2} σ_{A}^{2} + (1 - w)^{2} σ_{B}^{2} + 2 w (1 - w) ρ σ_{A} σ_{B}, ρ = 0.20, w^{*} = 0%

Reading this result: The assets differ sharply in volatility, so the minimum-variance blend leans heavily toward the calmer one to hold total risk down.

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

↓

Monte Carlo

open full solver →

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.

Need a private, branded version?

We build custom solvers and workflows for labs, firms, agencies, and courses — your parameters, your branding, your data.

Explore Custom Solver Sets →

More in the Finance & Quant pack

Portfolio Builder Retirement Planner Mortgage Optimizer Fixed-Income Suite Dividend Growth Model College Savings Emergency Fund Planner Real-Estate Analyzer

Frequently asked questions

What is the Rebalancing Strategy multi-solver?: Rebalancing Strategy is a guided workflow that chains 2 individual PolySim solvers into one end-to-end analysis, piping each result into the next step.
Is it free to use?: Yes. Every step runs entirely in your browser using real numerics — no install, no account, no cloud cost. Custom or private solver packs are available as a paid service.